Transcriptome characterization by RNA sequencing identifies a major molecular and clinical subdivision in chronic lymphocytic leukemia

Multiple omics levels of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a lymphoproliferative malignancy characterized by the proliferation of functionally mature but incompetent B cells. It is the most prevalent type of leukemia in Western populations, accounting for approximately 25% of new leukemia cases. While recent advances, such as ibrutinib and venetoclax treatment have improved patient outlook, aggressive forms of CLL such as Richter transformation still pose a significant challenge. This discrepancy may be due to the heterogeneity of factors contributing to CLL development at multiple -omics levels. However, information on the omics of CLL is fragmented, hindering multi-omics-based research into potential treatment options. To address this, we aggregated and presented a selection of important aspects of various omics levels of the disease in this review. The purpose of the present literature analysis is to portray examples of CLL studies from different omics levels, including genomics, epigenomics, transcriptomics, epitranscriptomics, proteomics, epiproteomics, metabolomics, glycomics and lipidomics, as well as those identified by multi-omics approaches. The review includes the list of 102 CLL-associated genes with relevant genomics information. While single-omics studies yield substantial and useful data, they omit a significant level of complex biological interplay present in the disease. As multi-omics studies integrate several different layers of data, they may be better suited for complex diseases such as CLL and have thus far yielded promising results. Future multi-omics studies may assist clinicians in improved treatment choices based on CLL subtypes as well as allow the identification of novel biomarkers and targets for treatments.

Aberrant spliceosome activity via elevated intron retention and upregulation and phosphorylation of SF3B1 in chronic lymphocytic leukemia

Splicing factor 3b subunit 1 (SF3B1) is the largest subunit and core component of the spliceosome. Inhibition of SF3B1 was associated with an increase in broad intron retention (IR) on most transcripts, suggesting that IR can be used as a marker of spliceosome inhibition in chronic lymphocytic leukemia (CLL) cells. Furthermore, we separately analyzed exonic and intronic mapped reads on annotated RNA-sequencing transcripts obtained from B cells (n = 98 CLL patients) and healthy volunteers (n = 9). We measured intron/exon ratio to use that as a surrogate for alternative RNA splicing (ARS) and found that 66% of CLL-B cell transcripts had significant IR elevation compared with normal B cells (NBCs) and that correlated with mRNA downregulation and low expression levels. Transcripts with the highest IR levels belonged to biological pathways associated with gene expression and RNA splicing. A >2-fold increase of active pSF3B1 was observed in CLL-B cells compared with NBCs. Additionally, when the CLL-B cells were treated with macrolides (pladienolide-B), a significant decrease in pSF3B1, but not total SF3B1 protein, was observed. These findings suggest that IR/ARS is increased in CLL, which is associated with SF3B1 phosphorylation and susceptibility to SF3B1 inhibitors. These data provide additional support to the relevance of ARS in carcinogenesis and evidence of pSF3B1 participation in this process.

B cell receptor signaling proteins as biomarkers for progression of CLL requiring first-line therapy

The molecular landscape of chronic lymphocytic leukemia (CLL) has been extensively characterized, and various potent prognostic biomarkers were discovered. The genetic composition of the B-cell receptor (BCR) immunoglobulin (IG) was shown to be especially powerful for discerning indolent from aggressive disease at diagnosis. Classification based on the IG heavy chain variable gene (IGHV) somatic hypermutation status is routinely applied. Additionally, BCR IGH stereotypy has been implicated to improve risk stratification, through characterization of subsets with consistent clinical profiles. Despite these advances, it remains challenging to predict when CLL progresses to requiring first-line therapy, thus emphasizing the need for further refinement of prognostic indicators. Signaling pathways downstream of the BCR are essential in CLL pathogenesis, and dysregulated components within these pathways impact disease progression. Considering not only genomics but the entirety of factors shaping BCR signaling activity, this review offers insights in the disease for better prognostic assessment of CLL.

Non-canonical transcriptional regulation of the poor prognostic factor UGT2B17 in chronic lymphocytic leukemic and normal B cells

BACKGROUND

High expression of the glycosyltransferase UGT2B17 represents an independent adverse prognostic marker in chronic lymphocytic leukemia (CLL). It also constitutes a predictive marker for therapeutic response and a drug resistance mechanism. The key determinants driving expression of the UGT2B17 gene in normal and leukemic B-cells remain undefined. The UGT2B17 transcriptome is complex and is comprised of at least 10 alternative transcripts, identified by previous RNA-sequencing of liver and intestine. We hypothesized that the transcriptional program regulating UGT2B17 in B-lymphocytes is distinct from the canonical expression previously characterized in the liver.

RESULTS

RNA-sequencing and genomics data revealed a specific genomic landscape at the UGT2B17 locus in normal and leukemic B-cells. RNA-sequencing and quantitative PCR data indicated that the UGT2B17 enzyme is solely encoded by alternative transcripts expressed in CLL patient cells and not by the canonical transcript widely expressed in the liver and intestine. Chromatin accessible regions (ATAC-Seq) in CLL cells mapped with alternative promoters and non-coding exons, which may be derived from endogenous retrotransposon elements. By luciferase reporter assays, we identified key cis-regulatory STAT3, RELA and interferon regulatory factor (IRF) binding sequences driving the expression of UGT2B17 in lymphoblastoid and leukemic B-cells. Electrophoretic mobility shift assays and pharmacological inhibition demonstrated key roles for the CLL prosurvival transcription factors STAT3 and NF-κB in the leukemic expression of UGT2B17.

CONCLUSIONS

UGT2B17 expression in B-CLL is driven by key regulators of CLL progression. Our data suggest that a NF-κB/STAT3/IRF/UGT2B17 axis may represent a novel B-cell pathway promoting disease progression and drug resistance.

StellarPath: Hierarchical-vertical multi-omics classifier synergizes stable markers and interpretable similarity networks for patient profiling

The Patient Similarity Network paradigm implies modeling the similarity between patients based on specific data. The similarity can summarize patients' relationships from high-dimensional data, such as biological omics. The end PSN can undergo un/supervised learning tasks while being strongly interpretable, tailored for precision medicine, and ready to be analyzed with graph-theory methods. However, these benefits are not guaranteed and depend on the granularity of the summarized data, the clarity of the similarity measure, the complexity of the network's topology, and the implemented methods for analysis. To date, no patient classifier fully leverages the paradigm's inherent benefits. PSNs remain complex, unexploited, and meaningless. We present StellarPath, a hierarchical-vertical patient classifier that leverages pathway analysis and patient similarity concepts to find meaningful features for both classes and individuals. StellarPath processes omics data, hierarchically integrates them into pathways, and uses a novel similarity to measure how patients' pathway activity is alike. It selects biologically relevant molecules, pathways, and networks, considering molecule stability and topology. A graph convolutional neural network then predicts unknown patients based on known cases. StellarPath excels in classification performances and computational resources across sixteen datasets. It demonstrates proficiency in inferring the class of new patients described in external independent studies, following its initial training and testing phases on a local dataset. It advances the PSN paradigm and provides new markers, insights, and tools for in-depth patient profiling.

