Whole-genome sequencing reveals activation-induced cytidine deaminase signatures during indolent chronic lymphocytic leukaemia evolution

A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing

The B-cell acute lymphoblastic leukemia (ALL) cell line REH, with the t(12;21) ETV6::RUNX1 translocation, is known to have a complex karyotype defined by a series of large-scale chromosomal rearrangements. Taken from a 15-yr-old at relapse, the cell line offers a practical model for the study of pediatric B-ALL. In recent years, short- and long-read DNA and RNA sequencing have emerged as a complement to karyotyping techniques in the resolution of structural variants in an oncological context. Here, we explore the integration of long-read PacBio and Oxford Nanopore whole-genome sequencing, IsoSeq RNA sequencing, and short-read Illumina sequencing to create a detailed genomic and transcriptomic characterization of the REH cell line. Whole-genome sequencing clarified the molecular traits of disrupted ALL-associated genes including CDKN2A, PAX5, BTG1, VPREB1, and TBL1XR1, as well as the glucocorticoid receptor NR3C1 Meanwhile, transcriptome sequencing identified seven fusion genes within the genomic breakpoints. Together, our extensive whole-genome investigation makes high-quality open-source data available to the leukemia genomics community.

Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis

Human aging is marked by the emergence of a tapestry of clonal expansions in dividing tissues, particularly evident in blood as clonal hematopoiesis (CH). CH, linked to cancer risk and aging-related phenotypes, often stems from somatic mutations in a set of established genes. However, the majority of clones lack known drivers. Here we infer gene-level positive selection in whole blood exomes from 200,618 individuals in UK Biobank. We identify 17 additional genes, ZBTB33, ZNF318, ZNF234, SPRED2, SH2B3, SRCAP, SIK3, SRSF1, CHEK2, CCDC115, CCL22, BAX, YLPM1, MYD88, MTA2, MAGEC3 and IGLL5, under positive selection at a population level, and validate this selection pattern in 10,837 whole genomes from single-cell-derived hematopoietic colonies. Clones with mutations in these genes grow in frequency and size with age, comparable to classical CH drivers. They correlate with heightened risk of infection, death and hematological malignancy, highlighting the significance of these additional genes in the aging process.

Taming AID mutator activity in somatic hypermutation

Activation-induced cytidine deaminase (AID) initiates somatic hypermutation (SHM) by introducing base substitutions into antibody genes, a process enabling antibody affinity maturation in immune response. How a mutator is tamed to precisely and safely generate programmed DNA lesions in a physiological process remains unsettled, as its dysregulation drives lymphomagenesis. Recent research has revealed several hidden features of AID-initiated mutagenesis: preferential activity on flexible DNA substrates, restrained activity within chromatin loop domains, unique DNA repair factors to differentially decode AID-caused lesions, and diverse consequences of aberrant deamination. Here, we depict the multifaceted regulation of AID activity with a focus on emerging concepts/factors and discuss their implications for the design of base editors (BEs) that install somatic mutations to correct deleterious genomic variants.

AID in non-Hodgkin B-cell lymphomas: The consequences of on- and off-target activity

Activation induced cytidine deaminase (AID) is a key element of the adaptive immune system, required for immunoglobulin isotype switching and affinity maturation of B-cells as they undergo the germinal center (GC) reaction in peripheral lymphoid tissue. The inherent DNA damaging activity of this enzyme can also have off-target effects in B-cells, producing lymphomagenic chromosomal translocations that are characteristic features of various classes of non-Hodgkin B-cell lymphoma (B-NHL), and generating oncogenic mutations, so-called aberrant somatic hypermutation (aSHM). Additionally, AID has been found to affect gene expression through demethylation as well as altered interactions between gene regulatory elements. These changes have been most thoroughly studied in B-NHL arising from GC B-cells. Here, we describe the most common classes of GC-derived B-NHL and explore the consequences of on- and off-target AID activity in B and plasma cell neoplasms. The relationships between AID expression, including effects of infection and other exposures/agents, mutagenic activity and lymphoma biology are also discussed.

Follicular lymphoma B cells exhibit heterogeneous transcriptional states with associated somatic alterations and tumor microenvironments

Follicular lymphoma (FL) is an indolent non-Hodgkin lymphoma of germinal center origin, which presents with significant biologic and clinical heterogeneity. Using RNA-seq on B cells sorted from 87 FL biopsies, combined with machine-learning approaches, we identify 3 transcriptional states that divide the biological ontology of FL B cells into inflamed, proliferative, and chromatin-modifying states, with relationship to prior GC B cell phenotypes. When integrated with whole-exome sequencing and immune profiling, we find that each state was associated with a combination of mutations in chromatin modifiers, copy-number alterations to TNFAIP3, and T follicular helper cells (Tfh) cell interactions, or primarily by a microenvironment rich in activated T cells. Altogether, these data define FL B cell transcriptional states across a large cohort of patients, contribute to our understanding of FL heterogeneity at the tumor cell level, and provide a foundation for guiding therapeutic intervention.

5-Chloro-2'-deoxycytidine Induces a Distinctive High-Resolution Mutational Spectrum of Transition Mutations In Vivo

