Multi-platform profiling characterizes molecular subgroups and resistance networks in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) screening and abnormality detection based on multi-layer fluorescence imaging signal enhancement and compensation

PURPOSE

Fluorescence in situ hybridization (FISH) plays a critical role in cancer screening but faces challenges in signal clarity and manual intervention. This study aims to enhance FISH signal clarity, improve screening efficiency, and reduce false negatives through an automated image acquisition and signal enhancement framework.

METHODS

An automated workflow was developed, integrating a dynamic signal enhancement method that optimizes global and local features. An improved Cycle-GAN network was introduced, incorporating residual connections and layer-wise supervision to accurately model and compensate for complex signal characteristics. Key metrics such as signal brightness, edge gradients, contrast improvement index (CII), and structural similarity index (SSIM) were used to evaluate performance.

RESULTS

The proposed method increased weak signal brightness by 49.02%, edge gradients by 48.61%, and CII by 32.52%. The SSIM reached 0.996, indicating high fidelity to original signals.

CONCLUSION

Visual analysis demonstrated clearer, more continuous, and uniform fluorescence signals, effectively mitigating fragmentation and uneven distribution. These improvements reduced false negatives and enhanced genomic abnormality detection accuracy. The proposed method significantly improves FISH signal clarity and stability, providing reliable support for cancer screening, genomic abnormality detection, molecular typing, prognosis evaluation, and targeted treatment planning.

Genomic characterization of chronic lymphocytic leukemia in patients of African ancestry

Despite the considerable effort to characterize the genomic landscape of chronic lymphocytic leukemia (CLL), published data have been almost exclusively derived from patients of European Ancestry (EA), with significant underrepresentation of minorities, including patients of African Ancestry (AA). To begin to address this gap, we evaluated whether differences exist in the genetic and transcriptomic features of 157 AA and 440 EA individuals diagnosed with CLL. We sequenced 59 putative driver genes and found an increased frequency of high-impact mutations in AA CLL, including genes of the DNA damage repair (DDR) pathway. Telomere erosion was also increased in AA CLL, amplifying the notion of increased genomic instability in AA CLL. Furthermore, we found transcription enrichment of the Tumor Necrosis Factor-alpha (TNFα) Signaling via NF-κB pathway in AA CLL compared to EA CLL, suggesting that tumor promoting inflammation plays an important role in AA CLL. In summary, these results suggest that genomic instability and NF-kB activation is more prevalent in AA CLL than EA CLL.

Mesenchymal stem/stromal cells: dedicator to maintain tumor homeostasis

Mesenchymal stem/stromal cells （MSCs） act as a factor in tumor recurrence after drug treatment with their involvement observed in various cancer types. As a constituent of the tumor microenvironment (TME), MSCs not only provide support to tumor growth but also establish connections with diverse cell populations within the TME, serving as mediators linking different tumor-associated components. MSCs play an important role in maintaining tumor progression due to their stem cell properties and remarkable differentiation capacity. Given the intensification of tumor research and the encouraging results achieved in recent years，the aim of this article is to investigate the supportive role of MSCs in tumor cells as well as in various cellular and non-cellular components of the tumor microenvironment. Furthermore, the article shows that MSCs do not have a specific anatomical ecological niche and describes the contribution of MSCs to the maintenance of tumor homeostasis on the basis of homing, plasticity and tumor-forming properties. By elucidating the critical roles of different components of TME, this study provides a comprehensive understanding of tumor therapy and may offer new insights into defeating cancer.

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.

Subtype-WGME enables whole-genome-wide multi-omics cancer subtyping

We present an innovative strategy for integrating whole-genome-wide multi-omics data, which facilitates adaptive amalgamation by leveraging hidden layer features derived from high-dimensional omics data through a multi-task encoder. Empirical evaluations on eight benchmark cancer datasets substantiated that our proposed framework outstripped the comparative algorithms in cancer subtyping, delivering superior subtyping outcomes. Building upon these subtyping results, we establish a robust pipeline for identifying whole-genome-wide biomarkers, unearthing 195 significant biomarkers. Furthermore, we conduct an exhaustive analysis to assess the importance of each omic and non-coding region features at the whole-genome-wide level during cancer subtyping. Our investigation shows that both omics and non-coding region features substantially impact cancer development and survival prognosis. This study emphasizes the potential and practical implications of integrating genome-wide data in cancer research, demonstrating the potency of comprehensive genomic characterization. Additionally, our findings offer insightful perspectives for multi-omics analysis employing deep learning methodologies.

