scholarly journals Splicing Regulation: A Molecular Device to Enhance Cancer Cell Adaptation

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Vittoria Pagliarini ◽  
Chiara Naro ◽  
Claudio Sette
Keyword(s):  
Cancer Cells ◽  
Splice Variants ◽  
Growth Conditions ◽  
Splicing Regulation ◽  
Molecular Device ◽  
Splice Isoforms ◽  
Regulate Gene Expression ◽  
Human Genes ◽  
Harsh Conditions ◽  
Coding Potential

Alternative splicing (AS) represents a major resource for eukaryotic cells to expand the coding potential of their genomes and to finely regulate gene expression in response to both intra- and extracellular cues. Cancer cells exploit the flexible nature of the mechanisms controlling AS in order to increase the functional diversity of their proteome. By altering the balance of splice isoforms encoded by human genes or by promoting the expression of aberrant oncogenic splice variants, cancer cells enhance their ability to adapt to the adverse growth conditions of the tumoral microenvironment. Herein, we will review the most relevant cancer-related splicing events and the underlying regulatory mechanisms allowing tumour cells to rapidly adapt to the harsh conditions they may face during the occurrence and development of cancer.

scholarly journals Dissecting splicing decisions and cell-to-cell variability with designed sequence libraries

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Martin Mikl ◽  
Amit Hamburg ◽  
Yitzhak Pilpel ◽  
Eran Segal
Keyword(s):  
Secondary Structure ◽  
Single Cell ◽  
Splicing Regulation ◽  
Splice Isoforms ◽  
Cause And Effect ◽  
Human Genes ◽  
Large Expansion ◽  
Alternatively Spliced ◽  
Protein Splice ◽  
Cell To Cell Variability

Abstract Most human genes are alternatively spliced, allowing for a large expansion of the proteome. The multitude of regulatory inputs to splicing limits the potential to infer general principles from investigating native sequences. Here, we create a rationally designed library of >32,000 splicing events to dissect the complexity of splicing regulation through systematic sequence alterations. Measuring RNA and protein splice isoforms allows us to investigate both cause and effect of splicing decisions, quantify diverse regulatory inputs and accurately predict (R2 = 0.73–0.85) isoform ratios from sequence and secondary structure. By profiling individual cells, we measure the cell-to-cell variability of splicing decisions and show that it can be encoded in the DNA and influenced by regulatory inputs, opening the door for a novel, single-cell perspective on splicing regulation.

scholarly journals Dissecting splicing decisions and cell-to-cell variability with designed sequence libraries

2018 ◽  
Author(s):  
Martin Mikl ◽  
Amit Hamburg ◽  
Yitzhak Pilpel ◽  
Eran Segal
Keyword(s):  
Secondary Structure ◽  
Single Cell ◽  
Splicing Regulation ◽  
Splice Isoforms ◽  
Human Genes ◽  
Large Expansion ◽  
Alternatively Spliced ◽  
Protein Splice ◽  
Cell To Cell Variability

AbstractMost human genes are alternatively spliced, allowing for a large expansion of the proteome.The multitude of regulatory inputs to splicing limits the potential to infer general principles from investigating native sequences. Here, we created a rationally designed library of >32,000 splicing events to dissect the complexity of splicing regulation through systematicsequence alterations. Measuring RNA and protein splice isoforms allowed us to investigate bothcause and effect of splicing decisions, quantify diverse regulatory inputs and accurately predict (R2=0.75–0.85) isoform ratios from sequence and secondary structure. By profiling individual cells, we measure the cell-to-cell variability of splicing decisions and show that it can be encoded in the DNA and influenced by regulatory inputs, opening the door for a novel,single-cell perspective on splicing regulation.

scholarly journals Distinctive Prognostic Value and Cellular Functions of Osteopontin Splice Variants in Human Gastric Cancer

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1820
Author(s):  
Chengcheng Hao ◽  
Yuxin Cui ◽  
Jane Lane ◽  
Shuqin Jia ◽  
Jiafu Ji ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Cells ◽  
Cell Lines ◽  
Prognostic Value ◽  
Splice Variants ◽  
Tnm Staging ◽  
Migration And Invasion ◽  
Ros Production ◽  
Gastric Cancer Cells ◽  
Normal Tissues