The biomarker 5-chlorocytosine (5ClC) appears in the DNA of inflamed tissues. Replication of a site-specific 5ClC in a viral DNA genome results in C → T mutations, which is consistent with 5ClC acting as a thymine mimic in vivo. Direct damage of nucleic acids by immune-cell-derived hypochlorous acid is one mechanism by which 5ClC could appear in the genome. A second, nonmutually exclusive mechanism involves damage of cytosine nucleosides or nucleotides in the DNA precursor pool, with subsequent utilization of the 5ClC deoxynucleotide triphosphate as a precursor for DNA synthesis. The present work characterized the mutagenic properties of 5ClC in the nucleotide pool by exposing cells to the nucleoside 5-chloro-2'-deoxycytidine (5CldC). In both Escherichia coli and mouse embryonic fibroblasts (MEFs), 5CldC in the growth media was potently mutagenic, indicating that 5CldC enters cells and likely is erroneously incorporated into the genome from the nucleotide pool. High-resolution sequencing of DNA from MEFs derived from the gptΔ C57BL/6J mouse allowed qualitative and quantitative characterization of 5CldC-induced mutations; CG → TA transitions in 5'-GC(Y)-3' contexts (Y = a pyrimidine) were dominant, while TA → CG transitions appeared at a much lower frequency. The high-resolution mutational spectrum of 5CldC revealed a notable similarity to the Catalogue of Somatic Mutations in Cancer mutational signatures SBS84 and SBS42, which appear in human lymphoid tumors and in occupationally induced cholangiocarcinomas, respectively. SBS84 is associated with the expression of activation-induced cytidine deaminase (AID), a cytosine deaminase associated with inflammation, as well as immunoglobulin gene diversification during antibody maturation. The similarity between the spectra of AID activation and 5CldC could be coincidental; however, the administration of 5CldC did induce some AID expression in MEFs, which have no inherent expression of its gene. In summary, this work shows that 5CldC induces a distinct pattern of mutations in cells. Moreover, that pattern resembles human mutational signatures induced by inflammatory processes, such as those triggered in certain malignancies.

Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotype and phenotype in chronic lymphocytic leukemia

Bruton's tyrosine kinase (BTK) inhibitors are effective for the treatment of chronic lymphocytic leukemia (CLL) due to BTK's role in B cell survival and proliferation. Treatment resistance is most commonly caused by the emergence of the hallmark BTKC481S mutation that inhibits drug binding. In this study, we aimed to investigate whether the presence of additional CLL driver mutations in cancer subclones harboring a BTKC481S mutation accelerates subclone expansion. In addition, we sought to determine whether BTK-mutated subclones exhibit distinct transcriptomic behavior when compared to other cancer subclones. To achieve these goals, we employ our recently published method (Qiao et al. 2024) that combines bulk DNA sequencing and single-cell RNA sequencing (scRNA-seq) data to genotype individual cells for the presence or absence of subclone-defining mutations. While the most common approach for scRNA-seq includes short-read sequencing, transcript coverage is limited due to the vast majority of the reads being concentrated at the priming end of the transcript. Here, we utilized MAS-seq, a long-read scRNAseq technology, to substantially increase transcript coverage across the entire length of the transcripts and expand the set of informative mutations to link cells to cancer subclones in six CLL patients who acquired BTKC481S mutations during BTK inhibitor treatment. We found that BTK-mutated subclones often acquire additional mutations in CLL driver genes, leading to faster subclone proliferation. When examining subclone-specific gene expression, we found that in one patient, BTK-mutated subclones are transcriptionally distinct from the rest of the malignant B cell population with an overexpression of CLL-relevant genes.

Accurate and sensitive mutational signature analysis with MuSiCal

Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous 'flat' signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

IGLL5 controlled by super-enhancer affects cell survival and MYC expression in mature B-cell lymphoma

IGLL5 is shown to be located near super-enhancer (SE) in B-cell tumors, and this gene is frequently mutated and a target of translocation in B-cell tumors. These results suggest roles of the IGLL5 in tumorigenesis; however, its functional properties have been unclear. We found that two mature B-cell lymphoma cell lines expressed IGLL5 mRNA with Cλ1 segment. JQ1 treatment resulted in down-expression of IGLL5, indicating that IGLL5 is controlled by SE. IGLL5 knockdown induced cell death with down-expression of MYC. Our results suggested that IGLL5 might have a role in survival of mature B-cell tumors and involvement in MYC expression. (100 words).

The molecular map of CLL and Richter's syndrome

Clonal expansion of B-cells, from the early stages of monoclonal B-cell lymphocytosis through to chronic lymphocytic leukemia (CLL), and then in some cases to Richter's syndrome (RS) provides a comprehensive model of cancer evolution, notable for the marked morphological transformation and distinct clinical phenotypes. High-throughput sequencing of large cohorts of patients and single-cell studies have generated a molecular map of CLL and more recently, of RS, yielding fundamental insights into these diseases and of clonal evolution. A selection of CLL driver genes have been functionally interrogated to yield novel insights into the biology of CLL. Such findings have the potential to impact patient care through risk stratification, treatment selection and drug discovery. However, this molecular map remains incomplete, with extant questions concerning the origin of the B-cell clone, the role of the TME, inter- and intra-compartmental heterogeneity and of therapeutic resistance mechanisms. Through the application of multi-modal single-cell technologies across tissues, disease states and clinical contexts, these questions can now be addressed with the answers holding great promise of generating translatable knowledge to improve patient care.

APOBEC Mutagenesis in Cancer Development and Susceptibility

APOBEC cytosine deaminases are prominent mutators in cancer, mediating mutations in over 50% of cancers. APOBEC mutagenesis has been linked to tumor heterogeneity, persistent cell evolution, and therapy responses. While emerging evidence supports the impact of APOBEC mutagenesis on cancer progression, the understanding of its contribution to cancer susceptibility and malignant transformation is limited. We examine the existing evidence for the role of APOBEC mutagenesis in carcinogenesis on the basis of the reported associations between germline polymorphisms in genes encoding APOBEC enzymes and cancer risk, insights into APOBEC activities from sequencing efforts of both malignant and non-malignant human tissues, and in vivo studies. We discuss key knowledge gaps and highlight possible ways to gain a deeper understanding of the contribution of APOBEC mutagenesis to cancer development.

Machine learning and multi-omics data in chronic lymphocytic leukemia: the future of precision medicine?

Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of high-throughput multi-omics technologies has significantly influenced chronic lymphocytic leukemia research and paved the way for precision medicine approaches. In this review, we explore the role of machine learning in the analysis of multi-omics data in this hematological malignancy. We discuss recent literature on different machine learning models applied to single omic studies in chronic lymphocytic leukemia, with a special focus on the potential contributions to precision medicine. Finally, we highlight the recently published machine learning applications in multi-omics data in this area of research as well as their potential and limitations.