Comparison of RNA-Seq and microarray in the prediction of protein expression and survival prediction

Gene expression profiling using RNA-sequencing (RNA-seq) and microarray technologies is widely used in cancer research to identify biomarkers for clinical endpoint prediction. We compared the performance of these two methods in predicting protein expression and clinical endpoints using The Cancer Genome Atlas (TCGA) datasets of lung cancer, colorectal cancer, renal cancer, breast cancer, endometrial cancer, and ovarian cancer. We calculated the correlation coefficients between gene expression measured by RNA-seq or microarray and protein expression measured by reverse phase protein array (RPPA). In addition, after selecting the top 103 survival-related genes, we compared the random forest survival prediction model performance across test platforms and cancer types. Both RNA-seq and microarray data were retrieved from TCGA dataset. Most genes showed similar correlation coefficients between RNA-seq and microarray, but 16 genes exhibited significant differences between the two methods. The BAX gene was recurrently found in colorectal cancer, renal cancer, and ovarian cancer, and the PIK3CA gene belonged to renal cancer and breast cancer. Furthermore, the survival prediction model using microarray was better than the RNA-seq model in colorectal cancer, renal cancer, and lung cancer, but the RNA-seq model was better in ovarian and endometrial cancer. Our results showed good correlation between mRNA levels and protein measured by RPPA. While RNA-seq and microarray performance were similar, some genes showed differences, and further clinical significance should be evaluated. Additionally, our survival prediction model results were controversial.

m6A-Modified circTET2 Interacting with HNRNPC Regulates Fatty Acid Oxidation to Promote the Proliferation of Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a hematological malignancy with high metabolic heterogeneity. N6-methyladenosine (m6A) modification plays an important role in metabolism through regulating circular RNAs (circRNAs). However, the underlying mechanism is not yet fully understood in CLL. Herein, an m6A scoring system and an m6A-related circRNA prognostic signature are established, and circTET2 as a potential prognostic biomarker for CLL is identified. The level of m6A modification is found to affect the transport of circTET2 out of the nucleus. By interacting with the RNA-binding protein (RBP) heterogeneous nuclear ribonucleoprotein C (HNRNPC), circTET2 regulates the stability of CPT1A and participates in the lipid metabolism and proliferation of CLL cells through mTORC1 signaling pathway. The mTOR inhibitor dactolisib and FAO inhibitor perhexiline exert a synergistic effect on CLL cells. In addition, the biogenesis of circTET2 can be affected by the splicing process and the RBPs RBMX and YTHDC1. CP028, a splicing inhibitor, modulates the expression of circTET2 and shows pronounced inhibitory effects. In summary, circTET2 plays an important role in the modulation of lipid metabolism and cell proliferation in CLL. This study demonstrates the clinical value of circTET2 as a prognostic indicator as well as provides novel insights in targeting treatment for CLL.

SF3B1 mutation-mediated sensitization to H3B-8800 splicing inhibitor in chronic lymphocytic leukemia

Splicing factor 3B subunit 1 (SF3B1) is involved in pre-mRNA branch site recognition and is the target of antitumor-splicing inhibitors. Mutations in SF3B1 are observed in 15% of patients with chronic lymphocytic leukemia (CLL) and are associated with poor prognosis, but their pathogenic mechanisms remain poorly understood. Using deep RNA-sequencing data from 298 CLL tumor samples and isogenic SF3B1 WT and K700E-mutated CLL cell lines, we characterize targets and pre-mRNA sequence features associated with the selection of cryptic 3' splice sites upon SF3B1 mutation, including an event in the MAP3K7 gene relevant for activation of NF-κB signaling. Using the H3B-8800 splicing modulator, we show, for the first time in CLL, cytotoxic effects in vitro in primary CLL samples and in SF3B1-mutated isogenic CLL cell lines, accompanied by major splicing changes and delayed leukemic infiltration in a CLL xenotransplant mouse model. H3B-8800 displayed preferential lethality towards SF3B1-mutated cells and synergism with the BCL2 inhibitor venetoclax, supporting the potential use of SF3B1 inhibitors as a novel therapeutic strategy in CLL.

MALAT1 expression is associated with aggressive behavior in indolent B-cell neoplasms

MALAT1 long non-coding RNA has oncogenic roles but has been poorly studied in indolent B-cell neoplasms. Here, MALAT1 expression was analyzed using RNA-seq, microarrays or qRT-PCR in primary samples from clinico-biological subtypes of chronic lymphocytic leukemia (CLL, n = 266), paired Richter transformation (RT, n = 6) and follicular lymphoma (FL, n = 61). In peripheral blood (PB) CLL samples, high MALAT1 expression was associated with a significantly shorter time to treatment independently from other known prognostic factors. Coding genes expressed in association with MALAT1 in CLL were predominantly related to oncogenic pathways stimulated in the lymph node (LN) microenvironment. In RT paired samples, MALAT1 levels were lower, concordant with their acquired increased independency of external signals. Moreover, MALAT1 levels in paired PB/LN CLLs were similar, suggesting that the prognostic value of MALAT1 expression in PB is mirroring expression differences already present in LN. Similarly, high MALAT1 expression in FL predicted for a shorter progression-free survival, in association with expression pathways promoting FL pathogenesis. In summary, MALAT1 expression is related to pathophysiology and more aggressive clinical behavior of indolent B-cell neoplasms. Particularly in CLL, its levels could be a surrogate marker of the microenvironment stimulation and may contribute to refine the clinical management of these patients.

Nucleosome repositioning in chronic lymphocytic leukemia

The location of nucleosomes in the human genome determines the primary chromatin structure and regulates access to regulatory regions. However, genome-wide information on deregulated nucleosome occupancy and its implications in primary cancer cells is scarce. Here, we conducted a genome-wide comparison of high-resolution nucleosome maps in peripheral blood B cells from patients with chronic lymphocytic leukemia (CLL) and healthy individuals at single-base-pair resolution. Our investigation uncovered significant changes of nucleosome positioning in CLL. Globally, the spacing between nucleosomes-the nucleosome repeat length (NRL)-is shortened in CLL. This effect is stronger in the more aggressive IGHV-unmutated CLL subtype than in the IGHV-mutated CLL subtype. Changes in nucleosome occupancy at specific sites are linked to active chromatin remodeling and reduced DNA methylation. Nucleosomes lost or gained in CLL marks differential binding of 3D chromatin organizers such as CTCF as well as immune response-related transcription factors and delineated mechanisms of epigenetic deregulation. The principal component analysis of nucleosome occupancy in cancer-specific regions allowed the classification of samples between cancer subtypes and normal controls. Furthermore, patients could be better assigned to CLL subtypes according to differential nucleosome occupancy than based on DNA methylation or gene expression. Thus, nucleosome positioning constitutes a novel readout to dissect molecular mechanisms of disease progression and to stratify patients. Furthermore, we anticipate that the global nucleosome repositioning detected in our study, such as changes in the NRL, can be exploited for liquid biopsy applications based on cell-free DNA to stratify patients and monitor disease progression.

Subgroup-specific gene expression profiles and mixed epistasis in chronic lymphocytic leukemia

Understanding the molecular and phenotypic heterogeneity of cancer is a prerequisite for effective treatment. For chronic lymphocytic leukemia (CLL), recurrent genetic driver events have been extensively cataloged, but this does not suffice to explain the disease's diverse course. Here, we performed RNA sequencing on 184 CLL patient samples. Unsupervised analysis revealed two major, orthogonal axes of gene expression variation: the first one represented the mutational status of the immunoglobulin heavy variable (IGHV) genes, and concomitantly, the three-group stratification of CLL by global DNA methylation. The second axis aligned with trisomy 12 status and affected chemokine, MAPK and mTOR signaling. We discovered non-additive effects (epistasis) of IGHV mutation status and trisomy 12 on multiple phenotypes, including the expression of 893 genes. Multiple types of epistasis were observed, including synergy, buffering, suppression and inversion, suggesting that molecular understanding of disease heterogeneity requires studying such genetic events not only individually but in combination. We detected strong differentially expressed gene signatures associated with major gene mutations and copy number aberrations including SF3B1, BRAF and TP53, as well as del(17)(p13), del(13)(q14) and del(11)(q22.3) beyond dosage effect. Our study reveals previously underappreciated gene expression signatures for the major molecular subtypes in CLL and the presence of epistasis between them.

Network analysis reveals a major role for 14q32 cluster miRNAs in determining transcriptional differences between IGHV-mutated and unmutated CLL

Chronic lymphocytic leukaemia (CLL) cells can express unmutated (U-CLL) or mutated (M-CLL) immunoglobulin heavy chain (IGHV) genes with differing clinical behaviours, variable B cell receptor (BCR) signalling capacity and distinct transcriptional profiles. As it remains unclear how these differences reflect the tumour cells' innate pre/post germinal centre origin or their BCR signalling competence, we applied mRNA/miRNA sequencing to 38 CLL cases categorised into three subsets by IGHV mutational status and BCR signalling capacity. We identified 492 mRNAs and 38 miRNAs differentially expressed between U-CLL and M-CLL, but only 9 mRNAs and 0 miRNAs associated with BCR competence within M-CLL. Of the IGHV-associated miRNAs, (14/38 (37%)) derived from chr14q32 clusters where all miRNAs were co-expressed with the MEG3 lncRNA from a cancer associated imprinted locus. Integrative analysis of miRNA/mRNA data revealed pronounced regulatory potential for the 14q32 miRNAs, potentially accounting for up to 25% of the IGHV-related transcriptome signature. GAB1, a positive regulator of BCR signalling, was potentially regulated by five 14q32 miRNAs and we confirmed that two of these (miR-409-3p and miR-411-3p) significantly repressed activity of the GAB1 3'UTR. Our analysis demonstrates a potential key role of the 14q32 miRNA locus in the regulation of CLL-related gene regulation.