Background: Osteopontin (OPN) splice variants are identified as predictors of tumour progression and therapeutic resistance in certain types of solid tumours. However, their roles in gastric cancer (GC) remain poorly characterized. The current study sought to assess the prognostic value of the three OPN splice variants (namely OPN-a, OPN-b, and OPN-c) in gastric cancer and their potential functions within gastric cancer cells. Methods: RNA extraction and reverse transcription were performed using our clinical cohort of gastric carcinomas and matched normal tissues (n = 324 matched pairs). Transcript levels were determined using real-time quantitative PCR. Three OPN splice variants overexpressed cell lines were created from the gastric cancer cell line HGC-27. Subsequently, biological functions, including cell growth, adhesion, migration, and invasion, were studied. The potential effects of OPN isoforms on cisplatin and 5-Fu were evaluated by detecting cellular reactive oxygen species (ROS) levels in the HGC-27-derived cell lines. Results: Compared with normal tissues, the expression levels of three splice variants were all elevated in gastric cancer tissues in an order of OPN-a > OPN-b > OPN-c. The OPN-a level significantly increased with increasing TNM staging and worse clinical outcome. There appeared to be a downregulation for OPN-c in increasing lymph node status (p < 0.05), increasing TNM staging, and poor differentiation. High levels of OPN-a and OPN-b were correlated with short overall survival and disease-free survival of gastric cancer patients. However, the low expression of OPN-c was significantly associated with a poor prognosis. Functional analyses further showed that ectopic expression of OPN-c suppressed in vitro proliferation, adhesiveness, migration, and invasion properties of HGC-27 cells, while the opposite role was seen for OPN-a. Cellular ROS detection indicated that OPN-a and OPN-c significantly promoted ROS production after treatment with 5-Fu comparing to OPN-vector, while only OPN-a markedly induced ROS production after treatment with cisplatin. Conclusion: Our results suggest that OPN splice variants have distinguished potential to predict the prognosis of gastric cancer. Three OPN variants exert distinctive functions in gastric cancer cells. Focusing on specific OPN isoforms could be a novel direction for developing diagnostic and therapeutic approaches in gastric cancer.

scholarly journals Differential Expression of BARD1 Isoforms in Melanoma

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 320
Author(s):  
Lorissa I. McDougall ◽  
Ryan M. Powell ◽  
Magdalena Ratajska ◽  
Chi F. Lynch-Sutherland ◽  
Sultana Mehbuba Hossain ◽  
...  
Keyword(s):  
Long Range ◽  
Patient Outcomes ◽  
Splice Variants ◽  
Significant Proportion ◽  
Nanopore Sequencing ◽  
Rna Seq ◽  
Splice Isoforms ◽  
Tissue Samples ◽  
Multiple Transcripts ◽  
Mrna Variants

Melanoma comprises <5% of cutaneous malignancies, yet it causes a significant proportion of skin cancer-related deaths worldwide. While new therapies for melanoma have been developed, not all patients respond well. Thus, further research is required to better predict patient outcomes. Using long-range nanopore sequencing, RT-qPCR, and RNA sequencing analyses, we examined the transcription of BARD1 splice isoforms in melanoma cell lines and patient tissue samples. Seventy-six BARD1 mRNA variants were identified in total, with several previously characterised isoforms (γ, φ, δ, ε, and η) contributing to a large proportion of the expressed transcripts. In addition, we identified four novel splice events, namely, Δ(E3_E9), ▼(i8), IVS10+131▼46, and IVS10▼176, occurring in various combinations in multiple transcripts. We found that short-read RNA-Seq analyses were limited in their ability to predict isoforms containing multiple non-contiguous splicing events, as compared to long-range nanopore sequencing. These studies suggest that further investigations into the functional significance of the identified BARD1 splice variants in melanoma are warranted.

scholarly journals Regulation of Multiple Core Spliceosomal Proteins by Alternative Splicing-Coupled Nonsense-Mediated mRNA Decay

2008 ◽  
Vol 28 (13) ◽  
pp. 4320-4330 ◽  
Author(s):  
Arneet L. Saltzman ◽  
Yoon Ki Kim ◽  
Qun Pan ◽  
Matthew M. Fagnani ◽  
Lynne E. Maquat ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Mrna Decay ◽  
Splice Variants ◽  
Cellular Functions ◽  
Regulate Gene Expression ◽  
Premature Termination Codons ◽  
Microarray Profiling ◽  
Nonsense Mediated Mrna Decay ◽  
Regulate Gene

ABSTRACT Alternative splicing (AS) can regulate gene expression by introducing premature termination codons (PTCs) into spliced mRNA that subsequently elicit transcript degradation by the nonsense-mediated mRNA decay (NMD) pathway. However, the range of cellular functions controlled by this process and the factors required are poorly understood. By quantitative AS microarray profiling, we find that there are significant overlaps among the sets of PTC-introducing AS events affected by individual knockdown of the three core human NMD factors, Up-Frameshift 1 (UPF1), UPF2, and UPF3X/B. However, the levels of some PTC-containing splice variants are less or not detectably affected by the knockdown of UPF2 and/or UPF3X, compared with the knockdown of UPF1. The intron sequences flanking the affected alternative exons are often highly conserved, suggesting important regulatory roles for these AS events. The corresponding genes represent diverse cellular functions, and surprisingly, many encode core spliceosomal proteins and assembly factors. We further show that conserved, PTC-introducing AS events are enriched in genes that encode core spliceosomal proteins. Where tested, altering the expression levels of these core spliceosomal components affects the regulation of PTC-containing splice variants from the corresponding genes. Together, our results show that AS-coupled NMD can have different UPF factor requirements and is likely to regulate many general components of the spliceosome. The results further implicate general spliceosomal components in AS regulation.

