Evolution and impact of subclonal mutations in chronic lymphocytic leukemia

Subclonal TP53 mutations are frequent and predict resistance to radioimmunotherapy in follicular lymphoma

Although TP53 is commonly mutated in transformed follicular lymphoma, mutations are reported in <5% of pretreatment follicular lymphoma (FL) specimens. We assayed archival follicular B-cell non-Hodgkin lymphoma specimens from a completed clinical trial, Southwest Oncology Group S0016, a phase 3 randomized intergroup trial of CHOP (cyclophosphamide, hydroxydaunorubicin, oncovin, and prednisone) chemotherapy plus R-CHOP (rituximab-CHOP) compared with CHOP chemotherapy plus 131-iodine tositumomab (radioimmunotherapy [RIT]-CHOP). Subclonal TP53 mutations (median allele frequency 0.02) were found in 25% of diagnostic FL specimens and in 27% of a separate validation cohort. In the R-CHOP arm, pathogenic TP53 mutations were not associated with progression-free survival (PFS) (10-year PFS 43% vs 44%). In contrast, among patients with no detectable pathogenic TP53 mutation, RIT-CHOP was associated with a longer PFS than with R-CHOP (10-year PFS 67% vs 44%; hazard ratio = 0.49; P = .008). No relationship was detected between PFS and the extent of activation-induced cytidine deaminase (AICDA)-mediated heterogeneity. In summary, subclonal TP53 mutations are common in FL and are a distinct phenomenon from AICDA-mediated genetic heterogeneity. The absence of a detectable subclonal mutation in TP53 defined a population that particularly benefited from RIT.

In Vitro 3D Spheroid Culture System Displays Sustained T Cell-dependent CLL Proliferation and Survival

Chronic lymphocytic leukemia (CLL) cells are highly dependent on microenvironmental cells and signals. The lymph node (LN) is the critical site of in vivo CLL proliferation and development of resistance to both chemotherapy and targeted agents. We present a new model that incorporates key aspects of the CLL LN, which enables investigation of CLL cells in the context of a protective niche. We describe a three-dimensional (3D) in vitro culture system using ultra-low attachment plates to create spheroids of CLL cells derived from peripheral blood. Starting from CLL:T cell ratios as observed in LN samples, CLL activation was induced by either direct stimulation and/or indirectly via T cells. Compared with two-dimensional cultures, 3D cultures promoted CLL proliferation in a T cell-dependent manner, and enabled expansion for up to 7 weeks, including the formation of follicle-like structures after several weeks of culture. This model enables high-throughput drug screening, of which we describe response to Btk inhibition, venetoclax resistance, and T cell-mediated cytotoxicity as examples. In summary, we present the first LN-mimicking in vitro 3D culture for primary CLL, which enables readouts such as real-time drug screens, kinetic growth assays, and spatial localization. This is the first in vitro CLL system that allows testing of response and resistance to venetoclax and Bruton's tyrosine kinase inhibitors in the context of the tumor microenvironment, thereby opening up new possibilities for clinically useful applications.

A Leukemic Target with a Thousand Faces: The Mitochondria

In the era of personalized medicine greatly improved by molecular diagnosis and tailor-made therapies, the survival rate of acute myeloid leukemia (AML) at 5 years remains unfortunately low. Indeed, the high heterogeneity of AML clones with distinct metabolic and molecular profiles allows them to survive the chemotherapy-induced changes, thus leading to resistance, clonal evolution, and relapse. Moreover, leukemic stem cells (LSCs), the quiescent reservoir of residual disease, can persist for a long time and activate the recurrence of disease, supported by significant metabolic differences compared to AML blasts. All these points highlight the relevance to develop combination therapies, including metabolism inhibitors to improve treatment efficacy. In this review, we summarized the metabolic differences in AML blasts and LSCs, the molecular pathways related to mitochondria and metabolism are druggable and targeted in leukemia therapies, with a distinct interest for Venetoclax, which has revolutionized the therapeutic paradigms of several leukemia subtype, unfit for intensive treatment regimens.