Targeting splicing factors for cancer therapy

Alternative splicing (AS) of mRNAs is an essential regulatory mechanism in eukaryotic gene expression. AS misregulation, caused by either dysregulation or mutation of splicing factors, has been shown to be involved in cancer development and progression, making splicing factors suitable targets for cancer therapy. In recent years, various types of pharmacological modulators, such as small molecules and oligonucleotides, targeting distinct components of the splicing machinery, have been under development to treat multiple disorders. Although these approaches have promise, targeting the core spliceosome components disrupts the early stages of spliceosome assembly and can lead to nonspecific and toxic effects. New research directions have been focused on targeting specific splicing factors for a more precise effect. In this Perspective, we will highlight several approaches for targeting splicing factors and their functions and suggest ways to improve their specificity.

Epigenetic regulation in hematopoiesis and its implications in the targeted therapy of hematologic malignancies

Hematologic malignancies are one of the most common cancers, and the incidence has been rising in recent decades. The clinical and molecular features of hematologic malignancies are highly heterogenous, and some hematologic malignancies are incurable, challenging the treatment, and prognosis of the patients. However, hematopoiesis and oncogenesis of hematologic malignancies are profoundly affected by epigenetic regulation. Studies have found that methylation-related mutations, abnormal methylation profiles of DNA, and abnormal histone deacetylase expression are recurrent in leukemia and lymphoma. Furthermore, the hypomethylating agents and histone deacetylase inhibitors are effective to treat acute myeloid leukemia and T-cell lymphomas, indicating that epigenetic regulation is indispensable to hematologic oncogenesis. Epigenetic regulation mainly includes DNA modifications, histone modifications, and noncoding RNA-mediated targeting, and regulates various DNA-based processes. This review presents the role of writers, readers, and erasers of DNA methylation and histone methylation, and acetylation in hematologic malignancies. In addition, this review provides the influence of microRNAs and long noncoding RNAs on hematologic malignancies. Furthermore, the implication of epigenetic regulation in targeted treatment is discussed. This review comprehensively presents the change and function of each epigenetic regulator in normal and oncogenic hematopoiesis and provides innovative epigenetic-targeted treatment in clinical practice.

Expression of BCL11A in chronic lymphocytic leukaemia

INTRODUCTION

The B-cell lymphoma/leukaemia 11A (BCL11A) gene encodes a Krüppel-like transcription factor involved in lymphocyte development during normal haematopoiesis. Aberrant expression of BCL11A has been observed in several haematological malignancies, including chronic lymphocytic leukaemia (CLL). However, its functions in the regulatory networks of malignant B lymphocytes are poorly understood, as are the relations to clinical course and outcome of B-cell malignancies, particularly CLL.

METHODS

The expression of BCL11A was analysed in peripheral blood mononuclear cells of 87 newly-diagnosed CLL patients by quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR), and association with clinical and molecular variables was assessed.

RESULTS

BCL11A was significantly overexpressed in CLL samples compared to control samples (p < 0.001). BCL11A expression level exhibited no association with age, sex, leukocyte, lymphocyte and platelet counts, haemoglobin level, serum β2-microglobulin, CD38 status and cytogenetic abnormalities. On the other hand, high BCL11A expression was associated with low serum lactate dehydrogenase (p = 0.031), Binet A stage (p = 0.047) and mutated IGHV (p = 0.028). In addition, a positive correlation with BCL2/BAX mRNA ratio was observed (r = 0.36; p < 0.001). Regarding the association with the time to first treatment (TTFT), a trend towards longer median TTFT in BCL11A high- versus BCL11A low-expressing cases was detected (21 vs. 6 months; p = 0.164).

CONCLUSION

The results of this study show that BCL11A is upregulated in CLL patients, and that high BCL11A expression at diagnosis may be associated with better prognosis. These data are consistent with the role of BCL11A expression in CLL biology, and imply its potential prognostic relevance.

Transcriptome analysis of intestine from alk-SMase knockout mice reveals the effect of alk-SMase

Objective

Intestinal alkaline sphingomyelinase (alk-SMase) generates ceramide and inactivates platelet-activating factor associated with digestion and inhibition of cancer. There is few study to analyze the correlated function and characterize the genes related to alk-SMase comprehensively. We characterised transcriptome landscapes of intestine tissues from alk-SMase knockout (KO) mice aiming to identify novel associated genes and research targets.

Methods

We performed the high-resolution RNA sequencing of alk-SMase KO mice and compared them to wild type (WT) mice. Differentially expressed genes (DEGs) for the training group were screened. Functional enrichment analysis of the DEGs between KO mice and WT mice was implemented using the Database for Annotation, Visualization and Integrated Discovery (DAVID). An integrated protein–protein interaction (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) network was chose to study the relationship of differentially expressed gene. Moreover, quantitative real-time polymerase chain reaction (qPCR) was further used to validate the accuracy of RNA-seq technology.

Results

Our RNA-seq data found 97 differentially expressed mRNAs between the WT mice and alk-SMase gene NPP7 KO mice, in which 32 were significantly up-regulated and 65 were down-regulated, including protein coding genes, non-coding RNAs. Notably, the results of gene ontology functional enrichment analysis indicated that DEGs were functionally associated with the immune response, regulation of cell proliferation and development related terms. Additionally, an integrated network analysis was shown that some modules was significantly related to alk-SMase and with accordance of previously results. We chose 6 of these genes randomly were validated the accuracy of RNA-seq technology using qPCR and 2 genes showed difference significantly (P < 0.05).

Conclusions

We investigated the potential biological significant of alk-SMase with high resolution genome-wide transcriptome of alk-SMase knockout mice. The results revealed new insight into the functional modules related to alk-SMase was involved in the intestinal related diseases.

Molecular map of chronic lymphocytic leukemia and its impact on outcome

Recent advances in cancer characterization have consistently revealed marked heterogeneity, impeding the completion of integrated molecular and clinical maps for each malignancy. Here, we focus on chronic lymphocytic leukemia (CLL), a B cell neoplasm with variable natural history that is conventionally categorized into two subtypes distinguished by extent of somatic mutations in the heavy-chain variable region of immunoglobulin genes (IGHV). To build the 'CLL map,' we integrated genomic, transcriptomic and epigenomic data from 1,148 patients. We identified 202 candidate genetic drivers of CLL (109 new) and refined the characterization of IGHV subtypes, which revealed distinct genomic landscapes and leukemogenic trajectories. Discovery of new gene expression subtypes further subcategorized this neoplasm and proved to be independent prognostic factors. Clinical outcomes were associated with a combination of genetic, epigenetic and gene expression features, further advancing our prognostic paradigm. Overall, this work reveals fresh insights into CLL oncogenesis and prognostication.

Analysis of Data on Fludarabine, Cyclophosphamide, and Rituximab Chemoimmunotherapy for Chronic Lymphocytic Leukemia Shows High Patient Heterogeneity and the Need for More Consideration of Individualized Treatment

Methods

Data from single-cell RNA sequencing (RNA-seq) of CLL patients were obtained from the Gene Expression Omnibus database. The R package was utilized to analyze the data, and the relation of results was predicted via the GeneMANIA website. The information of 7 samples covered three stages: observation stage, pretreatment by CIT with rituximab, fludarabine, and cyclophosphamide (pre-CIT), and post-CIT. The differentially expressed genes (DEGs) were identified, and functional enrichment analyses were performed. B cell subpopulations and pseudotime trajectories analysis was conducted.

Results

A total of 70,659 DEGs were identified. Each patient's DEGs presented their own characteristics, with low similarity. Therefore, it is difficult to identify potential hub genes. Similarly, pathway enrichment analysis showed significant tumor heterogeneity among CLL patients. Analysis of relapsed post-CIT compared to the observation stage suggested that the TP53 pathway should be taken seriously as it is closely related to treatment strategy and patient prognosis.

Conclusions

Tumor heterogeneity may be a more common manifestation of CLL. Individualized treatment should be considered for CLL. TP53 abnormality and its regulatory factors should still be the focus of CLL diagnosis and treatment.