Metabolic and toxicological considerations of Bruton's tyrosine kinase inhibitors for the treatment of chronic lymphocytic leukemia/small lymphocytic lymphoma

INTRODUCTION

Bruton tyrosine kinase inhibitors (BTKi) have been used for the management of human diseases since the approval of the first-in class agent, ibrutinib, by the Food and Drug Administration in 2013 for the treatment of patients with mantle cell lymphoma (MCL). Ibrutinib is a covalent inhibitor along with second-class BTKis: acalabrutinib and zanubrutinib. These well-tolerated agents have transformed the treatment landscape of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). A new class of these inhibitors, non-covalent, might become an answer to the emerging resistance by avoiding the sustained contact with the kinase binding domain.

AREAS COVERED

This article examines the chemical composition, mechanism of action, metabolic characteristics, and potential toxicity of inhibitors targeting Bruton tyrosine kinase. A comprehensive search was conducted across English-language articles in PubMed, Web of Science, and Google Scholar.

EXPERT OPINION

Bruton tyrosine kinase inhibitors have greatly enhanced the armamentarium against lymphoid malignancies including CLL/SLL. Their future lies in the choice of appropriate patients who will benefit from the treatment without significant adverse reaction. Combination chemotherapy-free fixed-duration regimens with targeted molecules will allow for MRD-driven approach in patients with CLL/SLL in the near future.

Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

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.

Transcriptomic profiles and 5-year results from the randomized CLL14 study of venetoclax plus obinutuzumab versus chlorambucil plus obinutuzumab in chronic lymphocytic leukemia

Data on long-term outcomes and biological drivers associated with depth of remission after BCL2 inhibition by venetoclax in the treatment of chronic lymphocytic leukemia (CLL) are limited. In this open-label parallel-group phase-3 study, 432 patients with previously untreated CLL were randomized (1:1) to receive either 1-year venetoclax-obinutuzumab (Ven-Obi, 216 patients) or chlorambucil-Obi (Clb-Obi, 216 patients) therapy (NCT02242942). The primary endpoint was investigator-assessed progression-free survival (PFS); secondary endpoints included minimal residual disease (MRD) and overall survival. RNA sequencing of CD19-enriched blood was conducted for exploratory post-hoc analyses. After a median follow-up of 65.4 months, PFS is significantly superior for Ven-Obi compared to Clb-Obi (Hazard ratio [HR] 0.35 [95% CI 0.26-0.46], p < 0.0001). At 5 years after randomization, the estimated PFS rate is 62.6% after Ven-Obi and 27.0% after Clb-Obi. In both arms, MRD status at the end of therapy is associated with longer PFS. MRD + ( ≥ 10-4) status is associated with increased expression of multi-drug resistance gene ABCB1 (MDR1), whereas MRD6 (< 10-6) is associated with BCL2L11 (BIM) expression. Inflammatory response pathways are enriched in MRD+ patient solely in the Ven-Obi arm. These data indicate sustained long-term efficacy of fixed-duration Ven-Obi in patients with previously untreated CLL. The distinct transcriptomic profile of MRD+ status suggests possible biological vulnerabilities.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

Glyoxalase 1 inhibitor BBGC suppresses the progression of chronic lymphocytic leukemia and promotes the efficacy of Palbociclib

Chronic lymphocytic leukemia (CLL) is a highly heterogeneous disease. Despite recent tremen-dous progress in managing CLL, the disease remains incurable with clinical therapies, and relapse is inevitable. To overcome this, new diagnostic and prognostic markers need to be investigated. We thus screened through the public database for genes with diagnostic, prognostic, and therapeutic implications in CLL. We further performed RT-qPCR and Western blot analysis to measure the candidate gene and protein expression levels, respectively, in peripheral blood mononuclear cells. Our results indicated that Glyoxalase 1 (GLO1) expression was significantly higher in patients with CLL than in healthy controls. Furthermore, cell proliferation, apoptosis, and cell cycle assay results together indicated that S-p-bromobenzylglutathione cyclopentyl diester (BBGC), an effective inhibitor of GLO1, suppresses the progression of CLL. Bioinformatics analysis revealed that GLO1 expression is closely associated with CDK4 expression in a wide variety of cancer types, and inhibition of CDK4 through silencing of genes or inhibitors can downregulate GLO1 expression. Subsequent validation experiments demonstrated that GLO1 protein levels were downregulated in MEC-1 and Jurkat cell lines after palbociclib exposure, and combination treatment of palbociclib with GLO1 inhibitor BBGC effectively delayed the growth of tumor cell lines.