Clonal architecture and evolutionary history of Waldenström's macroglobulinemia at the single-cell level

To provide insight into the subclonal architecture and co-dependency patterns of the alterations in Waldenström's macroglobulinemia (WM), we performed single-cell mutational and protein profiling of eight patients. A custom panel was designed to screen for mutations and copy number alterations at the single-cell level in samples taken from patients at diagnosis (n=5) or at disease progression (n=3). Results showed that in asymptomatic WM at diagnosis, MYD88L265P was the predominant clonal alteration; other events, if present, were secondary and subclonal to MYD88L265P. In symptomatic WM, clonal diversity was more evident, uncovering combinations of alterations that synergized to promote clonal expansion and dominance. At disease progression, a dominant clone was observed, sometimes accompanied by other less complex minor clones, which could be consistent with a clonal selection process. Clonal diversity was also reduced, probably due to the effect of treatment. Finally, we combined protein expression with mutational analysis to map somatic genotype with the immunophenotype. Our findings provide a comprehensive view of the clonality of tumor populations in WM and how clonal complexity can evolve and impact disease progression.

SF3B1 hotspot mutations confer sensitivity to PARP inhibition by eliciting a defective replication stress response

SF3B1 hotspot mutations are associated with a poor prognosis in several tumor types and lead to global disruption of canonical splicing. Through synthetic lethal drug screens, we identify that SF3B1 mutant (SF3B1MUT) cells are selectively sensitive to poly (ADP-ribose) polymerase inhibitors (PARPi), independent of hotspot mutation and tumor site. SF3B1MUT cells display a defective response to PARPi-induced replication stress that occurs via downregulation of the cyclin-dependent kinase 2 interacting protein (CINP), leading to increased replication fork origin firing and loss of phosphorylated CHK1 (pCHK1; S317) induction. This results in subsequent failure to resolve DNA replication intermediates and G2/M cell cycle arrest. These defects are rescued through CINP overexpression, or further targeted by a combination of ataxia-telangiectasia mutated and PARP inhibition. In vivo, PARPi produce profound antitumor effects in multiple SF3B1MUT cancer models and eliminate distant metastases. These data provide the rationale for testing the clinical efficacy of PARPi in a biomarker-driven, homologous recombination proficient, patient population.

Using Intratumor Heterogeneity of Immunohistochemistry Biomarkers to Classify Laryngeal and Hypopharyngeal Tumors Based on Histologic Features

Haralick texture features are used to quantify the spatial distribution of signal intensities within an image. In this study, the heterogeneity of proliferation (Ki-67 expression) and immune cells (CD45 expression) within tumors was quantified and used to classify histologic characteristics of larynx and hypopharynx carcinomas. Of 21 laryngectomy specimens, 74 whole-mount tumor slides were scored on histologic characteristics. Ki-67 and CD45 immunohistochemistry was performed, and all sections were digitized. The tumor area was annotated in QuPath. Haralick features independent of the diaminobenzidine intensity were extracted from the isolated diaminobenzidine signal to quantify intratumor heterogeneity. Haralick features from both Ki-67 and CD45 were used as input for a principal component analysis. A linear support vector machine was fitted to the first 4 principal components for classification and validated with a leave-one-patient-out cross-validation method. Significant differences in individual Haralick features were found between cohesive and noncohesive tumors for CD45 (angular second motion: P =.03, inverse difference moment: P =.009, and entropy: P =.02) and between the larynx and hypopharynx tumors for both CD45 (angular second motion: P =.03, inverse difference moment: P =.007, and entropy: P =.005) and Ki-67 (correlation: P =.003). Therefore, these features were used for classification. The linear classifier resulted in a classification accuracy of 85% for site of origin and 81% for growth pattern. A leave-one-patient-out cross-validation resulted in an error rate of 0.27 and 0.35 for both classifiers, respectively. In conclusion, we show a method to quantify intratumor heterogeneity of immunohistochemistry biomarkers using Haralick features. This study also shows the feasibility of using these features to classify tumors by histologic characteristics. The classifiers created in this study are a proof of concept because more data are needed to create robust classifiers, but the method shows potential for automated tumor classification.