Integration of TE Induces Cancer Specific Alternative Splicing Events

Alternative splicing of messenger RNA (mRNA) precursors contributes to genetic diversity by generating structurally and functionally distinct transcripts. In a disease state, alternative splicing promotes incidence and development of several cancer types through regulation of cancer-related biological processes. Transposable elements (TEs), having the genetic ability to jump to other regions of the genome, can bring about alternative splicing events in cancer. TEs can integrate into the genome, mostly in the intronic regions, and induce cancer-specific alternative splicing by adjusting various mechanisms, such as exonization, providing splicing donor/acceptor sites, alternative regulatory sequences or stop codons, and driving exon disruption or epigenetic regulation. Moreover, TEs can produce microRNAs (miRNAs) that control the proportion of transcripts by repressing translation or stimulating the degradation of transcripts at the post-transcriptional level. Notably, TE insertion creates a cancer-friendly environment by controlling the overall process of gene expression before and after transcription in cancer cells. This review emphasizes the correlative interaction between alternative splicing by TE integration and cancer-associated biological processes, suggesting a macroscopic mechanism controlling alternative splicing by TE insertion in cancer.

Inferring tumor-specific cancer dependencies through integrating ex vivo drug response assays and drug-protein profiling

The development of cancer therapies may be improved by the discovery of tumor-specific molecular dependencies. The requisite tools include genetic and chemical perturbations, each with its strengths and limitations. Chemical perturbations can be readily applied to primary cancer samples at large scale, but mechanistic understanding of hits and further pharmaceutical development is often complicated by the fact that a chemical compound has affinities to multiple proteins. To computationally infer specific molecular dependencies of individual cancers from their ex vivo drug sensitivity profiles, we developed a mathematical model that deconvolutes these data using measurements of protein-drug affinity profiles. Through integrating a drug-kinase profiling dataset and several drug response datasets, our method, DepInfeR, correctly identified known protein kinase dependencies, including the EGFR dependence of HER2+ breast cancer cell lines, the FLT3 dependence of acute myeloid leukemia (AML) with FLT3-ITD mutations and the differential dependencies on the B-cell receptor pathway in the two major subtypes of chronic lymphocytic leukemia (CLL). Furthermore, our method uncovered new subgroup-specific dependencies, including a previously unreported dependence of high-risk CLL on Checkpoint kinase 1 (CHEK1). The method also produced a detailed map of the kinase dependencies in a heterogeneous set of 117 CLL samples. The ability to deconvolute polypharmacological phenotypes into underlying causal molecular dependencies should increase the utility of high-throughput drug response assays for functional precision oncology.

As survival and proliferation of cancer cells depend on molecular aberrations that can be highly specific to cancer types and individual tumors, identifying such dependence is pivotal to designing individualized tumor therapy. Chemical perturbations, through screening of bioactive compounds using primary cancer cells, provide an important tool for identifying tumor-specific dependencies. However, many chemical compounds bind multiple proteins, which complicates interpreting screening results and pinpointing the phenotype-causing target. To overcome this challenge and increase the utility of drug screening approaches for functional precision medicine, we developed a computational framework, DepInfeR, to identify tumor-specific dependencies on druggable proteins through integrating two sources of information: drug sensitivity assays and drug-protein affinity profiling. Our approach correctly identifies known kinase dependencies, which validates our approach. Furthermore, by integrating a newly generated drug screening dataset on primary tumor samples, we discovered a previously unreported survival dependence on Checkpoint kinase 1 (CHEK1) by a molecular subgroup of chronic lymphocytic leukemia samples, highlighting the clinical potential of our method.

Molecular Basis and Role of Siglec-7 Ligand Expression on Chronic Lymphocytic Leukemia B Cells

Siglec-7 (sialic acid-binding immunoglobulin-like lectin 7) is an immune checkpoint-like glycan recognition protein on natural killer (NK) cells. Cancer cells often upregulate Siglec ligands to subvert immunosurveillance, but the molecular basis of Siglec ligands has been elusive. In this study, we investigated Siglec-7 ligands on chronic lymphocytic leukemia (CLL) B cells. CLL B cells express higher levels of Siglec-7 ligands compared with healthy donor B cells, and enzymatic removal of sialic acids or sialomucins makes them more sensitive to NK cell cytotoxicity. Gene knockout experiments have revealed that the sialyltransferase ST6GalNAc-IV is responsible for the biosynthesis of disialyl-T (Neu5Acα2-3Galβ1-3[Neu5Acα2-6]GalNAcα1-), which is the glycotope recognized by Siglec-7, and that CD162 and CD45 are the major carriers of this glycotope on CLL B cells. Analysis of public transcriptomic datasets indicated that the low expression of GCNT1 (encoding core 2 GlcNAc transferase, an enzyme that competes against ST6GalNAc-IV) and high expression of ST6GALNAC4 (encoding ST6GalNAc-IV) in CLL B cells, together enhancing the expression of the disialyl-T glycotope, are associated with poor patient prognosis. Taken together, our results determined the molecular basis of Siglec-7 ligand overexpression that protects CLL B cells from NK cell cytotoxicity and identified disialyl-T as a potential prognostic marker of CLL.

The immune microenvironment shapes transcriptional and genetic heterogeneity in chronic lymphocytic leukemia

In chronic lymphocytic leukemia (CLL), B-cell receptor signaling, tumor-microenvironment interactions, and somatic mutations drive disease progression. To better understand the intersection between the microenvironment and molecular events in CLL pathogenesis, we integrated bulk transcriptome profiling of paired peripheral blood (PB) and lymph node (LN) samples from 34 patients. Oncogenic processes were upregulated in LN compared with PB and in immunoglobulin heavy-chain variable (IGHV) region unmutated compared with mutated cases. Single-cell RNA sequencing (scRNA-seq) distinguished 3 major cell states: quiescent, activated, and proliferating. The activated subpopulation comprised only 2.2% to 4.3% of the total tumor bulk in LN samples. RNA velocity analysis found that CLL cell fate in LN is unidirectional, starts in the proliferating state, transitions to the activated state, and ends in the quiescent state. A 10-gene signature derived from activated tumor cells was associated with inferior treatment-free survival (TFS) and positively correlated with the proportion of activated CD4+ memory T cells and M2 macrophages in LN. Whole exome sequencing (WES) of paired PB and LN samples showed subclonal expansion in LN in approximately half of the patients. Since mouse models have implicated activation-induced cytidine deaminase in mutagenesis, we compared AICDA expression between cases with and without clonal evolution but did not find a difference. In contrast, the presence of a T-cell inflamed microenvironment in LN was associated with clonal stability. In summary, a distinct minor tumor subpopulation underlies CLL pathogenesis and drives the clinical outcome. Clonal trajectories are shaped by the LN milieu, where T-cell immunity may contribute to suppressing clonal outgrowth. The clinical study is registered at clinicaltrials.gov as NCT00923507.

Transposable Elements and Human Diseases: Mechanisms and Implication in the Response to Environmental Pollutants

Transposable elements (TEs) are recognized as major players in genome plasticity and evolution. The high abundance of TEs in the human genome, especially the Alu and Long Interspersed Nuclear Element-1 (LINE-1) repeats, makes them responsible for the molecular origin of several diseases. This involves several molecular mechanisms that are presented in this review: insertional mutation, DNA recombination and chromosomal rearrangements, modification of gene expression, as well as alteration of epigenetic regulations. This literature review also presents some of the more recent and/or more classical examples of human diseases in which TEs are involved. Whether through insertion of LINE-1 or Alu elements that cause chromosomal rearrangements, or through epigenetic modifications, TEs are widely implicated in the origin of human cancers. Many other human diseases can have a molecular origin in TE-mediated chromosomal recombination or alteration of gene structure and/or expression. These diseases are very diverse and include hemoglobinopathies, metabolic and neurological diseases, and common diseases. Moreover, TEs can also have an impact on aging. Finally, the exposure of individuals to stresses and environmental contaminants seems to have a non-negligible impact on the epigenetic derepression and mobility of TEs, which can lead to the development of diseases. Thus, improving our knowledge of TEs may lead to new potential diagnostic markers of diseases.

Unannotated proteins expand the MHC-I-restricted immunopeptidome in cancer

Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets.