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Transcriptomic analysis of mRNAs in human whole blood identified age-specific changes in healthy individuals

Older age is one of the most important shared risk factors for multiple chronic diseases, increasing the medical burden to contemporary societies. Current research focuses on identifying aging biomarkers to predict aging trajectories and developing interventions aimed at preventing and delaying the progression of multimorbidity with aging. Here, a transcriptomic changes analysis of whole blood genes with age was conducted. The age-related whole blood gene-expression profiling datasets were downloaded from the Gene Expression Omnibus (GEO) database. We screened the differentially expressed genes (DEGs) between healthy young and old individuals and performed functional enrichment analysis. Cytoscape with Cytohubba and MCODE was used to perform an interaction network of DEGs and identify hub genes. In addition, ROC curves and correlation analysis were used to evaluate the accuracy of hub genes. In total, we identified 29 DEGs between young and old samples that were enriched mainly in immunoglobulin binding and complex, humoral immune response, and immune response-activating signaling pathways. In combination with the PPI network and topological analysis, 4 hub genes (IGLL5, Jchain, POU2AF1, and Bach2) were identified. Pearson analysis showed that the expression changes of these hub genes were highly correlated with age. Among them, 3 hub genes (IGLL5, POU2AF1, and Bach2) were identified with good accuracy (AUC score > 0.7), indicating that these genes were the best indicators of age. Together, our results provided potential biomarkers IGLL5, POU2AF1, and Bach2 to identify individuals at high early risk of age-related disease to be targeted for early interventions and contribute to understanding the molecular mechanisms in the progression of aging.

Meiotic DNA breaks drive multifaceted mutagenesis in the human germ line

Meiotic recombination commences with hundreds of programmed DNA breaks; however, the degree to which they are accurately repaired remains poorly understood. We report that meiotic break repair is eightfold more mutagenic for single-base substitutions than was previously understood, leading to de novo mutation in one in four sperm and one in 12 eggs. Its impact on indels and structural variants is even higher, with 100- to 1300-fold increases in rates per break. We uncovered new mutational signatures and footprints relative to break sites, which implicate unexpected biochemical processes and error-prone DNA repair mechanisms, including translesion synthesis and end joining in meiotic break repair. We provide evidence that these mechanisms drive mutagenesis in human germ lines and lead to disruption of hundreds of genes genome wide.

Molecular characteristics in Chinese with chronic lymphocytic leukemia by next-generation sequencing: A single-center retrospective analysis

INTRODUCTION

Although the prevalence of Asian chronic lymphocytic leukemia (CLL) patients is not as high as that of Caucasians, there are more atypical CLLs in Asia whose genetic characteristics and their clinical significance are distinct and remain unclear.

METHODS

A retrospective analysis of 85 CLL samples in our center was conducted from 2019 to 2022. We used next-generation sequencing with a 172 gene panel to explore the multi-gene mutational data and the mutational status of immunoglobulin heavy variable (IGHV) gene.

RESULTS

MYD88 (20.0%) was the most frequently mutated gene, much higher than in Europe, followed in order by TP53 (18.8%), NOTCH1 (14.1%), IGLL5 (11.8%), and DNMT3A (8.2%). In addition, the incidence of ATM and SF3B1 mutations was relatively lower in our centre compared to Europe. Mutated (M)-IGHV patients were more likely to have a cooccurrence of MYD88 mutation, while complex karyotype and DNMT3A mutation were more common in the unmutated (U)-IGHV group. MYD88 mutated CLL was characterized by prevalence in young males in high-risk staging, with isolated 13q deletion and concomitant mutation of IGLL5. CLL patients with MYD88 and TP53 mutation showed an unfavorable prognosis.

CONCLUSION

These results would be valuable in helping to understand the characteristics and significance of cytogenetic genetics in Chinese patients with CLL.

Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma

The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL.

SIGNIFICANCE

Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.

Enhanced clinical assessment of hematologic malignancies through routine paired tumor and normal sequencing

Genomic profiling of hematologic malignancies has augmented our understanding of variants that contribute to disease pathogenesis and supported development of prognostic models that inform disease management in the clinic. Tumor only sequencing assays are limited in their ability to identify definitive somatic variants, which can lead to ambiguity in clinical reporting and patient management. Here, we describe the MSK-IMPACT Heme cohort, a comprehensive data set of somatic alterations from paired tumor and normal DNA using a hybridization capture-based next generation sequencing platform. We highlight patterns of mutations, copy number alterations, and mutation signatures in a broad set of myeloid and lymphoid neoplasms. We also demonstrate the power of appropriate matching to make definitive somatic calls, including in patients who have undergone allogeneic stem cell transplant. We expect that this resource will further spur research into the pathobiology and clinical utility of clinical sequencing for patients with hematologic neoplasms.

Mutations associated with progression in follicular lymphoma predict inferior outcomes at diagnosis: Alliance A151303