SF3B1 Mutations Are Associated with Resistance to Non-Genotoxic MDM2 Inhibition in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a genetically and clinically heterogeneous malignancy affecting older individuals. There are a number of current treatment options for CLL, including monoclonal antibodies, targeted drugs, chemotherapy, and different combinations of these. However, for those patients who are intrinsically treatment resistant, or relapse following initial responses, novel targeted therapies are still needed. Targeting the mouse double-minute-2 human homolog (MDM2), a primary negative regulator of p53, is an appealing therapeutic strategy for non-genotoxic reactivation of p53, since the TP53 gene is in its wild-type state at diagnosis in approximately 90% of patients. Mutated SF3B1 and TP53 are both associated with more aggressive disease, resistance to therapies and poorer overall survival for CLL. In this study, we performed a screen for SF3B1 and TP53 mutations and tested RG7388 (idasanutlin), a second-generation MDM2 inhibitor, in a cohort of CLL primary patient samples. SF3B1 mutations were detected in 24 of 195 cases (12.3%) and found associated with poor overall survival (hazard ratio [HR] 2.12, p = 0.032) and high CD38 expression (median CD38 (%) 32 vs. 5; p = 0.0087). The novel striking finding of this study was an independent link between SF3B1 mutational status and poor response to RG7388. Overall, SF3B1 mutations in CLL patient samples were associated with resistance to treatment with RG7388 ex vivo, and patients with the wild type for both SF3B1 and TP53 are more likely to benefit from treatment with MDM2 inhibitors.

Treatment Refractoriness in Chronic Lymphocytic Leukemia: Old and New Molecular Biomarkers

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. Despite its indolent clinical course, therapy refractoriness and disease progression still represent an unmet clinical need. Before the advent of pathway inhibitors, chemoimmunotherapy (CIT) was the commonest option for CLL treatment and is still widely used in areas with limited access to pathway inhibitors. Several biomarkers of refractoriness to CIT have been highlighted, including the unmutated status of immunoglobulin heavy chain variable genes and genetic lesions of TP53, BIRC3 and NOTCH1. In order to overcome resistance to CIT, targeted pathway inhibitors have become the standard of care for the treatment of CLL, with practice-changing results obtained through the inhibitors of Bruton tyrosine kinase (BTK) and BCL2. However, several acquired genetic lesions causing resistance to covalent and noncovalent BTK inhibitors have been reported, including point mutations of both BTK (e.g., C481S and L528W) and PLCG2 (e.g., R665W). Multiple mechanisms are involved in resistance to the BCL2 inhibitor venetoclax, including point mutations that impair drug binding, the upregulation of BCL2-related anti-apoptotic family members, and microenvironmental alterations. Recently, immune checkpoint inhibitors and CAR-T cells have been tested for CLL treatment, obtaining conflicting results. Potential refractoriness biomarkers to immunotherapy were identified, including abnormal levels of circulating IL-10 and IL-6 and the reduced presence of CD27+CD45RO- CD8+ T cells.

snoRNAs in hematopoiesis and blood malignancies: A comprehensive review

Small nucleolar RNAs (snoRNAs) are noncoding RNA molecules of highly variable size, usually ranging from 60 to 150 nucleotides. They are classified into H/ACA box snoRNAs, C/D box snoRNAs, and scaRNAs. Their functional profile includes biogenesis of ribosomes, processing of rRNAs, 2'-O-methylation and pseudouridylation of RNAs, alternative splicing and processing of mRNAs and the generation of small RNA molecules like miRNA. The snoRNAs have been observed to have an important role in hematopoiesis and malignant hematopoietic conditions including leukemia, lymphoma, and multiple myeloma. Blood malignancies arise in immune system cells or the bone marrow due to chromosome abnormalities. It has been estimated that annually over 1.25 million cases of blood cancer occur worldwide. The snoRNAs often show a differential expression profile in blood malignancies. Recent reports associate the abnormal expression of snoRNAs with the inhibition of apoptosis, uncontrolled cell proliferation, angiogenesis, and metastasis. This implies that targeting snoRNAs could be a potential way to treat hematologic malignancies. In this review, we describe the various functions of snoRNAs, their role in hematopoiesis, and the consequences of their dysregulation in blood malignancies. We also evaluate the potential of the dysregulated snoRNAs as biomarkers and therapeutic targets for blood malignancies.