Detecting Bacterial-Human Lateral Gene Transfer in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a very common and mostly incurable B-cell malignancy. Recent studies revealed high interpatient mutational heterogeneity and worsened therapy response and survival of patients with complex genomic aberrations. In line with this, a better understanding of the underlying mechanisms of specific genetic aberrations would reveal new prognostic factors and possible therapeutic targets. It is known that chromosomal rearrangements including DNA insertions often play a role during carcinogenesis. Recently it was reported that bacteria (microbiome)–human lateral gene transfer occurs in somatic cells and is enriched in cancer samples. To further investigate this mechanism in CLL, we analyzed paired-end RNA sequencing data of 45 CLL patients and 9 healthy donors, in which we particularly searched for bacterial DNA integrations into the human somatic genome. Applying the Burrows–Wheeler aligner (BWA) first on a human genome and then on bacterial genome references, we differentiated between sequencing reads mapping to the human genome, to the microbiome or to bacterial integrations into the human genome. Our results indicate that CLL samples featured bacterial DNA integrations more frequently (approx. two-fold) compared to normal samples, which corroborates the latest findings in other cancer entities. Moreover, we determined common integration sites and recurrent integrated bacterial transcripts. Finally, we investigated the contribution of bacterial integrations to oncogenesis and disease progression.

Clonal Evolution of High-Risk Chronic Lymphocytic Leukemia: A Contemporary Perspective

Clonal evolution represents the natural process through which cancer cells continuously search for phenotypic advantages that enable them to develop and expand within microenvironmental constraints. In chronic lymphocytic leukemia (CLL), clonal evolution underpins leukemic progression and therapeutic resistance, with differences in clonal evolutionary dynamics accounting for its characteristically diverse clinical course. The past few years have witnessed profound changes in our understanding of CLL clonal evolution, facilitated by a maturing definition of high-risk CLL and an increasing sophistication of next-generation sequencing technology. In this review, we offer a modern perspective on clonal evolution of high-risk CLL, highlighting recent discoveries, paradigm shifts and unresolved questions. We appraise recent advances in our understanding of the molecular basis of CLL clonal evolution, focusing on the genetic and non-genetic sources of intratumoral heterogeneity, as well as tumor-immune dynamics. We review the technological innovations, particularly in single-cell technology, which have fostered these advances and represent essential tools for future discoveries. In addition, we discuss clonal evolution within several contexts of particular relevance to contemporary clinical practice, including the settings of therapeutic resistance to CLL targeted therapy and immunotherapy, as well as Richter transformation of CLL to high-grade lymphoma.

Driving Out Chronic Lymphocytic Leukemia With CAR T Cells

Chronic lymphocytic leukemia (CLL) is the most prevalent leukemia in the Western hemisphere. The recent availability of novel targeted therapies, namely Bruton's tyrosine kinase, phosphoinositide-3 kinase, and BCL-2 inhibitors, have revolutionized the treatment algorithm for CLL but have not yet resulted in cure. Advances in the field of immuno-oncology and T cell engineering brought chimeric antigen receptor (CAR) T cell therapy from the laboratory to the clinic for treatment of B cell lymphoid malignancies and has improved the disease response and survival outcomes of various types of relapsed and/or refractory B cell lymphomas. While acknowledging that there are no approved CAR T cell therapies for CLL at this time, in this comprehensive review we explore novel targets for CAR T cell therapy in CLL and highlight the promising results of CAR T cell trials reported to date. Furthermore, we shed light on future areas of development, including multitarget CAR T cell products for this disease.

Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia

Chronic Lymphocytic Leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex-vivo drug response data from 217 Chronic Lymphocytic Leukemia (CLL) cases. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to the known biomarkers. We validated its presence and clinical relevance in four independent cohorts (n=547 patients). We find that this axis captures the proliferative drive (PD) of CLL cells, as it associates with lymphocyte doubling rate, global hypomethylation, accumulation of driver aberrations and response to pro-proliferative stimuli. CLL-PD was linked to the activation of mTOR-MYC-oxidative phosphorylation (OXPHOS) through transcriptomic, proteomic and single cell resolution analysis. CLL-PD is a key determinant of disease outcome in CLL. Our multi-table integration approach may be applicable to other tumors whose inter-individual differences are currently unexplained.

Identification of altered cell signaling pathways using proteomic profiling in stable and progressive chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is characterized by significant biologic and clinical heterogeneity. This study was designed to explore CLL B-cells' proteomic profile in order to identify biologic processes affected at an early stage and during disease evolution as stable or progressive. Purified B cells from 11 untreated CLL patients were tested at two time points by liquid chromatography-tandem mass spectrometry. Patients included in the study evolved to either progressive (n = 6) or stable disease (n = 5). First, at an early stage of the disease (Binet stage A), based on the relative abundance levels of 389 differentially expressed proteins (DEPs), samples were separated into stable and progressive clusters with the main differentiating factor being the RNA splicing pathway. Next, in order to test how the DEPs affect RNA splicing, a RNA-Seq study was conducted showing 4217 differentially spliced genes between the two clusters. Distinct longitudinal evolutions were observed with predominantly proteomic modifications in the stable CLL group and spliced genes in the progressive CLL group. Splicing events were shown to be six times more frequent in the progressive CLL group. The main aberrant biologic processes controlled by DEPs and spliced genes in the progressive group were cytoskeletal organization, Wnt/β-catenin signaling, and mitochondrial and inositol phosphate metabolism with a downstream impact on CLL B-cell survival and migration. This study suggests that proteomic profiles at the early stage of CLL can discriminate progressive from stable disease and that RNA splicing dysregulation underlies CLL evolution, which opens new perspectives in terms of biomarkers and therapy.

The Protein Landscape of Chronic Lymphocytic Leukemia (CLL)

Many functional consequences of mutations on tumor phenotypes in chronic lymphocytic leukemia (CLL) are unknown. This may be in part due to a scarcity of information on the proteome of CLL. We profiled the proteome of 117 CLL patient samples with data-independent acquisition mass spectrometry (DIA-MS) and integrated the results with genomic, transcriptomic, ex vivo drug response and clinical outcome data. We found trisomy 12, IGHV mutational status, mutated SF3B1, trisomy 19, del(17)(p13), del(11)(q22.3), mutated DDX3X, and MED12 to influence protein expression (FDR < 5%). Trisomy 12 and IGHV status were the major determinants of protein expression variation in CLL as shown by principal component analysis (1055 and 542 differentially expressed proteins, FDR=5%). Gene set enrichment analyses of CLL with trisomy 12 implicated BCR/PI3K/AKT signaling as a tumor driver. These findings were supported by analyses of protein abundance buffering and protein complex formation, which identified limited protein abundance buffering and an upregulated protein complex involved in BCR, AKT, MAPK and PI3K signaling in trisomy 12 CLL. A survey of proteins associated with trisomy 12/IGHV-independent drug response linked STAT2 protein expression with response to kinase inhibitors including BTK and MEK inhibitors. STAT2 was upregulated in U-CLL, trisomy 12 CLL and required for chemokine/cytokine signaling (interferon response). This study highlights the importance of protein abundance data as a non-redundant layer of information in tumor biology, and provides a protein expression reference map for CLL.

Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Background

Chronic lymphocytic leukemia (CLL) is an indolent heme malignancy characterized by the accumulation of CD5⁺ CD19⁺ B cells and episodes of relapse. The biological signaling that influence episodes of relapse in CLL are not fully described. Here, we identify gene networks associated with CLL relapse and survival risk.

Methods

Networks were investigated by using a novel weighted gene network co-expression analysis method and examining overrepresentation of upstream regulators and signaling pathways within co-expressed transcriptome modules across clinically annotated transcriptomes from CLL patients (N = 203). Gene Ontology analysis was used to identify biological functions overrepresented in each module. Differential Expression of modules and individual genes was assessed using an ANOVA (Binet Stage A and B relapsed patients) or T-test (SF3B1 mutations). The clinical relevance of biomarker candidates was evaluated using log-rank Kaplan Meier (survival and relapse interval) and ROC tests.

