Expression of Alternative Splice Variants of 6-Phosphofructo-2-kinase/Fructose-2,6-bisphosphatase-4 in Normoxic and Hypoxic Melanoma Cells

Cancer-specific isoenzyme of phosphofructokinase II (PFKFB4), as our previous research has shown, may be one of the most important enzymes contributing to the intensification of glycolysis in hypoxic malignant melanoma cells. Although the PFKFB4 gene seems to play a crucial role in the progression of melanoma, so far there are no complete data on the expression of PFKFB4 at the isoform level and the influence of hypoxia on alternative splicing. Using RT-qPCR and semi-quantitative RT-PCR, we presented the PFKFB4 gene expression profile at the level of six isoforms described in the OMIM NCBI database in normoxic and hypoxic melanoma cells. Additionally, using VMD software, we analyzed the structure of isoforms at the protein level, concluding about the catalytic activity of individual isoforms. Our research has shown that five isoforms of PFKFB4 are expressed in melanoma cells, of which the D and F isoforms are highly constitutive, while the canonical B isoform seems to be the main isoform induced in hypoxia. Our results also indicate that the expression profile at the level of the PFKFB4 gene does not reflect the expression at the level of individual isoforms. Our work clearly indicates that the PFKFB4 gene expression profile should be definitely analyzed at the level of individual isoforms. Moreover, the analysis at the protein level allowed the selection of those isoforms whose functional validation should be performed to fully understand the importance of PFKFB4 expression in the metabolic adaptation of malignant melanoma cells.

A concise critique on Breast Cancer: A historical and scientific perspective

Breast cancer, the most pervasive cancer afflicting 2.1 million women worldwide, contributes to the highest number of cancer deaths in women. It can affect both genders, but it is more prevalent in women than in men. It seems to be the major unbearable global cancer burden. As a result, it creates a great impact on society. The exact etiology is still mysterious, but its associated risk factors were evidently identified. Although there are several sophisticated treatments available, continuing changes in the breast cancer prognosis culminated in more than 60 % of mortalities from this metastatic disease. Therefore, in an attempt to offer a clear picture of this enigmatic condition, this review outlines a concise summary of the breast cancer history, epidemiology, types, available treatments, genomics role, signaling pathways as well as its alternative splice variants.

Alternative Splicing of Pre-mRNA in the Control of Immune Activity

The human immune response is a complex process that responds to numerous exogenous antigens in preventing infection by microorganisms, as well as to endogenous components in the surveillance of tumors and autoimmune diseases, and a great number of molecules are necessary to carry the functional complexity of immune activity. Alternative splicing of pre-mRNA plays an important role in immune cell development and regulation of immune activity through yielding diverse transcriptional isoforms to supplement the function of limited genes associated with the immune reaction. In addition, multiple factors have been identified as being involved in the control of alternative splicing at the cis, trans, or co-transcriptional level, and the aberrant splicing of RNA leads to the abnormal modulation of immune activity in infections, immune diseases, and tumors. In this review, we summarize the recent discoveries on the generation of immune-associated alternative splice variants, clinical disorders, and possible regulatory mechanisms. We also discuss the immune responses to the neoantigens produced by alternative splicing, and finally, we issue some alternative splicing and immunity correlated questions based on our knowledge.

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants

Background Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers. Results Transcriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype. Conclusions Using a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.

Alternative splice variants and germline polymorphisms in human immunoglobulin light chain genes

ABSTRACTImmunoglobulin loci are rich in germline polymorphisms and identification of novel polymorphic variants can be facilitated by germline inference of B cell receptor repertoires. Germline gene inference is complicated by somatic hypermutations, errors arising from PCR amplification, and DNA sequencing as well as from the varying length of reference alleles. Inference of light chain genes is even more challenging than inference of heavy chain genes due to large gene duplication events on the kappa locus as well as absence of D genes in the rearranged light chain transcripts. Here, we analyzed the light chain cDNA sequences from naïve BCR repertoires of a Norwegian cohort of 100 individuals. We optimized light chain allele inference by tweaking parameters within TIgGER functions, extending the germline reference sequences, and establishing mismatch frequency patterns at polymorphic positions to filter out false positive candidates. As a result, we identified 48 previously unreported variants of light chain variable genes. Altogether, we selected 14 candidates for novel light chain polymorphisms for validation and successfully validated 11 by Sanger sequencing. Additional clustering of light chain 5’UTR, L-PART1 and L-PART2 revealed partial intron retention in alternative splice variants in 11 kappa and 9 lambda V alleles. The alternatively spliced transcripts were only observed in genes with low expression levels, suggesting a possible role in expression regulation. Our results provide novel insight into germline variation in human light chain immunoglobulin loci.