scholarly journals Glucose Signaling Pathway and Growth Conditions Regulate Gene Expression in Retrotransposon Ty2

2009 ◽  
Vol 64 (7-8) ◽  
pp. 526-532 ◽  
Author(s):  
Sezai Türkel ◽  
Özgür Bayram ◽  
Elif Arık
Keyword(s):  
Gene Expression ◽  
Growth Conditions ◽  
Glucose Sensors ◽  
Yeast Cells ◽  
Growth Stages ◽  
Regulate Gene Expression ◽  
Glucose Signaling ◽  
Yeast Cultures ◽  
Membrane Bound ◽  
High Level

Gene expression in the yeast retrotransposon Ty2 is regulated at transcriptional and translational levels. In this study, we have shown that the transcription of Ty2 is partially dependent on the membrane-bound glucose sensors Gpr1p and Mth1p in Saccharomyces cerevisiae. Transcription of Ty2 decreased approx. 3-fold in the gpr1, mth1 yeast mutant. Moreover, our results revealed that the transcription of Ty2 fluctuates during the growth stages of S. cerevisae. Both transcription and the frameshift rate of Ty2 rapidly dropped when the stationary stage yeast cells were inoculated into fresh medium. There was an instant activation of Ty2 transcription and a high level expression during the entire logarithmic stage of yeast growth. However, the transcription of Ty2 decreased 2-fold when the yeast cultures entered the stationary stage. The frameshift rate in Ty2 also varied depending on the growth conditions. The highest frameshift level was observed during the mid-logarithmic stage. It decreased up to 2-fold during the stationary stage. Furthermore, we have found that the frameshift rate of Ty2 diminished at least 5-fold in slowly growing yeasts. These results indicate that the transcription and the frameshift efficiency are coordinately regulated in the retrotransposon Ty2 depending on the growth conditions of S. cerevisiae.

scholarly journals Insights into Telomerase/hTERT Alternative Splicing Regulation Using Bioinformatics and Network Analysis in Cancer

Cancers ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 666 ◽  
Author(s):  
Andrew T. Ludlow ◽  
Aaron L. Slusher ◽  
Mohammed E. Sayed
Keyword(s):  
Alternative Splicing ◽  
Cancer Cells ◽  
Rna Processing ◽  
Splicing Regulation ◽  
Cancer Cell Growth ◽  
Growth And Survival ◽  
Htert Gene ◽  
Splicing Variants ◽  
Cis And Trans ◽  
Telomerase Regulation

The reactivation of telomerase in cancer cells remains incompletely understood. The catalytic component of telomerase, hTERT, is thought to be the limiting component in cancer cells for the formation of active enzymes. hTERT gene expression is regulated at several levels including chromatin, DNA methylation, transcription factors, and RNA processing events. Of these regulatory events, RNA processing has received little attention until recently. RNA processing and alternative splicing regulation have been explored to understand how hTERT is regulated in cancer cells. The cis- and trans-acting factors that regulate the alternative splicing choice of hTERT in the reverse transcriptase domain have been investigated. Further, it was discovered that the splicing factors that promote the production of full-length hTERT were also involved in cancer cell growth and survival. The goals are to review telomerase regulation via alternative splicing and the function of hTERT splicing variants and to point out how bioinformatics approaches are leading the way in elucidating the networks that regulate hTERT splicing choice and ultimately cancer growth.

Next-generation sequencing reveals alternative L-DOPA decarboxylase (DDC) splice variants bearing novel exons, in human hepatocellular and lung cancer cells

Gene ◽  
2021 ◽  
Vol 768 ◽  
pp. 145262 ◽  
Author(s):  
Maria Papatsirou ◽  
Panagiotis G. Adamopoulos ◽  
Pinelopi I. Artemaki ◽  
Vasiliki P. Georganti ◽  
Andreas Scorilas ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Next Generation Sequencing ◽  
Cancer Cells ◽  
Splice Variants ◽  
Lung Cancer Cells ◽  
Dopa Decarboxylase ◽  
Next Generation ◽  
Generation Sequencing
Sign in / Sign up

Export Citation Format

Share Document