Predicting anti-cancer drug combination responses with a temporal cell state network model

Cancer chemotherapy combines multiple drugs, but predicting the effects of drug combinations on cancer cell proliferation remains challenging, even for simple in vitro systems. We hypothesized that by combining knowledge of single drug dose responses and cell state transition network dynamics, we could predict how a population of cancer cells will respond to drug combinations. We tested this hypothesis here using three targeted inhibitors of different cell cycle states in two different cell lines in vitro. We formulated a Markov model to capture temporal cell state transitions between different cell cycle phases, with single drug data constraining how drug doses affect transition rates. This model was able to predict the landscape of all three different pairwise drug combinations across all dose ranges for both cell lines with no additional data. While further application to different cell lines, more drugs, additional cell state networks, and more complex co-culture or in vivo systems remain, this work demonstrates how currently available or attainable information could be sufficient for prediction of drug combination response for single cell lines in vitro.

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.

B Cell Chronic Lymphocytic Leukemia Development in Mice with Chronic Lung Exposure to Coccidioides Fungal Arthroconidia

Links between repeated microbial infections and B cell chronic lymphocytic leukemia (B-CLL) have been proposed but not tested directly. This study examines how prolonged exposure to a human fungal pathogen impacts B-CLL development in Eµ-hTCL1-transgenic mice. Monthly lung exposure to inactivated Coccidioides arthroconidia, agents of Valley fever, altered leukemia development in a species-specific manner, with Coccidioides posadasii hastening B-CLL diagnosis/progression in a fraction of mice and Coccidioides immitis delaying aggressive B-CLL development, despite fostering more rapid monoclonal B cell lymphocytosis. Overall survival did not differ significantly between control and C. posadasii-treated cohorts but was significantly extended in C. immitis-exposed mice. In vivo doubling time analyses of pooled B-CLL showed no difference in growth rates of early and late leukemias. However, within C. immitis-treated mice, B-CLL manifests longer doubling times, as compared with B-CLL in control or C. posadasii-treated mice, and/or evidence of clonal contraction over time. Through linear regression, positive relationships were noted between circulating levels of CD5+/B220low B cells and hematopoietic cells previously linked to B-CLL growth, albeit in a cohort-specific manner. Neutrophils were positively linked to accelerated growth in mice exposed to either Coccidioides species, but not in control mice. Conversely, only C. posadasii-exposed and control cohorts displayed positive links between CD5+/B220low B cell frequency and abundance of M2 anti-inflammatory monocytes and T cells. The current study provides evidence that chronic lung exposure to fungal arthroconidia affects B-CLL development in a manner dependent on fungal genotype. Correlative studies suggest that fungal species differences in the modulation of nonleukemic hematopoietic cells are involved.

bITH, a blood-based metric of intratumor heterogeneity, is associated with clinical response to immune checkpoint blockade in non-small cell lung cancer

BACKGROUND

Intratumor heterogeneity (ITH) has been associated with poor prognosis in advanced non-small cell cancer (NSCLC) patients receiving immune checkpoint blockade (ICB) therapies. However, there is currently no evidence supporting an ITH metric as a predictor of clinical benefit from ICB. The unique advantages of blood make it a promising material for ITH estimation and relevant applications. This study aims to develop and validate a blood-based ITH index for predicting ICB response.

METHODS

NSCLC patients from the OAK and POPLAR clinical trials were used as the training cohorts for algorithm development. Survival analyses with overall survival (OS) and progression-free survival (PFS) as endpoints were performed to assess clinical response. The predictive value of bITH was subsequently validated with an independent cohort of 42 NSCLC patients treated with PD-1 blockade.

FINDINGS

bITH was significantly associated with the differential OS and PFS elicited by atezolizumab vs. docetaxel in both univariable and multivariable analyses in the OAK patients, suggesting bITH as an independent predictor for response to ICB. Moreover, compared with blood tumor mutation burden (bTMB), bITH enabled greater OS segregation and comparable PFS segregation, and obtained a predictive role regardless of bTMB status. Moreover, the association between bITH and PFS was validated with an independent cohort.

INTERPRETATION

Patients with low blood-based ITH metric manifest significant OS and PFS benefit from immunotherapy versus chemotherapy. Future research is awaited to corroborate our findings and to enrich the clinical utility of ITH.

