Comparative analysis of primary versus relapse/refractory DLBCL identifies shifts in mutation spectrum

Molecular targets of glucocorticoids that elucidate their therapeutic efficacy in aggressive lymphomas

Glucocorticoids have been used for decades to treat lymphomas without an established mechanism of action. Using functional genomic, proteomic, and chemical screens, we discover that glucocorticoids inhibit oncogenic signaling by the B cell receptor (BCR), a recurrent feature of aggressive B cell malignancies, including diffuse large B cell lymphoma and Burkitt lymphoma. Glucocorticoids induce the glucocorticoid receptor (GR) to directly transactivate genes encoding negative regulators of BCR stability (LAPTM5; KLHL14) and the PI3 kinase pathway (INPP5D; DDIT4). GR directly represses transcription of CSK, a kinase that limits the activity of BCR-proximal Src-family kinases. CSK inhibition attenuates the constitutive BCR signaling of lymphomas by hyperactivating Src-family kinases, triggering their ubiquitination and degradation. With the knowledge that glucocorticoids disable oncogenic BCR signaling, they can now be deployed rationally to treat BCR-dependent aggressive lymphomas and used to construct mechanistically sound combination regimens with inhibitors of BTK, PI3 kinase, BCL2, and CSK.

Genetic and transcriptomic analyses of diffuse large B-cell lymphoma patients with poor outcomes within two years of diagnosis

Despite the improvements in clinical outcomes for DLBCL, a significant proportion of patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. To further elucidate the underlying mechanism of R/R disease and to develop methods for identifying patients at risk of early disease progression, we integrated clinical, genetic and transcriptomic data derived from 2805 R-CHOP-treated patients from seven independent cohorts. Among these, 887 patients exhibited R/R disease within two years (poor outcome), and 1918 patients remained in remission at two years (good outcome). Our analysis identified four preferentially mutated genes (TP53, MYD88, SPEN, MYC) in the untreated (diagnostic) tumor samples from patients with poor outcomes. Furthermore, transcriptomic analysis revealed a distinct gene expression pattern linked to poor outcomes, affecting pathways involved in cell adhesion/migration, T-cell activation/regulation, PI3K, and NF-κB signaling. Moreover, we developed and validated a 24-gene expression score as an independent prognostic predictor for treatment outcomes. This score also demonstrated efficacy in further stratifying high-risk patients when integrated with existing genetic or cell-of-origin subtypes, including the unclassified cases in these models. Finally, based on these findings, we developed an online analysis tool ( https://lymphprog.serve.scilifelab.se/app/lymphprog ) that can be used for prognostic prediction for DLBCL patients.

Safety and efficacy of canakinumab treatment for undifferentiated autoinflammatory diseases: the data of a retrospective cohort two-centered study

Introduction

The blockade of interleukine-1 (anakinra and canakinumab) is a well-known highly effective tool for monogenic autoinflammatory diseases (AIDs), such as familial Mediterranean fever, tumor necrosis factor receptor-associated periodic syndrome, hyperimmunoglobulinaemia D syndrome, and cryopyrin-associated periodic syndrome, but this treatment has not been assessed for patients with undifferentiated AIDs (uAIDs). Our study aimed to assess the safety and efficacy of canakinumab for patients with uAIDs.

Methods

Information on 32 patients with uAIDs was retrospectively collected and analyzed. Next-generation sequencing and Federici criteria were used for the exclusion of the known monogenic AID.