Follicular lymphoma (FL) is clinically heterogeneous, with select patients tolerating extended watch-and-wait, whereas others require prompt treatment, suffer progression of disease within 24 months of treatment (POD24), and/or experience aggressive histologic transformation (t-FL). Because our understanding of the relationship between genetic alterations in FL and patient outcomes remains limited, we conducted a clinicogenomic analysis of 370 patients with FL or t-FL (from Cancer and Leukemia Group B/Alliance trials 50402/50701/50803, or real-world cohorts from Washington University School of Medicine, Cleveland Clinic, or University of Miami). FL subsets by grade, stage, watch-and-wait, or POD24 status did not differ by mutation burden, whereas mutation burden was significantly higher in relapsed/refractory (rel/ref) FL and t-FL than in newly diagnosed (dx) FL. Nonetheless, mutation burden in dx FL was not associated with frontline progression-free survival (PFS). CREBBP was the only gene more commonly mutated in FL than in t-FL yet mutated CREBBP was associated with shorter frontline PFS in FL. Mutations in 20 genes were more common in rel/ref FL or t-FL than in dx FL, including 6 significantly mutated genes (SMGs): STAT6, TP53, IGLL5, B2M, SOCS1, and MYD88. We defined a mutations associated with progression (MAP) signature as ≥2 mutations in these 7 genes (6 rel/ref FL or t-FL SMGs plus CREBBP). Patients with dx FL possessing a MAP signature had shorter frontline PFS, revealing a 7-gene set offering insight into FL progression risk potentially more generalizable than the m7-Follicular Lymphoma International Prognostic Index (m7-FLIPI), which had modest prognostic value in our cohort. Future studies are warranted to validate the poor prognosis associated with a MAP signature in dx FL, potentially facilitating novel trials specifically in this high-risk subset of patients.

Pan-cancer proteogenomics connects oncogenic drivers to functional states

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.

The off-target effects of AID in carcinogenesis

Activation-induced cytidine deaminase (AID) plays a crucial role in promoting B cell diversification through somatic hypermutation (SHM) and class switch recombination (CSR). While AID is primarily associated with the physiological function of humoral immune response, it has also been linked to the initiation and progression of lymphomas. Abnormalities in AID have been shown to disrupt gene networks and signaling pathways in both B-cell and T-cell lineage lymphoblastic leukemia, although the full extent of its role in carcinogenesis remains unclear. This review proposes an alternative role for AID and explores its off-target effects in regulating tumorigenesis. In this review, we first provide an overview of the physiological function of AID and its regulation. AID plays a crucial role in promoting B cell diversification through SHM and CSR. We then discuss the off-target effects of AID, which includes inducing mutations of non-Igs, epigenetic modification, and the alternative role as a cofactor. We also explore the networks that keep AID in line. Furthermore, we summarize the off-target effects of AID in autoimmune diseases and hematological neoplasms. Finally, we assess the off-target effects of AID in solid tumors. The primary focus of this review is to understand how and when AID targets specific gene loci and how this affects carcinogenesis. Overall, this review aims to provide a comprehensive understanding of the physiological and off-target effects of AID, which will contribute to the development of novel therapeutic strategies for autoimmune diseases, hematological neoplasms, and solid tumors.

Mutational signatures reveal mutual exclusivity of homologous recombination and mismatch repair deficiencies in colorectal and stomach tumors

Decomposing somatic mutation spectra into mutational signatures and their corresponding etiologies provides a powerful approach for investigating the mechanism of DNA damage and repair. Assessing microsatellite (in)stability (MSI/MSS) status and interpreting their clinical relevance in different malignancies offers significant diagnostic and prognostic value. However, little is known about microsatellite (in)stability and its interactions with other DNA repair mechanisms such as homologous recombination (HR) in different cancer types. Based on whole-genome/exome mutational signature analysis, we showed HR deficiency (HRd) and mismatch repair deficiency (MMRd) occur in a significantly mutually exclusive manner in stomach and colorectal adenocarcinomas. ID11 signature with currently unknown etiology was prevalent in MSS tumors, co-occurred with HRd and was mutually exclusive with MMRd. Apolipoprotein B mRNA editing enzyme, Catalytic polypeptide-like (APOBEC) signature co-occurred with HRd and was mutually exclusive with MMRd in stomach tumors. The HRd signature in MSS tumors and the MMRd signature in MSI tumors were the first or second dominant signatures wherever detected. HRd may drive a distinct subgroup of MSS tumors and lead to poor clinical outcome. These analyses offer insight into mutational signatures in MSI and MMS tumors and reveal opportunities for improved clinical diagnosis and personalized treatment of MSS tumors.

Cancer aneuploidies are shaped primarily by effects on tumour fitness

Aneuploidies-whole-chromosome or whole-arm imbalances-are the most prevalent alteration in cancer genomes1,2. However, it is still debated whether their prevalence is due to selection or ease of generation as passenger events1,2. Here we developed a method, BISCUT, that identifies loci subject to fitness advantages or disadvantages by interrogating length distributions of telomere- or centromere-bounded copy-number events. These loci were significantly enriched for known cancer driver genes, including genes not detected through analysis of focal copy-number events, and were often lineage specific. BISCUT identified the helicase-encoding gene WRN as a haploinsufficient tumour-suppressor gene on chromosome 8p, which is supported by several lines of evidence. We also formally quantified the role of selection and mechanical biases in driving aneuploidy, finding that rates of arm-level copy-number alterations are most highly correlated with their effects on cellular fitness1,2. These results provide insight into the driving forces behind aneuploidy and its contribution to tumorigenesis.

Pirtobrutinib targets BTK C481S in ibrutinib-resistant CLL but second-site BTK mutations lead to resistance

Covalent inhibitors of Bruton tyrosine kinase (BTK) have transformed the therapy of chronic lymphocytic leukemia (CLL), but continuous therapy has been complicated by the development of resistance. The most common resistance mechanism in patients whose disease progresses on covalent BTK inhibitors (BTKis) is a mutation in the BTK 481 cysteine residue to which the inhibitors bind covalently. Pirtobrutinib is a highly selective, noncovalent BTKi with substantial clinical activity in patients whose disease has progressed on covalent BTKi, regardless of BTK mutation status. Using in vitro ibrutinib-resistant models and cells from patients with CLL, we show that pirtobrutinib potently inhibits BTK-mediated functions including B-cell receptor (BCR) signaling, cell viability, and CCL3/CCL4 chemokine production in both BTK wild-type and C481S mutant CLL cells. We demonstrate that primary CLL cells from responding patients on the pirtobrutinib trial show reduced BCR signaling, cell survival, and CCL3/CCL4 chemokine secretion. At time of progression, these primary CLL cells show increasing resistance to pirtobrutinib in signaling inhibition, cell viability, and cytokine production. We employed longitudinal whole-exome sequencing on 2 patients whose disease progressed on pirtobrutinib and identified selection of alternative-site BTK mutations, providing clinical evidence that secondary BTK mutations lead to resistance to noncovalent BTKis.