FUNDING

This study was supported by the National Natural Science Foundation of China (Nos. 81972718 and 81572321), the Natural Scientific Foundation of Zhejiang Province, China (No. LY19H160007), the Science and Technology Program for Health and Medicine in Zhejiang Province, China (No. 2021KY541), the Scientific Research Project, Science and Technology Department of Sichuan Province (No. 21YYJC1616), the Scientific Research Project, Sichuan Medical Association (No. S20002), Wu Jieping Medical Foundation (No. 320.6750), and 2018 Entrepreneurial Leading Talent of Guangzhou Huangpu District and Guangzhou Development District (No. 2022-L023).

Machines on Genes through the Computational Microscope

Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.

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

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

Precision diagnostics in chronic lymphocytic leukemia: Past, present and future

Genetic diagnostics of hematological malignancies has evolved dramatically over the years, from chromosomal banding analysis to next-generation sequencing, with a corresponding increased capacity to detect clinically relevant prognostic and predictive biomarkers. In diagnostics of patients with chronic lymphocytic leukemia (CLL), we currently apply fluorescence in situ hybridization (FISH)-based analysis to detect recurrent chromosomal aberrations (del(11q), del(13q), del(17p) and trisomy 12) as well as targeted sequencing (IGHV and TP53 mutational status) for risk-stratifying purposes. These analyses are performed before start of any line of treatment and assist in clinical decision-making including selection of targeted therapy (BTK and BCL2 inhibitors). Here, we present the current view on the genomic landscape of CLL, including an update on recent advances with potential for clinical translation. We discuss different state-of-the-art technologies that are applied to enable precision diagnostics in CLL and highlight important genomic markers with current prognostic and/or predictive impact as well as those of prospective clinical relevance. In the coming years, it will be important to develop more comprehensive genomic analyses that can capture all types of relevant genetic aberrations, but also to develop highly sensitive assays to detect minor mutations that affect therapy response or confer resistance to targeted therapies. Finally, we will bring up the potential of new technologies and multi-omics analysis to further subclassify the disease and facilitate implementation of precision medicine approaches in this still incurable disease.

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

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

Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity

Background: The impact of gene-sets on a spatial phenotype is not necessarily uniform across different locations of cancer tissue. This study introduces a computational platform, GWLCT, for combining gene set analysis with spatial data modeling to provide a new statistical test for location-specific association of phenotypes and molecular pathways in spatial single-cell RNA-seq data collected from an input tumor sample.

Methods: The main advantage of GWLCT consists of an analysis beyond global significance, allowing the association between the gene-set and the phenotype to vary across the tumor space. At each location, the most significant linear combination is found using a geographically weighted shrunken covariance matrix and kernel function. Whether a fixed or adaptive bandwidth is determined based on a cross-validation cross procedure. Our proposed method is compared to the global version of linear combination test (LCT), bulk and random-forest based gene-set enrichment analyses using data created by the Visium Spatial Gene Expression technique on an invasive breast cancer tissue sample, as well as 144 different simulation scenarios.

Results: In an illustrative example, the new geographically weighted linear combination test, GWLCT, identifies the cancer hallmark gene-sets that are significantly associated at each location with the five spatially continuous phenotypic contexts in the tumors defined by different well-known markers of cancer-associated fibroblasts. Scan statistics revealed clustering in the number of significant gene-sets. A spatial heatmap of combined significance over all selected gene-sets is also produced. Extensive simulation studies demonstrate that our proposed approach outperforms other methods in the considered scenarios, especially when the spatial association increases.

Conclusion: Our proposed approach considers the spatial covariance of gene expression to detect the most significant gene-sets affecting a continuous phenotype. It reveals spatially detailed information in tissue space and can thus play a key role in understanding the contextual heterogeneity of cancer cells.