Results

The median age of the first episode was 2.5 years (IQR: 1.3; 5.5), that of the disease diagnosis was 5.7 years (IQR: 2.5;12.7), and that of diagnostic delay was 1.1 years (IQR: 0.4; 6.1). Patients had variations in the following genes: IL10, NLRP12, STAT2, C8B, LPIN2, NLRC4, PSMB8, PRF1, CARD14, IFIH1, LYST, NFAT5, PLCG2, COPA, IL23R, STXBP2, IL36RN, JAK1, DDX58, LACC1, LRBA, TNFRSF11A, PTHR1, STAT4, TNFRSF1B, TNFAIP3, TREX1, and SLC7A7. The main clinical features were fever (100%), rash (91%; maculopapular predominantly), joint involvement (72%), splenomegaly (66%), hepatomegaly (59%), lymphadenopathy (50%), myalgia (28%), heart involvement (31%), intestinal involvement (19%); eye involvement (9%), pleuritis (16%), ascites (6%), deafness, hydrocephalia (3%), and failure to thrive (25%). Initial treatment before canakinumab consisted of non-biologic therapies: non-steroidal anti-inflammatory drugs (NSAID) (91%), corticosteroids (88%), methotrexate (38%), intravenous immunoglobulin (IVIG) (34%), cyclosporine A (25%), colchicine (6%) cyclophosphamide (6%), sulfasalazine (3%), mycophenolate mofetil (3%), hydroxychloroquine (3%), and biologic drugs: tocilizumab (62%), sarilumab, etanercept, adalimumab, rituximab, and infliximab (all 3%). Canakinumab induced complete remission in 27 patients (84%) and partial remission in one patient (3%). Two patients (6%) were primary non-responders, and two patients (6%) further developed secondary inefficacy. All patients with partial efficacy or inefficacy were switched to tocilizumab (n = 4) and sarilumab (n = 1). The total duration of canakinumab treatment was 3.6 (0.1; 8.7) years. During the study, there were no reported Serious Adverse Events (SAEs). The patients experienced non-frequent mild respiratory infections at a rate that is similar as before canakinumab is administered. Additionally, one patient developed leucopenia, but it was not necessary to stop canakinumab for this patient.

Conclusion

The treatment of patients with uAIDs using canakinumab was safe and effective. Further randomized clinical trials are required to confirm the efficacy and safety.

Biological heterogeneity in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is heterogeneous both in clinical outcomes and the underlying disease biology. Over the last 2 decades, several different approaches for dissecting biological heterogeneity have emerged. Gene expression profiling (GEP) stratifies DLBCL into 3 broad groups (ABC, GCB, and DZsig/MHG), each with parallels to different normal mature B cell developmental states and prognostic implications. More recently, several different genomic approaches have been developed to categorize DLBCL based on the co-occurrence of tumor somatic mutations, identifying more granular biologically unified subgroups that complement GEP-based approaches. We review the molecular approaches and clinical evidence supporting the stratification of DLBCL patients based on tumor biology. By offering a platform for subtype-guided therapy, these divisions remain a promising avenue for improving patient outcomes, especially in subgroups with inferior outcomes with current standard-of-care therapy.

Sequence analyses of relapsed or refractory diffuse large B-cell lymphomas unravel three genetic subgroups of patients and the GNA13 mutant as poor prognostic biomarker, results of LNH-EP1 study

Advances in molecular profiling of newly diagnosed diffuse large B-cell lymphoma (DLBCL) have recently refine genetic subgroups. Genetic subgroups remain undetermined at the time of relapse or refractory (RR) disease. This study aims to decipher genetic subgroups and search for prognostic molecular biomarkers in patients with RR-DLBCL. From 2015 to 2021, targeted next-generation sequencing analyses of germline-matched tumor samples and fresh tissue from RR-DLBCL patients were performed. Unsupervised clustering of somatic mutations was performed and correlations with patient outcome were sought. A number of 120 patients with RR-DLBCL were included in LNH-EP1 study and a molecular tumor landscape was successfully analyzed in 87% of patients (104/120 tumor samples). The median age was 67.5 years (range 27.4-87.4), median number of previous treatments was 2 (range 1-9). The most frequently mutated genes were TP53 (n = 53 mutations; 42% of samples), CREBBP (n = 39; 32%), BCL2 (n = 86; 31%), KMT2D (n = 39; 28%) and PIM1 (n = 54; 22%). Unsupervised clustering separated three genetic subgroups entitled BST (enriched in BCL2, SOCS1, and TNFRSF14 mutations); TKS (enriched in TP53, KMT2D, and STAT6 mutations); and PCM (enriched in PIM1, CD79B, and MYD88 mutations). Median overall survival (OS) was 11.0 (95% confidence interval [CI]: 8.1-12.6) months. OS was not significantly different between the three genetic subgroups. GNA13 mutant was significantly associated with an increased risk of death (hazard ratio: 6.6 [95% CI: 2.1-20.6]; p = .0011) and shorter OS (p = .0340). At the time of relapse or refractory disease, three genetic subgroups of DLBCL patients were delineated, which could help advance precision molecular medicine programs.