Prognostication of DNA Damage Response Protein Expression Patterns in Chronic Lymphocytic Leukemia

Proteomic DNA Damage Repair (DDR) expression patterns in Chronic Lymphocytic Leukemia were characterized by quantifying and clustering 24 total and phosphorylated DDR proteins. Overall, three protein expression patterns (C1-C3) were identified and were associated as an independent predictor of distinct patient overall survival outcomes. Patients within clusters C1 and C2 had poorer survival outcomes and responses to fludarabine, cyclophosphamide, and rituxan chemotherapy compared to patients within cluster C3. However, DDR protein expression patterns were not prognostic in more modern therapies with BCL2 inhibitors or a BTK/PI3K inhibitor. Individually, nine of the DDR proteins were prognostic for predicting overall survival and/or time to first treatment. When looking for other proteins that may be associated with or influenced by DDR expression patterns, our differential expression analysis found that cell cycle and adhesion proteins were lower in clusters compared to normal CD19 controls. In addition, cluster C3 had a lower expression of MAPK proteins compared to the poor prognostic patient clusters thus implying a potential regulatory connection between adhesion, cell cycle, MAPK, and DDR signaling in CLL. Thus, assessing the proteomic expression of DNA damage proteins in CLL provided novel insights for deciphering influences on patient outcomes and expanded our understanding of the potential complexities and effects of DDR cell signaling.

Harnessing epithelial-mesenchymal plasticity to boost cancer immunotherapy

Immune checkpoint blockade (ICB) therapy is a powerful option for cancer treatment. Despite demonstrable progress, most patients fail to respond or achieve durable responses due to primary or acquired ICB resistance. Recently, tumor epithelial-to-mesenchymal plasticity (EMP) was identified as a critical determinant in regulating immune escape and immunotherapy resistance in cancer. In this review, we summarize the emerging role of tumor EMP in ICB resistance and the tumor-intrinsic or extrinsic mechanisms by which tumors exploit EMP to achieve immunosuppression and immune escape. We discuss strategies to modulate tumor EMP to alleviate immune resistance and to enhance the efficiency of ICB therapy. Our discussion provides new prospects to enhance the ICB response for therapeutic gain in cancer patients.

Integrative epigenomics in chronic lymphocytic leukaemia: Biological insights and clinical applications

Chronic lymphocytic leukaemia (CLL) is not only characterised by driver genetic alterations but by extensive epigenetic changes. Over the last decade, epigenomic studies have described the DNA methylome, chromatin accessibility, histone modifications and the three-dimensional (3D) genome architecture of CLL. Beyond its regulatory role, the DNA methylome contains imprints of the cellular origin and proliferative history of CLL cells. These two aspects are strong independent prognostic factors. Integrative analyses of chromatin marks have uncovered novel regulatory elements and altered transcription factor networks as non-genetic means mediating gene deregulation in CLL. Additionally, CLL cells display a disease-specific pattern of 3D genome interactions. From the technological perspective, we are currently witnessing a transition from bulk omics to single-cell analyses. This review aims at summarising the major findings from the epigenomics field as well as providing a prospect of the present and future of single-cell analyses in CLL.

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.

Precision diagnostics in lymphomas - Recent developments and future directions

Genetics is an integral part of the clinical diagnostics of lymphomas that improves disease subclassification and patient risk-stratification. With the introduction of high-throughput sequencing technologies, a rapid, in-depth portrayal of the genomic landscape in major lymphoma entities was achieved. Whilst a few lymphoma entities were characterized by a predominant gene mutation (e.g. Waldenström's macroglobulinemia and hairy cell leukemia), the vast majority demonstrated a very diverse genetic landscape with a high number of recurrent gene mutations (e.g. chronic lymphocytic leukemia and diffuse large B cell lymphoma), indeed reflecting the great clinical heterogeneity among lymphomas. These studies have allowed better understanding of the ontogeny and evolution of different lymphomas, while also identifying new genetic markers that can complement lymphoma diagnostics and improve prognostication. However, despite these efforts, there is still a limited number of gene mutations with predictive impact that can guide treatment selection. In this review, we will highlight clinically relevant diagnostic, prognostic and predictive markers in lymphomas that are used today in routine diagnostics. We will also discuss how comprehensive genomic characterization using broad sequencing panels, allowing for the simultaneous detection of different types of genetic aberrations, may aid future development of precision diagnostics in lymphomas. This may in turn pave the way for the implementation of tailored precision therapy strategies at the individual patient level.