Emerging Therapies in CLL in the Era of Precision Medicine

Over the past decade, the treatment landscape of CLL has vastly changed from the conventional FC (fludarabine and cyclophosphamide) and FCR (FC with rituximab) chemotherapies to targeted therapies, including inhibitors of Bruton tyrosine kinase (BTK) and phosphatidylinositol 3-kinase (PI3K) as well as inhibitors of BCL2. These treatment options dramatically improved clinical outcomes; however, not all patients respond well to these therapies, especially high-risk patients. Clinical trials of immune checkpoint inhibitors (PD-1, CTLA4) and chimeric antigen receptor T (CAR T) or NK (CAR NK) cell treatment have shown some efficacy; still, long-term outcomes and safety issues have yet to be determined. CLL remains an incurable disease. Thus, there are unmet needs to discover new molecular pathways with targeted or combination therapies to cure the disease. Large-scale genome-wide whole-exome and whole-genome sequencing studies have discovered genetic alterations associated with disease progression, refined the prognostic markers in CLL, identified mutations underlying drug resistance, and pointed out critical targets to treat the disease. More recently, transcriptome and proteome landscape characterization further stratified the disease and revealed novel therapeutic targets in CLL. In this review, we briefly summarize the past and present available single or combination therapies, focusing on potential emerging therapies to address the unmet clinical needs in CLL.

Estimating linkage disequilibrium and selection from allele frequency trajectories

Genetic sequences collected over time provide an exciting opportunity to study natural selection. In such studies, it is important to account for linkage disequilibrium to accurately measure selection and to distinguish between selection and other effects that can cause changes in allele frequencies, such as genetic hitchhiking or clonal interference. However, most high-throughput sequencing methods cannot directly measure linkage due to short-read lengths. Here we develop a simple method to estimate linkage disequilibrium from time-series allele frequencies. This reconstructed linkage information can then be combined with other inference methods to infer the fitness effects of individual mutations. Simulations show that our approach reliably outperforms inference that ignores linkage disequilibrium and, with sufficient sampling, performs similarly to inference using the true linkage information. We also introduce two regularization methods derived from random matrix theory that help to preserve its performance under limited sampling effects. Overall, our method enables the use of linkage-aware inference methods even for data sets where only allele frequency time series are available.

Causes of Clonal Hematopoiesis: a Review

PURPOSE OF REVIEW

Clonal hematopoiesis (CH) is an age-dependent process detectable using advanced sequencing technologies and is associated with multiple adverse health outcomes including cardiovascular disease and cancer. The purpose of this review is to summarize known causes of CH mutations and to identify key areas and considerations for future research on CH.

RECENT FINDINGS

Studies have identified multiple potential causes of CH mutations including smoking, cancer therapies, cardiometabolic disease, inflammation, and germline risk factors. Additionally, large-scale studies have facilitated the identification of gene-specific effects of CH mutation risk factors that may have unique downstream health implications. For example, cancer therapies and sources of environmental radiation appear to cause CH through their impact on DNA damage repair genes. There is a growing body of evidence defining risk factors for CH mutations. Standardization in the identification of CH mutations may have important implications for future research. Additional studies in underrepresented populations and their diverse environmental exposures are needed to facilitate broad public health impact of the study of CH mutations.

Genetics and epigenetics of CLL

Chronic lymphocytic leukemia (CLL) has a heterogeneous biological behavior, which is highly influenced by its immunogenetic, epigenetic, and genomic properties. The remarkably variable clinical course of the disease has been associated with genetic features such as chromosomal abnormalities, the presence of either high or low numbers of somatic hypermutations (SHM) in the variable region of the immunoglobulin heavy chain locus (IGHV), and somatic mutations of several specific driver genes. Next-generation sequencing (NGS) technologies have provided a comprehensive characterization of the genomic and epigenomic landscape in CLL, elucidating important underlying mechanisms of the disease's biology. The scope of this review is to summarize the most recent discoveries about novel genetic and epigenetic alterations, discussing their impact on clinical outcomes and response to currently available therapy.

Genetic Lesions in Russian CLL Patients with the Most Common Stereotyped Antigen Receptors

Chronic lymphocytic leukemia (CLL) is one of the most common B-cell malignancies in Western countries. IGHV mutational status is the most important prognostic factor for this disease. CLL is characterized by an extreme narrowing of the IGHV genes repertoire and the existence of subgroups of quasi-identical stereotyped antigenic receptors (SAR). Some of these subgroups have already been identified as independent prognostic factors for CLL. Here, we report the frequencies of TP53, NOTCH1, and SF3B1 gene mutations and chromosomal aberrations assessed by NGS and FISH in 152 CLL patients with the most common SAR in Russia. We noted these lesions to be much more common in patients with certain SAR than average in CLL. The profile of these aberrations differs between the subgroups of SAR, despite the similarity of their structure. For most of these subgroups mutations prevailed in a single gene, except for CLL#5 with all three genes affected by mutations. It should be noted that our data concerning the mutation frequency in some SAR groups differ from that obtained previously, which could be due to the population differences between patient cohorts. The research in this area should be important for better understanding the pathogenesis of CLL and therapy optimization.