Longitudinal expression profiling identifies a poor risk subset of patients with ABC-type diffuse large B-cell lymphoma

Despite the effectiveness of immuno-chemotherapy, 40% of patients with diffuse large B-cell lymphoma (DLBCL) experience relapse or refractory disease. Longitudinal studies have previously focused on the mutational landscape of relapse but fell short of providing a consistent relapse-specific genetic signature. In our study, we have focused attention on the changes in GEP accompanying DLBCL relapse using archival paired diagnostic/relapse specimens from 38 de novo patients with DLBCL. COO remained stable from diagnosis to relapse in 80% of patients, with only a single patient showing COO switching from activated B-cell-like (ABC) to germinal center B-cell-like (GCB). Analysis of the transcriptomic changes that occur following relapse suggest ABC and GCB relapses are mediated via different mechanisms. We developed a 30-gene discriminator for ABC-DLBCLs derived from relapse-associated genes that defined clinically distinct high- and low-risk subgroups in ABC-DLBCLs at diagnosis in datasets comprising both population-based and clinical trial cohorts. This signature also identified a population of <60-year-old patients with superior PFS and OS treated with ibrutinib-R-CHOP as part of the PHOENIX trial. Altogether this new signature adds to the existing toolkit of putative genetic predictors now available in DLBCL that can be readily assessed as part of prospective clinical trials.

In-depth characterization of intratumoral heterogeneity in refractory B-cell non-Hodgkin lymphoma through the lens of a Research Autopsy Program

Intratumoral heterogeneity (ITH) provides the substrate for tumor evolution and treatment resistance, yet is remarkably understudied in lymphoma, due to the often limited amount of tissue that gets sampled during the routine diagnostic process, generally from a single nodal or extranodal site. Furthermore, the trajectory of how lymphoma, and especially non-Hodgkin lymphoma, spreads throughout the human body remains poorly understood. Here, we present a detailed characterization of ITH by applying whole-genome sequencing to spatially separated tumor samples harvested at the time of autopsy (n=24) and/or diagnosis (n=3) in three patients presenting with refractory B-cell non-Hodgkin lymphoma. Through deconvolution of bulk samples into clonal mixtures and inference of phylogenetic trees, we found evidence that polyclonal seeding underlies tumor dissemination in lymphoma. We identify mutation signatures associated with ancestral and descendant clones. In our series of patients with highly refractory lymphoma, the determinants of resistance were often harbored by founding clones, although there was also evidence of positive selection of driver mutations, likely under the influence of therapy. Lastly, we show that circulating tumor DNA is suitable for the detection of ancestral mutations but may miss a significant proportion of private mutations that can be detected in tissue. Our study clearly shows the existence of intricate patterns of regional and anatomical evolution that can only be disentangled through multi-regional tumor tissue profiling.

Genetic Landscape of Relapsed and Refractory Diffuse Large B-Cell Lymphoma: A Systemic Review and Association Analysis With Next-Generation Sequencing

In our research, we screened 1,495 documents, compiled the whole-exome sequencing data of several studies, formed a data set including 92 observations of RRDLBCL (Relapsed and refractory diffuse large B-cell lymphoma), and performed association analysis on the high-frequency mutations among them. The most common mutations in the data set include TTN, KMT2D, TP53, IGLL5, CREBBP, BCL2, MYD88, and SOCS1 etc. Among these, CREBBP, KMT2D, and BCL2 have a strong association with each other, and SOCS1 has a strong association with genes such as STAT6, ACTB, CIITA, ITPKB, and GNA13. TP53 lacks significant associations with most genes. Through SOM clustering, expression-level analysis and protein interaction analysis of common gene mutations, we believe that RRDLBCL can be divided into five main types. We tested the function of the model and described the clinical characteristics of each subtype through a targeted sequencing RRDLBCL cohort of 96 patients. The classification is stated as follows: 1) JAK-STAT-related type: including STAT6, SOCS1, CIITA, etc. The genetic lineage is similar to PMBL and cHL. Retrospective analysis suggests that this subtype responds poorly to induction therapy (R-CHOP, p < 0.05). 2) BCL-CREBBP type: Epigenetic mutations such as KMT2D and CREBBP are more common in this type, and are often accompanied by BCL2 and EZH2 mutations. 3) MCD type: including MYD88 and CD79B, PIM1 is more common in this subtype. 4) TP53 mutation: TP53 mutant patients, which suggests the worst prognosis (p < 0.05) and worst response to CART treatment. 5) Undefined type (Sparse item type): Major Genetic Change Lacking Type, which has a better prognosis and better response to CART treatment. We also reviewed the literature from recent years concerning the previously mentioned common gene mutations.