Molecular Evolution of Classic Hodgkin Lymphoma Revealed Through Whole-Genome Sequencing of Hodgkin and Reed Sternberg Cells

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells in classic Hodgkin lymphoma (cHL) limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Using this approach, we now report the whole-genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events leading to cHL. We identified alterations in driver genes not previously described in cHL, APOBEC mutational activity, and the presence of complex structural variants including chromothripsis. We found that high ploidy in cHL is often acquired through multiple, independent chromosomal gains events including whole-genome duplication. Evolutionary timing analyses revealed that structural variants enriched for RAG motifs, driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID-driven mutagenesis usually preceded large chromosomal gains. This study provides a temporal reconstruction of cHL pathogenesis.

SIGNIFICANCE

Previous studies in cHL were limited to coding sequences and therefore not able to comprehensively decipher the tumor complexity. Here, leveraging cHL whole-genome characterization, we identify driver events and reconstruct the tumor evolution, finding that structural variants, driver mutations, and AID mutagenesis precede chromosomal gains. This article is highlighted in the In This Issue feature, p. 171.

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.

Overcoming Cancer Multi-drug Resistance (MDR): Reasons, mechanisms, nanotherapeutic solutions, and challenges

Multi-drug resistance (MDR) in cancer cells, either intrinsic or acquired through various mechanisms, significantly hinders the therapeutic efficacy of drugs. Typically, the reduced therapeutic performance of various drugs is predominantly due to the inherent over expression of ATP-binding cassette (ABC) transporter proteins on the cell membrane, resulting in the deprived uptake of drugs, augmenting drug detoxification, and DNA repair. In addition to various physiological abnormalities and extensive blood flow, MDR cancer phenotypes exhibit improved apoptotic threshold and drug efflux efficiency. These severe consequences have substantially directed researchers in the fabrication of various advanced therapeutic strategies, such as co-delivery of drugs along with various generations of MDR inhibitors, augmented dosage regimens and frequency of administration, as well as combinatorial treatment options, among others. In this review, we emphasize different reasons and mechanisms responsible for MDR in cancer, including but not limited to the known drug efflux mechanisms mediated by permeability glycoprotein (P-gp) and other pumps, reduced drug uptake, altered DNA repair, and drug targets, among others. Further, an emphasis on specific cancers that share pathogenesis in executing MDR and effluxed drugs in common is provided. Then, the aspects related to various nanomaterials-based supramolecular programmable designs (organic- and inorganic-based materials), as well as physical approaches (light- and ultrasound-based therapies), are discussed, highlighting the unsolved issues and future advancements. Finally, we summarize the review with interesting perspectives and future trends, exploring further opportunities to overcome MDR.

Adjusting for common variant polygenic scores improves yield in rare variant association analyses

With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10-6), without marked increases in false-positive rates or genomic inflation. Benefits were seen for various models, with the largest improvements seen for efficient sparse mixed-effects models. Our results illustrate how polygenic score adjustment can efficiently improve power in rare variant association discovery.

Computational Methods Summarizing Mutational Patterns in Cancer: Promise and Limitations for Clinical Applications

Since the rise of next-generation sequencing technologies, the catalogue of mutations in cancer has been continuously expanding. To address the complexity of the cancer-genomic landscape and extract meaningful insights, numerous computational approaches have been developed over the last two decades. In this review, we survey the current leading computational methods to derive intricate mutational patterns in the context of clinical relevance. We begin with mutation signatures, explaining first how mutation signatures were developed and then examining the utility of studies using mutation signatures to correlate environmental effects on the cancer genome. Next, we examine current clinical research that employs mutation signatures and discuss the potential use cases and challenges of mutation signatures in clinical decision-making. We then examine computational studies developing tools to investigate complex patterns of mutations beyond the context of mutational signatures. We survey methods to identify cancer-driver genes, from single-driver studies to pathway and network analyses. In addition, we review methods inferring complex combinations of mutations for clinical tasks and using mutations integrated with multi-omics data to better predict cancer phenotypes. We examine the use of these tools for either discovery or prediction, including prediction of tumor origin, treatment outcomes, prognosis, and cancer typing. We further discuss the main limitations preventing widespread clinical integration of computational tools for the diagnosis and treatment of cancer. We end by proposing solutions to address these challenges using recent advances in machine learning.

Lymphoma-associated mutations in autoreactive memory B cells of patients with Sjögren's syndrome

We recently demonstrated that normal memory B lymphocytes carry a substantial number of de novo mutations in the genome. Here, we performed exome-wide somatic mutation analyses of bona fide autoreactive rheumatoid factor (RF)-expressing memory B cells retrieved from patients with Sjӧgren's syndrome (SS). The amount and repertoire of the de novo exome mutations of RF B cells were found to be essentially different from those detected in healthy donor memory B cells. In contrast to the mutation spectra of normal B cells, which appeared random and non-selected, the mutations of the RF B cells were greater in number and enriched for mutations in genes also found mutated in B-cell non-Hodgkin lymphomas. During the study, one of the SS patients developed a diffuse large B-cell lymphoma (DLBCL) out of an RF clone that was identified 2 years earlier in an inflamed salivary gland biopsy. The successive oncogenic events in the RF precursor clone and the DLBCL were assessed. In conclusion, our findings of enhanced and selected genomic damage in growth-regulating genes in RF memory B cells of SS patients together with the documented transformation of an RF-precursor clone into DLBCL provide unique novel insight into the earliest stages of B-cell derailment and lymphomagenesis. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers

Analysis of mutational signatures can reveal underlying molecular mechanisms of the processes that have imprinted the somatic mutations found in cancer genomes. Here, we analyze single base substitutions and small insertions and deletions in pediatric cancers encompassing 785 whole-genome sequenced tumors from 27 molecularly defined cancer subtypes. We identified only a small number of mutational signatures active in pediatric cancers, compared with previously analyzed adult cancers. Further, we report a significant difference in the proportion of pediatric tumors showing homologous recombination repair defect signatures compared with previous analyses. In pediatric leukemias, we identified an indel signature, not previously reported, characterized by long insertions in nonrepeat regions, affecting mainly intronic and intergenic regions, but also exons of known cancer genes. We provide a systematic overview of COSMIC v.3 mutational signatures active across pediatric cancers, which is highly relevant for understanding tumor biology and enabling future research in defining biomarkers of treatment response.

mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery

Mutational signatures are characteristic patterns of mutations caused by endogenous or exogenous mutational processes. These signatures can be discovered by analyzing mutations in large sets of samples-usually somatic mutations in tumor samples. Most programs for discovering mutational signatures are based on non-negative matrix factorization (NMF). Alternatively, signatures can be discovered using hierarchical Dirichlet process (HDP) mixture models, an approach that has been less explored. These models assign mutations to clusters and view each cluster as being generated from the signature of a particular mutational process. Here, we describe mSigHdp, an improved approach to using HDP mixture models to discover mutational signatures. We benchmarked mSigHdp and state-of-the-art NMF-based approaches on four realistic synthetic data sets. These data sets encompassed 18 cancer types. In total, they contained 3.5 × 10⁷ single-base-substitution mutations representing 32 signatures and 6.1 × 10⁶ small insertion and deletion mutations representing 13 signatures. For three of the four data sets, mSigHdp had the best positive predictive value for discovering mutational signatures, and for all four data sets, it had the best true positive rate. Its CPU usage was similar to that of the NMF-based approaches. Thus, mSigHdp is an important and practical addition to the set of tools available for discovering mutational signatures.

Unravelling the instability of mutational signatures extraction via archetypal analysis

The high cosine similarity between some single-base substitution mutational signatures and their characteristic flat profiles could suggest the presence of overfitting and mathematical artefacts. The newest version (v3.3) of the signature database available in the Catalogue Of Somatic Mutations In Cancer (COSMIC) provides a collection of 79 mutational signatures, which has more than doubled with respect to previous version (30 profiles available in COSMIC signatures v2), making more critical the associations between signatures and specific mutagenic processes. This study both provides a systematic assessment of the de novo extraction task through simulation scenarios based on the latest version of the COSMIC signatures and highlights, through a novel approach using archetypal analysis, which COSMIC signatures are redundant and more likely to be considered as mathematical artefacts. 29 archetypes were able to reconstruct the profile of all the COSMIC signatures with cosine similarity > 0.8. Interestingly, these archetypes tend to group similar original signatures sharing either the same aetiology or similar biological processes. We believe that these findings will be useful to encourage the development of new de novo extraction methods avoiding the redundancy of information among the signatures while preserving the biological interpretation.

Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome

Richter syndrome (RS) arising from chronic lymphocytic leukemia (CLL) exemplifies an aggressive malignancy that develops from an indolent neoplasm. To decipher the genetics underlying this transformation, we computationally deconvoluted admixtures of CLL and RS cells from 52 patients with RS, evaluating paired CLL-RS whole-exome sequencing data. We discovered RS-specific somatic driver mutations (including IRF2BP2, SRSF1, B2M, DNMT3A and CCND3), recurrent copy-number alterations beyond del(9p21)(CDKN2A/B), whole-genome duplication and chromothripsis, which were confirmed in 45 independent RS cases and in an external set of RS whole genomes. Through unsupervised clustering, clonally related RS was largely distinct from diffuse large B cell lymphoma. We distinguished pathways that were dysregulated in RS versus CLL, and detected clonal evolution of transformation at single-cell resolution, identifying intermediate cell states. Our study defines distinct molecular subtypes of RS and highlights cell-free DNA analysis as a potential tool for early diagnosis and monitoring.

Characterization of clonal immunoglobulin heavy V-D-J gene rearrangements in Chinese patients with chronic lymphocytic leukemia: Clinical features and molecular profiles

Introduction

Several prognostic factors of chronic lymphocytic leukemia (CLL) have been identified, such as cytogenetic aberrations and recurrent gene mutations. B-cell receptor (BCR) signaling plays an important role in the tumorigenesis of CLL, and its clinical significance in predicting prognosis is also under study.

Methods

Therefore, we assessed the already-known prognostic markers, immunoglobulin heavy chain (IGH) gene usage and the associations among these factors in 71 patients diagnosed with CLL in our center from October 2017 to March 2022. Sequencing of IGH gene rearrangements was performed using Sanger sequencing or IGH-based next-generation sequencing, and the results were further analyzed for distinct IGH/IGHD/IGHJ genes and the mutational status of the clonotypic IGHV (IGH variable) gene.

Results

In summary, by analyzing the distribution of potential prognostic factors in CLL patients, we displayed a landscape of molecular profiles, confirmed the predictive value of recurrent genetic mutations and chromosome aberrations, and found that IGHJ3 was associated with favorable markers (mutated IGHV, trisomy 12), while IGHJ6 tended to correlate with unfavorable factors (unmutated IGHV, del17p).

Discussion

These results provided an indication for IGH gene sequencing in predicting the prognosis of CLL.