Results

Eight distinct modules (M2, M3, M4, M7, M9, M10, M11, M13) were significantly correlated with relapse and differentially expressed between relapsed and non-relapsed Binet Stage A CLL patients. The biological functions of modules positively correlated with relapse were carbohydrate and mRNA metabolism, whereas negatively correlated modules to relapse were protein translation associated. Additionally, M1, M3, M7, and M13 modules negatively correlated with overall survival. CLL biomarkers BTK, BCL2, and TP53 were co-expressed, while unmutated IGHV biomarker ZAP70 and cell survival-associated NOTCH1 were co-expressed in modules positively correlated with relapse and negatively correlated with survival days.

Conclusions

This study provides novel insights into CLL relapse biology and pathways associated with known and novel biomarkers for relapse and overall survival. The modules associated with relapse and overall survival represented both known and novel pathways associated with CLL pathogenesis and can be a resource for the CLL research community. The hub genes of these modules, e.g., ARHGAP27P2, C1S, CASC2, CLEC3B, CRY1, CXCR5, FUT5, MID1IP1, and URAHP, can be studied further as new therapeutic targets or clinical markers to predict CLL patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01012-y.

Absence of Non-Canonical, Inhibitory MYD88 Splice Variants in B Cell Lymphomas Correlates With Sustained NF-κB Signaling

Gain-of-function mutations of the TLR adaptor and oncoprotein MyD88 drive B cell lymphomagenesis via sustained NF-κB activation. In myeloid cells, both short and sustained TLR activation and NF-κB activation lead to the induction of inhibitory MYD88 splice variants that restrain prolonged NF-κB activation. We therefore sought to investigate whether such a negative feedback loop exists in B cells. Analyzing MYD88 splice variants in normal B cells and different primary B cell malignancies, we observed that MYD88 splice variants in transformed B cells are dominated by the canonical, strongly NF-κB-activating isoform of MYD88 and contain at least three novel, so far uncharacterized signaling-competent splice isoforms. Sustained TLR stimulation in B cells unexpectedly reinforces splicing of NF-κB-promoting, canonical isoforms rather than the 'MyD88s', a negative regulatory isoform reported to be typically induced by TLRs in myeloid cells. This suggests that an essential negative feedback loop restricting TLR signaling in myeloid cells at the level of alternative splicing, is missing in B cells when they undergo proliferation, rendering B cells vulnerable to sustained NF-κB activation and eventual lymphomagenesis. Our results uncover MYD88 alternative splicing as an unappreciated promoter of B cell lymphomagenesis and provide a rationale why oncogenic MYD88 mutations are exclusively found in B cells.

Long non-coding RNAs and their targets as potential biomarkers in breast cancer

Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease-specific biomarkers. Recently, long non-coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post-transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co-expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co-expressed lncRNAs and their cis- and trans-regulating mRNA targets which include RP11-108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.

CLL intraclonal fractions exhibit established and recently acquired patterns of DNA methylation

Intraclonal subpopulations of circulating chronic lymphocytic leukemia (CLL) cells with different proliferative histories and reciprocal surface expression of CXCR4 and CD5 have been observed in the peripheral blood of CLL patients and named proliferative (PF), intermediate (IF), and resting (RF) cellular fractions. Here, we found that these intraclonal circulating fractions share persistent DNA methylation signatures largely associated with the mutation status of the immunoglobulin heavy chain locus (IGHV) and their origins from distinct stages of differentiation of antigen-experienced B cells. Increased leukemic birth rate, however, showed a very limited impact on DNA methylation of circulating CLL fractions independent of IGHV mutation status. Additionally, DNA methylation heterogeneity increased as leukemic cells advanced from PF to RF in the peripheral blood. This frequently co-occurred with heterochromatin hypomethylation and hypermethylation of Polycomb-repressed regions in the PF, suggesting accumulation of longevity-associated epigenetic features in recently born cells. On the other hand, transcriptional differences between paired intraclonal fractions confirmed their proliferative experience and further supported a linear advancement from PF to RF in the peripheral blood. Several of these differentially expressed genes showed unique associations with clinical outcome not evident in the bulk clone, supporting the pathological and therapeutic relevance of studying intraclonal CLL fractions. We conclude that independent methylation and transcriptional landscapes reflect both preexisting cell-of-origin fingerprints and more recently acquired hallmarks associated with the life cycle of circulating CLL cells.

Regulation of RNA Splicing: Aberrant Splicing Regulation and Therapeutic Targets in Cancer

RNA splicing is a critical step in the maturation of precursor mRNA (pre-mRNA) by removing introns and exons. The combination of inclusion and exclusion of introns and exons in pre-mRNA can generate vast diversity in mature mRNA from a limited number of genes. Cancer cells acquire cancer-specific mechanisms through aberrant splicing regulation to acquire resistance to treatment and to promote malignancy. Splicing regulation involves many factors, such as proteins, non-coding RNAs, and DNA sequences at many steps. Thus, the dysregulation of splicing is caused by many factors, including mutations in RNA splicing factors, aberrant expression levels of RNA splicing factors, small nuclear ribonucleoproteins biogenesis, mutations in snRNA, or genomic sequences that are involved in the regulation of splicing, such as 5' and 3' splice sites, branch point site, splicing enhancer/silencer, and changes in the chromatin status that affect the splicing profile. This review focuses on the dysregulation of RNA splicing related to cancer and the associated therapeutic methods.

Endometrial Receptivity Analysis (ERA): data versus opinions

This article summarises and contextualises the accumulated basic and clinical data on the ERA test and addresses specific comments and opinions presented by the opponent as part of an invited debate. Progress in medicine depends on new technologies and concepts that translate to practice to solve long-standing problems. In a key example, combining RNA sequencing data (transcriptomics) with artificial intelligence (AI) led to a clinical revolution in personalising disease diagnosis and fostered the concept of precision medicine. The reproductive field is no exception. Translation of endometrial transcriptomics to the clinic yielded an objective definition of the limited time period during which the maternal endometrium is receptive to an embryo, known as the window of implantation (WOI). The WOI is induced by the presence of exogenous and/or endogenous progesterone (P) after proper oestradiol (E2) priming. The window lasts 30-36 hours and, depending on the patient, occurs between LH + 6 and LH + 9 in natural cycles or between P + 4 and P + 7 in hormonal replacement therapy (HRT) cycles. In approximately 30% of IVF cycles in which embryo transfer is performed blindly, the WOI is displaced and embryo-endometrial synchrony is not achieved. Extending this application of endometrial transcriptomics, the endometrial receptivity analysis (ERA) test couples next-generation sequencing (NGS) to a computational predictor to identify transcriptomic signatures for each endometrial stage: proliferative (PRO), pre-receptive (PRE), receptive (R) and post-receptive (POST). In this way, personalised embryo transfer (pET) may be possible by synchronising embryo transfer with each patient's WOI. Data are the only way to confront arguments sustained in opinions and/or misleading concepts; it is up to the reader to make their own conclusions regarding its clinical utility.

Non-coding RNAs (miRNAs and lncRNAs) and their roles in lymphogenesis in all types of lymphomas and lymphoid malignancies

Contemporary developments in molecular biology have been combined with discoveries on the analysis of the role of all non-coding RNAs (ncRNAs) in human diseases, particularly in cancer, by examining their roles in cells. Currently, included among these common types of cancer, are all the lymphomas and lymphoid malignancies, which represent a diverse group of neoplasms and malignant disorders. Initial data suggest that non-coding RNAs, particularly long ncRNAs (lncRNAs), play key roles in oncogenesis and that lncRNA-mediated biology is an important key pathway to cancer progression. Other non-coding RNAs, termed microRNAs (miRNAs or miRs), are very promising cancer molecular biomarkers. They can be detected in tissues, cell lines, biopsy material and all biological fluids, such as blood. With the number of well-characterized cancer-related lncRNAs and miRNAs increasing, the study of the roles of non-coding RNAs in cancer is bringing forth new hypotheses of the biology of cancerous cells. For the first time, to the best of our knowledge, the present review provides an up-to-date summary of the recent literature referring to all diagnosed ncRNAs that mediate the pathogenesis of all types of lymphomas and lymphoid malignancies.