Effect of ibrutinib with R-CHOP chemotherapy in genetic subtypes of DLBCL

In diffuse large B cell lymphoma (DLBCL), tumors belonging to the ABC but not GCB gene expression subgroup rely upon chronic active B cell receptor signaling for viability, a dependency that is targetable by ibrutinib. A phase III trial ("Phoenix;" ClinicalTrials.gov: NCT01855750) showed a survival benefit of ibrutinib addition to R-CHOP chemotherapy in younger patients with non-GCB DLBCL, but the molecular basis for this benefit was unclear. Analysis of biopsies from Phoenix trial patients revealed three previously characterized genetic subtypes of DLBCL: MCD, BN2, and N1. The 3-year event-free survival of younger patients (age ≤60 years) treated with ibrutinib plus R-CHOP was 100% in the MCD and N1 subtypes while the survival of patients with these subtypes treated with R-CHOP alone was significantly inferior (42.9% and 50%, respectively). This work provides a mechanistic understanding of the benefit of ibrutinib addition to chemotherapy, supporting its use in younger patients with non-GCB DLBCL.

The mutational profile of immune surveillance genes in diagnostic and refractory/relapsed DLBCLs

Background

Diffuse large B-cell lymphoma (DLBCL) is the most frequent lymphoid neoplasm among adults,and approximately 30–40% of patients will experience relapse while 5–10% will suffer from primary refractory disease caused by different mechanisms, including treatment-induced resistance. For refractory and relapsed DLBCL (rrDLBCL) patients, early detection and understanding of the mechanisms controlling treatment resistance are of great importance to guide therapy decisions. Here, we have focused on genetic variations in immune surveillance genes in diagnostic DLBCL (dDLBCL) and rrDLBCL patients to elaborate on the suitability of new promising immunotherapies.

Methods

Biopsies from 30 dDLBCL patients who did not progress or relapse during follow up and 17 rrDLBCL patients with refractory disease or who relapsed during follow up were analyzed by whole-exome sequencing, including matched individual germline samples to include only somatic genetic variants in downstream analysis of a curated list of 58 genes involved in major immune surveillance pathways.

Results

More than 70% of both dDLBCLs and rrDLBCLs harbored alterations in immune surveillance genes, but rrDLBCL tumor samples have a lower number of genes affected compared to dDLBCL tumor samples. Increased gene mutation frequencies in rrDLBCLs were observed in more than half of the affected immune surveillance genes than dDLBCLs.

Conclusion

Genetic variants in the antigen-presenting genes affect a higher number of rrDLBCL patients supporting an important role for these genes in tumor progression and development of refractory disease and relapse.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08556-3.

Mutational dynamics and immune evasion in diffuse large B-cell lymphoma explored in a relapse-enriched patient series

Diagnostic and relapse diffuse large B-cell lymphoma (DLBCL) biopsies reveal increased mutational burden/loss of heterozygosity in HLA-A. Serially sampled tumor biopsies provide insight into therapeutic targets and evolutionary divergence in relapsed/refractory DLBCL.

Molecular Genetics of Relapsed Diffuse Large B-Cell Lymphoma: Insight into Mechanisms of Therapy Resistance

The majority of patients with diffuse large B-cell lymphoma (DLBCL) can be treated successfully with a combination of chemotherapy and the monoclonal anti-CD20 antibody rituximab. Nonetheless, approximately one-third of the patients with DLBCL still experience relapse or refractory (R/R) disease after first-line immunochemotherapy. Whole-exome sequencing on large cohorts of primary DLBCL has revealed the mutational landscape of DLBCL, which has provided a framework to define novel prognostic subtypes in DLBCL. Several studies have investigated the genetic alterations specifically associated with R/R DLBCL, thereby uncovering molecular pathways linked to therapy resistance. Here, we summarize the current state of knowledge regarding the genetic alterations that are enriched in R/R DLBCL, and the corresponding pathways affected by these gene mutations. Furthermore, we elaborate on their potential role in mediating therapy resistance, also in connection with findings in other B-cell malignancies, and discuss alternative treatment options. Hence, this review provides a comprehensive overview on the gene lesions and molecular mechanisms underlying R/R DLBCL, which are considered valuable parameters to guide treatment.