Roles of developmentally regulated KIF2A alternative isoforms in cortical neuron migration and differentiation

ABSTRACTKIF2A is a kinesin motor protein with essential roles in neural progenitor division and axonal pruning during brain development. However, how different KIF2A alternative isoforms function during development of the cerebral cortex is not known. Here, we focus on three Kif2a isoforms expressed in the developing cortex. We show that Kif2a is essential for dendritic arborization in mice and that the functions of all three isoforms are sufficient for this process. Interestingly, only two of the isoforms can sustain radial migration of cortical neurons; a third isoform, lacking a key N-terminal region, is ineffective. By proximity-based interactome mapping for individual isoforms, we identify previously known KIF2A interactors, proteins localized to the mitotic spindle poles and, unexpectedly, also translation factors, ribonucleoproteins and proteins that are targeted to organelles, prominently to the mitochondria. In addition, we show that a KIF2A mutation, which causes brain malformations in humans, has extensive changes to its proximity-based interactome, with depletion of mitochondrial proteins identified in the wild-type KIF2A interactome. Our data raises new insights about the importance of alternative splice variants during brain development.

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants

ABSTRACTBackgroundBreast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been successfully used to classify breast tumours into 5 major types with different prognosis and sensitivity to specific treatments. Unfortunately, these profiles have failed to subclassify breast tumours into more subtypes to improve diagnostics and survival rate. Alternative splicing is emerging as a new source of highly specific biomarkers to classify tumours in different grades. Taking advantage of extensive public transcriptomics datasets in breast cancer cell lines (CCLE) and breast cancer tumours (TCGA), we have addressed the capacity of alternative splice variants to subclassify highly aggressive breast cancers.ResultsTranscriptomics analysis of alternative splicing events between luminal, basal A and basal B breast cancer cell lines identified a unique splicing signature for a subtype of tumours, the basal B, whose classification is not in use in the clinic yet. Basal B cell lines, in contrast with luminal and basal A, are highly metastatic and express epithelial-to-mesenchymal (EMT) markers, which are hallmarks of cell invasion and resistance to drugs. By developing a semi-supervised machine learning approach, we transferred the molecular knowledge gained from these cell lines into patients to subclassify basal-like triple negative tumours into basal A- and basal B-like categories. Changes in splicing of 25 alternative exons, intimately related to EMT and cell invasion such as ENAH, CD44 and CTNND1, were sufficient to identify the basal-like patients with the worst prognosis. Moreover, patients expressing this basal B-specific splicing signature also expressed newly identified biomarkers of metastasis-initiating cells, like CD36, supporting a more invasive phenotype for this basal B-like breast cancer subtype.ConclusionsUsing a novel machine learning approach, we have identified an EMT-related splicing signature capable of subclassifying the most aggressive type of breast cancer, which are basal-like triple negative tumours. This proof-of-concept demonstrates that the biological knowledge acquired from cell lines can be transferred to patients data for further clinical investigation. More studies, particularly in 3D culture and organoids, will increase the accuracy of this transfer of knowledge, which will open new perspectives into the development of novel therapeutic strategies and the further identification of specific biomarkers for drug resistance and cancer relapse.

Splice variants of RAS—translational significance

One of the mechanisms potentially explaining the discrepancy between the number of human genes and the functional complexity of organisms is generating alternative splice variants, an attribute of the vast majority of multi-exon genes. Members of the RAS family, such as NRAS, KRAS and HRAS, all of which are of significant importance in cancer biology, are no exception. The structural and functional differences of these splice variants, particularly if they contain the canonical (and therefore routinely targeted for diagnostic purposes) hot spot mutations, pose a significant challenge for targeted therapies. We must therefore consider whether these alternative splice variants constitute a minor component as originally thought and how therapies targeting the canonical isoforms affect these alternative splice variants and their overall functions.