Identification of key genes in late-onset major depressive disorder through a co-expression network module

Late-onset major depressive disorder (LOD) increases the risk of disability and suicide in elderly patients. However, the complex pathological mechanism of LOD still remains unclear. We selected 10 LOD patients and 12 healthy control samples from the GSE76826 dataset for statistical analysis. Under the screening criteria, 811 differentially expressed genes (DEGs) were screened. We obtained a total of two most clinically significant modules through the weighted gene co-expression network analysis (WGCNA). Functional analysis of the genes in the most clinically significant modules was performed to explore the potential mechanism of LOD, followed by protein-protein interaction (PPI) analysis and hub gene identification in the core area of the PPI network. Furthermore, we identified immune infiltrating cells using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm between healthy subjects and LOD patients with the GSE98793 dataset. Next, six hub genes (CD27, IL7R, CXCL1, CCR7, IGLL5, and CD79A) were obtained by intersecting hub genes with DEGs, followed by verifying the diagnostic accuracy with the receiver operating characteristic curve (ROC). In addition, we constructed the least absolute shrinkage and selection operator (LASSO) regression model for hub gene cross-validation. Finally, we found that CD27 and IGLL5 were good diagnostic indicators of LOD, and CD27 may be the key gene of immune function change in LOD. In conclusion, our research shows that the changes in the immune function may be an important mechanism in the development of LOD, which can provide some guidance for the related research of LOD in the future.

Pan-cancer landscape of AID-related mutations, composite mutations, and their potential role in the ICI response

Activation-induced cytidine deaminase, AICDA or AID, is a driver of somatic hypermutation and class-switch recombination in immunoglobulins. In addition, this deaminase belonging to the APOBEC family may have off-target effects genome-wide, but its effects at pan-cancer level are not well elucidated. Here, we used different pan-cancer datasets, totaling more than 50,000 samples analyzed by whole-genome, whole-exome, or targeted sequencing. AID mutations are present at pan-cancer level with higher frequency in hematological cancers and higher presence at transcriptionally active TAD domains. AID synergizes initial hotspot mutations by a second composite mutation. AID mutational load was found to be independently associated with a favorable outcome in immune-checkpoint inhibitors (ICI) treated patients across cancers after analyzing 2000 samples. Finally, we found that AID-related neoepitopes, resulting from mutations at more frequent hotspots if compared to other mutational signatures, enhance CXCL13/CCR5 expression, immunogenicity, and T-cell exhaustion, which may increase ICI sensitivity.

Immune biomarkers of response to immunotherapy in patients with high-risk smoldering myeloma

Patients with smoldering multiple myeloma (SMM) are observed until progression, but early treatment may improve outcomes. We conducted a phase II trial of elotuzumab, lenalidomide, and dexamethasone (EloLenDex) in patients with high-risk SMM and performed single-cell RNA and T cell receptor (TCR) sequencing on 149 bone marrow (BM) and peripheral blood (PB) samples from patients and healthy donors (HDs). We find that early treatment with EloLenDex is safe and effective and provide a comprehensive characterization of alterations in immune cell composition and TCR repertoire diversity in patients. We show that the similarity of a patient's immune cell composition to that of HDs may have prognostic relevance at diagnosis and after treatment and that the abundance of granzyme K (GZMK)+ CD8+ effector memory T (TEM) cells may be associated with treatment response. Last, we uncover similarities between immune alterations observed in the BM and PB, suggesting that PB-based immune profiling may have diagnostic and prognostic utility.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

Mathematical Modeling of Impacts of Patient Differences on COVID-19 Lung Fibrosis Outcomes

Patient-specific premorbidity, age, and sex are significant heterogeneous factors that influence the severe manifestation of lung diseases, including COVID-19 fibrosis. The renin-angiotensin system (RAS) plays a prominent role in regulating effects of these factors. Recent evidence suggests that patient-specific alteration of RAS homeostasis with premorbidity and the expression level of angiotensin converting enzyme 2 (ACE2), depending on age and sex, is correlated with lung fibrosis. However, conflicting evidence suggests decreases, increases, or no changes in RAS after SARS-CoV-2 infection. In addition, detailed mechanisms connecting the patient-specific conditions before infection to infection-induced fibrosis are still unknown. Here, a mathematical model is developed to quantify the systemic contribution of heterogeneous factors of RAS in the progression of lung fibrosis. Three submodels are connected-a RAS model, an agent-based COVID-19 in-host immune response model, and a fibrosis model-to investigate the effects of patient-group-specific factors in the systemic alteration of RAS and collagen deposition in the lung. The model results indicate cell death due to inflammatory response as a major contributor to the reduction of ACE and ACE2, whereas there are no significant changes in ACE2 dynamics due to viral-bound internalization of ACE2. Reduction of ACE reduces the homeostasis of RAS including angiotensin II (ANGII), while the decrease in ACE2 increases ANGII and results in severe lung injury and fibrosis. The model explains possible mechanisms for conflicting evidence of RAS alterations in previously published studies. Also, the results show that ACE2 variations with age and sex significantly alter RAS peptides and lead to fibrosis with around 20% additional collagen deposition from systemic RAS with slight variations depending on age and sex. This model may find further applications in patient-specific calibrations of tissue models for acute and chronic lung diseases to develop personalized treatments.

Bioinformatics roadmap for therapy selection in cancer genomics

Tumour heterogeneity is one of the main characteristics of cancer and can be categorised into inter- or intratumour heterogeneity. This heterogeneity has been revealed as one of the key causes of treatment failure and relapse. Precision oncology is an emerging field that seeks to design tailored treatments for each cancer patient according to epidemiological, clinical and omics data. This discipline relies on bioinformatics tools designed to compute scores to prioritise available drugs, with the aim of helping clinicians in treatment selection. In this review, we describe the current approaches for therapy selection depending on which type of tumour heterogeneity is being targeted and the available next-generation sequencing data. We cover intertumour heterogeneity studies and individual treatment selection using genomics variants, expression data or multi-omics strategies. We also describe intratumour dissection through clonal inference and single-cell transcriptomics, in each case providing bioinformatics tools for tailored treatment selection. Finally, we discuss how these therapy selection workflows could be integrated into the clinical practice.

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.

Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features

The value of genome-wide over targeted driver analyses for predicting clinical outcomes of cancer patients is debated. Here, we report the whole-genome sequencing of 485 chronic lymphocytic leukemia patients enrolled in clinical trials as part of the United Kingdom's 100,000 Genomes Project. We identify an extended catalog of recurrent coding and noncoding genetic mutations that represents a source for future studies and provide the most complete high-resolution map of structural variants, copy number changes and global genome features including telomere length, mutational signatures and genomic complexity. We demonstrate the relationship of these features with clinical outcome and show that integration of 186 distinct recurrent genomic alterations defines five genomic subgroups that associate with response to therapy, refining conventional outcome prediction. While requiring independent validation, our findings highlight the potential of whole-genome sequencing to inform future risk stratification in chronic lymphocytic leukemia.

Whole-exome sequencing analysis identifies distinct mutational profile and novel prognostic biomarkers in primary gastrointestinal diffuse large B-cell lymphoma

Background

Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma, and about 10% of DLBCL cases primarily occur in the gastrointestinal tract. Previous reports have revealed that primary gastrointestinal-DLBCL (pGI-DLBCL) harbors different genetic mutations from other nodal or extranodal DLBCL. However, the exonic mutation profile of pGI-DLBCL has not been fully addressed.

Methods

We performed whole-exome sequencing of matched tumor tissues and blood samples from 53 pGI-DLBCL patients. The exonic mutation profiles were screened, and the correlations between genetic mutations and clinicopathological characteristics were analyzed.

Results

A total of 6,588 protein-altering events were found and the five most frequent mutated genes in our pGI-DLBCL cohort were IGLL5 (47%), TP53 (42%), BTG2 (28%), P2RY8 (26%) and PCLO (23%). Compared to the common DLBCL, significantly less or absence of MYD88 (0%), EZH2 (0%), BCL2 (2%) or CD79B (8%) mutations were identified in pGI-DLBCL. The recurrent potential driver genes were mainly enriched in pathways related to signal transduction, infectious disease and immune regulation. In addition, HBV infection had an impact on the mutational signature in pGI-DLBCL, as positive HBsAg was significantly associated with the TP53 and LRP1B mutations, two established tumor suppressor genes in many human cancers. Moreover, IGLL5 and LRP1B mutations were significantly correlated with patient overall survival and could serve as two novel prognostic biomarkers in pGI-DLBCL.

Conclusions

Our study provides a comprehensive view of the exonic mutation profile of the largest pGI-DLBCL cohort to date. The results could facilitate the clinical development of novel therapeutic and prognostic biomarkers for pGI-DLBCL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40164-022-00325-7.

Loss of AID exacerbates the malignant progression of CLL

Activation-induced cytidine deaminase (AID) has been implicated as both a positive and a negative factor in the progression of B cell chronic lymphocytic leukemia (CLL), but the role that it plays in the development and progression of this disease is still unclear. We generated an AID knockout CLL mouse model, AID-/-/Eμ-TCL1, and found that these mice die significantly earlier than their AID-proficient counterparts. AID-deficient CLL cells exhibit a higher ER stress response compared to Eμ-TCL1 controls, particularly through activation of the IRE1/XBP1s pathway. The increased production of secretory IgM in AID-deficient CLL cells contributes to their elevated expression levels of XBP1s, while secretory IgM-deficient CLL cells express less XBP1s. This increase in XBP1s in turn leads AID-deficient CLL cells to exhibit higher levels of B cell receptor signaling, supporting leukemic growth and survival. Further, AID-/-/Eμ-TCL1 CLL cells downregulate the tumor suppressive SMAD1/S1PR2 pathway and have altered homing to non-lymphoid organs. Notably, CLL cells from patients with IgHV-unmutated disease express higher levels of XBP1s mRNA compared to those from patients with IgHV-mutated CLL. Our studies thus reveal novel mechanisms by which the loss of AID leads to worsened CLL and may explain why unmutated CLL is more aggressive than mutated CLL.

Detection of early seeding of Richter transformation in chronic lymphocytic leukemia

Richter transformation (RT) is a paradigmatic evolution of chronic lymphocytic leukemia (CLL) into a very aggressive large B cell lymphoma conferring a dismal prognosis. The mechanisms driving RT remain largely unknown. We characterized the whole genome, epigenome and transcriptome, combined with single-cell DNA/RNA-sequencing analyses and functional experiments, of 19 cases of CLL developing RT. Studying 54 longitudinal samples covering up to 19 years of disease course, we uncovered minute subclones carrying genomic, immunogenetic and transcriptomic features of RT cells already at CLL diagnosis, which were dormant for up to 19 years before transformation. We also identified new driver alterations, discovered a new mutational signature (SBS-RT), recognized an oxidative phosphorylation (OXPHOS)^high–B cell receptor (BCR)^low-signaling transcriptional axis in RT and showed that OXPHOS inhibition reduces the proliferation of RT cells. These findings demonstrate the early seeding of subclones driving advanced stages of cancer evolution and uncover potential therapeutic targets for RT.

Single-cell genomic and transcriptomic analyses of longitudinal samples of patients with Richter syndrome reveal the presence and dynamics of clones driving transformation from chronic lymphocytic leukemia years before clinical manifestation

Enabling Inference for Context-Dependent Models of Mutation by Bounding the Propagation of Dependency

Although the rates at which positions in the genome mutate are known to depend not only on the nucleotide to be mutated, but also on neighboring nucleotides, it remains challenging to do phylogenetic inference using models of context-dependent mutation. In these models, the effects of one mutation may in principle propagate to faraway locations, making it difficult to compute exact likelihoods. This article shows how to use bounds on the propagation of dependency to compute likelihoods of mutation of a given segment of genome by marginalizing over sufficiently long flanking sequence. This can be used for maximum likelihood or Bayesian inference. Protocols examining residuals and iterative model refinement are also discussed. Tools for efficiently working with these models are provided in an R package, which could be used in other applications. The method is used to examine context dependence of mutations since the common ancestor of humans and chimpanzee.