Genetic and evolutionary patterns of treatment resistance in relapsed B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) patients are typically treated with immunochemotherapy containing rituximab (rituximab, cyclophosphamide, hydroxydaunorubicin-vincristine (Oncovin), and prednisone [R-CHOP]); however, prognosis is extremely poor if R-CHOP fails. To identify genetic mechanisms contributing to primary or acquired R-CHOP resistance, we performed target-panel sequencing of 135 relapsed/refractory DLBCLs (rrDLBCLs), primarily comprising circulating tumor DNA from patients on clinical trials. Comparison with a metacohort of 1670 diagnostic DLBCLs identified 6 genes significantly enriched for mutations upon relapse. TP53 and KMT2D were mutated in the majority of rrDLBCLs, and these mutations remained clonally persistent throughout treatment in paired diagnostic-relapse samples, suggesting a role in primary treatment resistance. Nonsense and missense mutations affecting MS4A1, which encodes CD20, are exceedingly rare in diagnostic samples but show recurrent patterns of clonal expansion following rituximab-based therapy. MS4A1 missense mutations within the transmembrane domains lead to loss of CD20 in vitro, and patient tumors harboring these mutations lacked CD20 protein expression. In a time series from a patient treated with multiple rounds of therapy, tumor heterogeneity and minor MS4A1-harboring subclones contributed to rapid disease recurrence, with MS4A1 mutations as founding events for these subclones. TP53 and KMT2D mutation status, in combination with other prognostic factors, may be used to identify high-risk patients prior to R-CHOP for posttreatment monitoring. Using liquid biopsies, we show the potential to identify tumors with loss of CD20 surface expression stemming from MS4A1 mutations. Implementation of noninvasive assays to detect such features of acquired treatment resistance may allow timely transition to more effective treatment regimens.

The interval between progression and therapy initiation is the key prognostic parameter in relapsing diffuse large B cell lymphoma: analysis from the Czech Lymphoma Study Group database (NIHIL)

Relapsing diffuse large B cell lymphomas (rDLBCL) represent a heterogeneous disease. This heterogeneity should be recognized and reflected, because it can deform the interpretation of clinical trial results. DLBCL patients with the first relapse and without CNS involvement were identified in the Czech Lymphoma Study Group (CLSG) database. Interval-to-therapy (ITT) was defined as the time between the first manifestation of rDLBCL and the start of any treatment. The overall survival (OS) of different ITT cohorts (< 7 vs. 7-21 vs. > 21 days) was compared. In total, 587 rDLBCLs (51.8% males) progressed with a median of 12.8 months (range 1.6 to 152.3) since the initial diagnosis (2000-2017). At the time of relapse, the median age was 67 years (range 22-95). First-line therapy was administered in 99.3% of the patients; CHOP and anti-CD20 were given to 69.2% and 84.7% of the patients, respectively. The salvage immune/chemotherapy was administered in 88.1% of the patients (39.2% platinum-based regimen). The median ITT was 20 days (range 1-851), but 23.2% of patients initiated therapy within 7 days. The 5-year OS was 17.4% (range 10-24.5%) vs. 20.5% (range 13.5-27.4%) vs. 42.2% (range 35.5-48.8%) for ITT < 7 vs. 7-21 vs. > 21 days (p < 0.001). ITT was associated with B symptoms (p 0.004), ECOG (p < 0.001), stage (p 0.002), bulky disease (p 0.005), elevated LDH (p < 0.001), and IPI (p < 0.001). The ITT mirrors the real clinical behavior of rDLBCL. There are patients (ITT < 7 days) with aggressive disease and a poor outcome. Conversely, there are rDLBCLs with ITT ≥ 21 days who survive for a long time.

Mutational landscape of immune surveillance genes in diffuse large B-cell lymphoma

INTRODUCTION

Immune surveillance is the dynamic process whereby the immune system identifies and kills tumor cells based on their aberrant expression of stress-related surface molecules or presentation of tumor neoantigens. It plays a crucial role in controlling the initiation and progression of hematologic cancers such as leukemia and lymphoma, and it has been reported that diffuse large B-cell lymphoma (DLBCL) fails to express specific cell-surface molecules that are necessary for the recognition and elimination of tumor cells.

AREAS COVERED

This review is based on a systematic search strategy to identify relevant literature in the PubMed and Embase databases. Ten candidate genes are identified based on mutational frequency, and functions with detailed mapping performed for hotspot alterations that may have a functional impact on malignant transformation and decreased immune surveillance efficacy.

EXPERT OPINION

Ongoing development of technology and bioinformatics tools combined with data from large clinical cohorts have the potential to define the mutational landscape associated with immune surveillance in DLBCL. Specific functional studies are required to make an unambiguous link between genetic aberrations and biological impact on impaired immune surveillance.