A hotspot mutation in transcription factor IKZF3 drives B cell neoplasia via transcriptional dysregulation

Hotspot mutation of IKZF3 (IKZF3-L162R) has been identified as a putative driver of chronic lymphocytic leukemia (CLL), but its function remains unknown. Here, we demonstrate its driving role in CLL through a B cell-restricted conditional knockin mouse model. Mutant Ikzf3 alters DNA binding specificity and target selection, leading to hyperactivation of B cell receptor (BCR) signaling, overexpression of nuclear factor κB (NF-κB) target genes, and development of CLL-like disease in elderly mice with a penetrance of ~40%. Human CLL carrying either IKZF3 mutation or high IKZF3 expression was associated with overexpression of BCR/NF-κB pathway members and reduced sensitivity to BCR signaling inhibition by ibrutinib. Our results thus highlight IKZF3 oncogenic function in CLL via transcriptional dysregulation and demonstrate that this pro-survival function can be achieved by either somatic mutation or overexpression of this CLL driver. This emphasizes the need for combinatorial approaches to overcome IKZF3-mediated BCR inhibitor resistance.

The Effect of SF3B1 Mutation on the DNA Damage Response and Nonsense-Mediated mRNA Decay in Cancer

Recurrent mutations in splicing factor 3B subunit 1 (SF3B1) have been identified in several malignancies and are associated with an increased expression of 3' cryptic transcripts as a result of alternative branchpoint recognition. A large fraction of cryptic transcripts associated with SF3B1 mutations is expected to be sensitive for RNA degradation via nonsense-mediated mRNA decay (NMD). Several studies indicated alterations in various signaling pathways in SF3B1-mutated cells, including an impaired DNA damage response (DDR) in chronic lymphocytic leukemia (CLL). In this study, we investigated isogenic cell lines and treatment naïve primary CLL samples without any TP53 and/or ATM defect, and found no significant effects of SF3B1 mutations on the ATM/p53 response, phosphorylation of H2AX and sensitivity to fludarabine. Cryptic transcripts associated with SF3B1 mutation status were observed at relatively low levels compared to the canonical transcripts and were validated as target for mRNA degradation via NMD. Expression of cryptic transcripts increased after NMD inhibition. In conclusion, our results confirm involvement of NMD in the biological effects of SF3B1 mutations. Further studies may elucidate whether SF3B1-mutant patients could benefit from NMD modulatory agents.

Analysis of retrotransposon subfamily DNA methylation reveals novel early epigenetic changes in chronic lymphocytic leukemia

Retrotransposons such as LINE-1 and Alu comprise >25% of the human genome. While global hypomethylation of these elements has been widely reported in solid tumours, their epigenetic dysregulation is yet to be characterised in chronic lymphocytic leukemia (CLL), and there has been scant consideration of their evolutionary history that mediates sensitivity to hypomethylation. Here, we developed an approach for locus- and evolutionary subfamily-specific analysis of retrotransposons using the Illumina Infinium Human Methylation 450K microarray platform, which we applied to publicly-available datasets from CLL and other haematological malignancies. We identified 9,797 microarray probes mapping to 117 LINE-1 subfamilies and 13,130 mapping to 37 Alu subfamilies. Of these, 10,782 were differentially methylated (PFDR<0.05) in CLL patients (n=139) compared with healthy individuals (n=14), with enrichment at enhancers (P=0.002). Differential methylation was associated with evolutionary age of LINE-1 (r²=0.31, P=0.003) and Alu (r²=0.74, P=0.002) elements, with greater hypomethylation of older subfamilies (L1M, AluJ). Locus-specific hypomethylation was associated with differential expression of proximal genes, including DCLK2, HK1, ILRUN, TANK, TBCD, TNFRSF1B and TXNRD2, with higher expression of DCLK2 and TNFRSF1B associated with reduced patient survival. Hypomethylation at nine loci was highly frequent in CLL (>90% patients) but not observed in healthy individuals or other leukaemias, and was detectable in blood samples taken prior to CLL diagnosis in 9 of 82 individuals from the Melbourne Collaborative Cohort Study. Our results demonstrate differential methylation of retrotransposons in CLL by their evolutionary heritage that modulates expression of proximal genes.

The role of alternative splicing in cancer: From oncogenesis to drug resistance

Alternative splicing is a tightly regulated process whereby non-coding sequences of pre-mRNA are removed and protein-coding segments are assembled in diverse combinations, ultimately giving rise to proteins with distinct or even opposing functions. In the past decade, whole genome/transcriptome sequencing studies revealed the high complexity of splicing regulation, which occurs co-transcriptionally and is influenced by chromatin status and mRNA modifications. Consequently, splicing profiles of both healthy and malignant cells display high diversity and alternative splicing was shown to be widely deregulated in multiple cancer types. In particular, mutations in pre-mRNA regulatory sequences, splicing regulators and chromatin modifiers, as well as differential expression of splicing factors are important contributors to cancer pathogenesis. It has become clear that these aberrations contribute to many facets of cancer, including oncogenic transformation, cancer progression, response to anticancer drug treatment as well as resistance to therapy. In this respect, alternative splicing was shown to perturb the expression a broad spectrum of relevant genes involved in drug uptake/metabolism (i.e. SLC29A1, dCK, FPGS, and TP), activation of nuclear receptor pathways (i.e. GR, AR), regulation of apoptosis (i.e. MCL1, BCL-X, and FAS) and modulation of response to immunotherapy (CD19). Furthermore, aberrant splicing constitutes an important source of novel cancer biomarkers and the spliceosome machinery represents an attractive target for a novel and rapidly expanding class of therapeutic agents. Small molecule inhibitors targeting SF3B1 or splice factor kinases were highly cytotoxic against a wide range of cancer models, including drug-resistant cells. Importantly, these effects are enhanced in specific cancer subsets, such as splicing factor-mutated and c-MYC-driven tumors. Furthermore, pre-clinical studies report synergistic effects of spliceosome modulators in combination with conventional antitumor agents. These strategies based on the use of low dose splicing modulators could shift the therapeutic window towards decreased toxicity in healthy tissues. Here we provide an extensive overview of the latest findings in the field of regulation of splicing in cancer, including molecular mechanisms by which cancer cells harness alternative splicing to drive oncogenesis and evade anticancer drug treatment as well as splicing-based vulnerabilities that can provide novel treatment opportunities. Furthermore, we discuss current challenges arising from genome-wide detection and prediction methods of aberrant splicing, as well as unravelling functional relevance of the plethora of cancer-related splicing alterations.

Prognostic models for newly-diagnosed chronic lymphocytic leukaemia in adults: a systematic review and meta-analysis

BACKGROUND

Chronic lymphocytic leukaemia (CLL) is the most common cancer of the lymphatic system in Western countries. Several clinical and biological factors for CLL have been identified. However, it remains unclear which of the available prognostic models combining those factors can be used in clinical practice to predict long-term outcome in people newly-diagnosed with CLL.

OBJECTIVES

To identify, describe and appraise all prognostic models developed to predict overall survival (OS), progression-free survival (PFS) or treatment-free survival (TFS) in newly-diagnosed (previously untreated) adults with CLL, and meta-analyse their predictive performances.

SEARCH METHODS

We searched MEDLINE (from January 1950 to June 2019 via Ovid), Embase (from 1974 to June 2019) and registries of ongoing trials (to 5 March 2020) for development and validation studies of prognostic models for untreated adults with CLL. In addition, we screened the reference lists and citation indices of included studies.

SELECTION CRITERIA

We included all prognostic models developed for CLL which predict OS, PFS, or TFS, provided they combined prognostic factors known before treatment initiation, and any studies that tested the performance of these models in individuals other than the ones included in model development (i.e. 'external model validation studies'). We included studies of adults with confirmed B-cell CLL who had not received treatment prior to the start of the study. We did not restrict the search based on study design.

DATA COLLECTION AND ANALYSIS

We developed a data extraction form to collect information based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). Independent pairs of review authors screened references, extracted data and assessed risk of bias according to the Prediction model Risk Of Bias ASsessment Tool (PROBAST). For models that were externally validated at least three times, we aimed to perform a quantitative meta-analysis of their predictive performance, notably their calibration (proportion of people predicted to experience the outcome who do so) and discrimination (ability to differentiate between people with and without the event) using a random-effects model. When a model categorised individuals into risk categories, we pooled outcome frequencies per risk group (low, intermediate, high and very high). We did not apply GRADE as guidance is not yet available for reviews of prognostic models.