Genetic alterations and their clinical implications in DLBCL

Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous lymphoid neoplasm with variations in gene expression profiles and genetic alterations, which lead to substantial variations in clinical course and response to therapy. The advent of high-throughput genome sequencing platforms, and especially whole-exome sequencing, has helped to define the genetic landscape of DLBCL. In the past 10 years, these studies have identified many genetic alterations in DLBCL, some of which are specific to B cell lymphomas, whereas others can also be observed in other types of cancer. These aberrations result in altered activation of a wide range of signalling pathways and other cellular processes, including those involved in B cell differentiation, B cell receptor signalling, activation of the NF-κB pathway, apoptosis and epigenetic regulation. Further elaboration of the genetics of DLBCL will not only improve our understanding of disease pathogenesis but also provide further insight into disease classification, prognostication and therapeutic targets. In this Review, we describe the current understanding of the prevalence and causes of specific genetic alterations in DLBCL and their role in disease development and progression. We also summarize the available clinical data on therapies designed to target the aberrant pathways driven by these alterations.

Mutations found in cell-free DNAs of patients with malignant lymphoma at remission can derive from clonal hematopoiesis

Cell-free DNA (cfDNA) analysis to detect circulating tumor DNA has been focused on monitoring malignant lymphomas. However, clonal hematopoiesis of indeterminate potential (CHIP)-associated mutations can also be detected by cfDNA analysis. Our aim is to investigate the origin of mutations detected in cfDNA among B-cell lymphoma patients. MYD88/CD79B, DNMT3A, and TP53 were chosen as genes of interest, representing each of the following categories: lymphoma driver genes, CHIP-related genes, and genes shared between lymphoma and CHIP. Seventy-five B-cell lymphoma patients were included in this retrospective study. Serum cfDNAs at time of complete metabolic response (CMR) were sequenced for TP53 (N = 75) and DNMT3A (N = 49). MYD88 p.L265P and CD79B p.Y196C/H mutations were analyzed in diffuse large B-cell lymphoma (DLBCL) patients whose tumor samples were available (N = 29). Two and seven mutations in TP53 and DNMT3A, respectively, were detected in cfDNA at CMR. These mutations were detected in either bone marrow mononuclear cells (BMMC) or PBMC. Although four DNMT3A mutations were also detected in tumors, median variant allele frequencies in the tumors (<1.0%) were significantly lower than those in both BMMC (6.1%) and serum (5.2%) obtained before the therapy. Conversely, five MYD88 and three CD79B mutations detected in tumors were confirmed in cfDNA before therapy, but not in BMMC nor in cfDNA at CMR. Thus, all TP53 and DNMT3A mutations detected in cfDNA at remission seemed to originate from CHIP rather than from residual disease. Results of liquid biopsy should be carefully interpreted, especially in genes shared between lymphomas and CHIP.

Precision Medicine in Pediatric Cancer: Current Applications and Future Prospects

Precision oncologic medicine is an emerging approach for cancer treatment that has recently taken giant steps in solid clinical practice. Recent advances in molecular diagnostics that can analyze the individual tumor’s variability in genes have provided greater understanding and additional strategies to treat cancers. Although tumors can be tested by several molecular methods, the use of next-generation sequencing (NGS) has greatly facilitated our understanding of pediatric cancer and identified additional therapeutic opportunities. Pediatric tumors have a different genetic make-up, with a fewer number of actionable targets than adult tumors. Nevertheless, precision oncology in the pediatric population has greatly improved the survival of patients with leukemia and solid tumors. This review discusses the current status of pediatric precision oncology and the different clinical scenarios in which it can be effectively applied.

The Dynamic Roles of TGF-β Signalling in EBV-Associated Cancers

The transforming growth factor-β (TGF-β) signalling pathway plays a critical role in carcinogenesis. It has a biphasic action by initially suppressing tumorigenesis but promoting tumour progression in the later stages of disease. Consequently, the functional outcome of TGF-β signalling is strongly context-dependent and is influenced by various factors including cell, tissue and cancer type. Disruption of this pathway can be caused by various means, including genetic and environmental factors. A number of human viruses have been shown to modulate TGF-β signalling during tumorigenesis. In this review, we describe how this pathway is perturbed in Epstein-Barr virus (EBV)-associated cancers and how EBV interferes with TGF-β signal transduction. The role of TGF-β in regulating the EBV life cycle in tumour cells is also discussed.