MAIN RESULTS

From 52 eligible studies, we identified 12 externally validated models: six were developed for OS, one for PFS and five for TFS. In general, reporting of the studies was poor, especially predictive performance measures for calibration and discrimination; but also basic information, such as eligibility criteria and the recruitment period of participants was often missing. We rated almost all studies at high or unclear risk of bias according to PROBAST. Overall, the applicability of the models and their validation studies was low or unclear; the most common reasons were inappropriate handling of missing data and serious reporting deficiencies concerning eligibility criteria, recruitment period, observation time and prediction performance measures. We report the results for three models predicting OS, which had available data from more than three external validation studies: CLL International Prognostic Index (CLL-IPI) This score includes five prognostic factors: age, clinical stage, IgHV mutational status, B2-microglobulin and TP53 status. Calibration: for the low-, intermediate- and high-risk groups, the pooled five-year survival per risk group from validation studies corresponded to the frequencies observed in the model development study. In the very high-risk group, predicted survival from CLL-IPI was lower than observed from external validation studies. Discrimination: the pooled c-statistic of seven external validation studies (3307 participants, 917 events) was 0.72 (95% confidence interval (CI) 0.67 to 0.77). The 95% prediction interval (PI) of this model for the c-statistic, which describes the expected interval for the model's discriminative ability in a new external validation study, ranged from 0.59 to 0.83. Barcelona-Brno score Aimed at simplifying the CLL-IPI, this score includes three prognostic factors: IgHV mutational status, del(17p) and del(11q). Calibration: for the low- and intermediate-risk group, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of four external validation studies (1755 participants, 416 events) was 0.64 (95% CI 0.60 to 0.67); 95% PI 0.59 to 0.68. MDACC 2007 index score The authors presented two versions of this model including six prognostic factors to predict OS: age, B2-microglobulin, absolute lymphocyte count, gender, clinical stage and number of nodal groups. Only one validation study was available for the more comprehensive version of the model, a formula with a nomogram, while seven studies (5127 participants, 994 events) validated the simplified version of the model, the index score. Calibration: for the low- and intermediate-risk groups, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of the seven external validation studies for the index score was 0.65 (95% CI 0.60 to 0.70); 95% PI 0.51 to 0.77.

AUTHORS' CONCLUSIONS

Despite the large number of published studies of prognostic models for OS, PFS or TFS for newly-diagnosed, untreated adults with CLL, only a minority of these (N = 12) have been externally validated for their respective primary outcome. Three models have undergone sufficient external validation to enable meta-analysis of the model's ability to predict survival outcomes. Lack of reporting prevented us from summarising calibration as recommended. Of the three models, the CLL-IPI shows the best discrimination, despite overestimation. However, performance of the models may change for individuals with CLL who receive improved treatment options, as the models included in this review were tested mostly on retrospective cohorts receiving a traditional treatment regimen. In conclusion, this review shows a clear need to improve the conducting and reporting of both prognostic model development and external validation studies. For prognostic models to be used as tools in clinical practice, the development of the models (and their subsequent validation studies) should adapt to include the latest therapy options to accurately predict performance. Adaptations should be timely.

RNA editing contributes to epitranscriptome diversity in chronic lymphocytic leukemia

RNA editing-primarily conversion of adenosine to inosine (A > I)-is a widespread posttranscriptional mechanism, mediated by Adenosine Deaminases acting on RNA (ADAR) enzymes to alter the RNA sequence of primary transcripts. Hence, in addition to somatic mutations and alternative RNA splicing, RNA editing can be a further source for recoding events. Although RNA editing has been detected in many solid cancers and normal tissue, RNA editing in chronic lymphocytic leukemia (CLL) has not been addressed so far. We determined global RNA editing and recurrent, recoding RNA editing events from matched RNA-sequencing and whole exome sequencing data in CLL samples from 45 untreated patients. RNA editing was verified in a validation cohort of 98 CLL patients and revealed substantially altered RNA editing profiles in CLL compared with normal B cells. We further found that RNA editing patterns were prognostically relevant. Finally, we showed that ADAR knockout decreased steady state viability of MEC1 cells and made them more susceptible to treatment with fludarabine and ibrutinib in vitro. We propose that RNA editing contributes to the pathophysiology of CLL and targeting the RNA editing machinery could be a future strategy to maximize treatment efficacy.

The role of long non-coding RNAs and downstream signaling pathways in leukemia progression

The study of long non-coding RNAs (lncRNA) is a newly established field and our knowledge about them is rapidly growing. These kinds of RNAs are unchanged parts of the genome throughout evolution, that modulate cell growth, differentiation, and apoptosis during diverse physiological and pathological processes including leukemia development. They have the capability to be useful biomarkers for the diagnosis, clinical typing, prognosis, as well as potential therapeutic targets. In this study, we summarized the role of lncRNAs in the expression and function of white blood cells and oncogenic transformation into four main types of leukemia.

Chromatin network markers of leukemia

MOTIVATION

The structure of chromatin impacts gene expression. Its alteration has been shown to coincide with the occurrence of cancer. A key challenge is in understanding the role of chromatin structure (CS) in cellular processes and its implications in diseases.

RESULTS

We propose a comparative pipeline to analyze CSs and apply it to study chronic lymphocytic leukemia (CLL). We model the chromatin of the affected and control cells as networks and analyze the network topology by state-of-the-art methods. Our results show that CSs are a rich source of new biological and functional information about DNA elements and cells that can complement protein-protein and co-expression data. Importantly, we show the existence of structural markers of cancer-related DNA elements in the chromatin. Surprisingly, CLL driver genes are characterized by specific local wiring patterns not only in the CS network of CLL cells, but also of healthy cells. This allows us to successfully predict new CLL-related DNA elements. Importantly, this shows that we can identify cancer-related DNA elements in other cancer types by investigating the CS network of the healthy cell of origin, a key new insight paving the road to new therapeutic strategies. This gives us an opportunity to exploit chromosome conformation data in healthy cells to predict new drivers.

AVAILABILITY AND IMPLEMENTATION

Our predicted CLL genes and RNAs are provided as a free resource to the community at https://life.bsc.es/iconbi/chromatin/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic and Epigenomic Alterations in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia is a common disease in Western countries and has heterogeneous clinical behavior. The relevance of the genetic basis of the disease has come to the forefront recently, with genome-wide studies that have provided a comprehensive view of structural variants, somatic mutations, and different layers of epigenetic changes. The mutational landscape is characterized by relatively common copy number alterations, a few mutated genes occurring in 10-15% of cases, and a large number of genes mutated in a small number of cases. The epigenomic profile has revealed a marked reprogramming of regulatory regions in tumor cells compared with normal B cells. All of these alterations are differentially distributed in clinical and biological subsets of the disease, indicating that they may underlie the heterogeneous evolution of the disease. These global studies are revealing the molecular complexity of chronic lymphocytic leukemia and provide new perspectives that have helped to understand its pathogenic mechanisms and improve the clinical management of patients.

RNA Editing Alters miRNA Function in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a high incidence B cell leukemia with a highly variable clinical course, leading to survival times ranging from months to several decades. MicroRNAs (miRNAs) are small non-coding RNAs that regulate the expression levels of genes by binding to the untranslated regions of transcripts. Although miRNAs have been previously shown to play a crucial role in CLL development, progression and treatment resistance, their further processing and diversification by RNA editing (specifically adenosine to inosine or cytosine to uracil deamination) has not been addressed so far. In this study, we analyzed next generation sequencing data to provide a detailed map of adenosine to inosine and cytosine to uracil changes in miRNAs from CLL and normal B cells. Our results reveal that in addition to a CLL-specific expression pattern, there is also specific RNA editing of many miRNAs, particularly miR-3157 and miR-6503, in CLL. Our data draw further light on how miRNAs and miRNA editing might be implicated in the pathogenesis of the disease.

Profiling and bioinformatics analyses reveal chronic lymphocytic leukemia cells share a unique circular RNA expression pattern

Approximately 10% of the human transcriptome is composed of circular RNAs (circRNAs). These are non-coding RNA molecules in which a covalent bond between the 3' and 5' forms a stable circular loop. Herein, we profiled the expression of 13,368 cricRNAS in 21 patients with chronic lymphocytic leukemia (CLL). Regardless of clinical, genetic, or prognostic characteristics, CLL cells share a unique expression profile distinguishable from that of normal B cells. Specifically, 859 circRNAs from 592 genes were differentially expressed (fold change ≥2 and false discovery rate ≤0.05). Whether dysregulation of circRNAs contributes to the pathogenesis of CLL remains to be determined.