Rare Germline ATM Variants Influence the Development of Chronic Lymphocytic Leukemia

PURPOSE

Germline missense variants of unknown significance in cancer-related genes are increasingly being identified with the expanding use of next-generation sequencing. The ataxia telangiectasia-mutated (ATM) gene on chromosome 11 has more than 1,000 germline missense variants of unknown significance and is a tumor suppressor. We aimed to determine if rare germline ATM variants are more frequent in chronic lymphocytic leukemia (CLL) compared with other hematologic malignancies and if they influence the clinical characteristics of CLL.

METHODS

We identified 3,128 patients (including 825 patients with CLL) in our hematologic malignancy clinic who had received clinical-grade sequencing of the entire coding region of ATM. We ascertained the comparative frequencies of germline ATM variants in categories of hematologic neoplasms, and, in patients with CLL, we determined whether these variants affected CLL-associated characteristics such as somatic 11q deletion.

RESULTS

Rare germline ATM variants are present in 24% of patients with CLL, significantly greater than that in patients with other lymphoid malignancies (16% prevalence), myeloid disease (15%), or no hematologic neoplasm (14%). Patients with CLL with germline ATM variants are younger at diagnosis and twice as likely to have 11q deletion. The ATM variant p.L2307F is present in 3% of patients with CLL, is associated with a three-fold increase in rates of somatic 11q deletion, and is a hypomorph in cell-based assays.

CONCLUSION

Germline ATM variants cluster within CLL and affect the phenotype of CLL that develops, implying that some of these variants (such as ATM p.L2307F) have functional significance and should not be ignored. Further studies are needed to determine whether these variants affect the response to therapy or account for some of the inherited risk of CLL.

Genetic and Clinical Characteristics of Korean Chronic Lymphocytic Leukemia Patients with High Frequencies of MYD88 Mutations

Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in Western countries. However, CLL is relatively rare in Asia; its genetic features are rarely studied. Here, we aimed to genetically characterize Korean CLL patients and to elucidate the genetic and clinical associations based on data obtained from 113 patients at a single Korean institute. We used next-generation sequencing to explore the multi-gene mutational data and immunoglobulin heavy chain variable gene clonality with somatic hypermutation (SHM). MYD88 (28.3%), including L265P (11.5%) and V217F (13.3%), was the most frequently mutated gene, followed by KMT2D (6.2%), NOTCH1 (5.3%), SF3B1 (5.3%), and TP53 (4.4%). MYD88-mutated CLL was characterized by SHM and atypical immunophenotype with fewer cytogenetic abnormalities. The 5-year time to treatment (TTT) of the overall cohort was 49.8% ± 8.2% (mean ± standard deviation) and the 5-year overall survival was 86.2% ± 5.8%. Patients with SHM, isolated del(13q), TP53-wild type, and NOTCH1-wild type showed better results than those without these conditions. In the subgroup analyses, patients with SHM and L265P presented shorter TTT than patients with SHM but not L265P. In contrast, V217F was associated with a higher SHM percentage and showed a favorable prognosis. Our study revealed the distinct characteristics of Korean CLL patients with high frequencies of MYD88 mutations and their clinical relevance.

The end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia

Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.

Targeting Pim kinases in hematological cancers: molecular and clinical review

Decades of research has recognized a solid role for Pim kinases in lymphoproliferative disorders. Often up-regulated following JAK/STAT and tyrosine kinase receptor signaling, Pim kinases regulate cell proliferation, survival, metabolism, cellular trafficking and signaling. Targeting Pim kinases represents an interesting approach since knock-down of Pim kinases leads to non-fatal phenotypes in vivo suggesting clinical inhibition of Pim may have less side effects. In addition, the ATP binding site offers unique characteristics that can be used for the development of small inhibitors targeting one or all Pim isoforms. This review takes a closer look at Pim kinase expression and involvement in hematopoietic cancers. Current and past clinical trials and in vitro characterization of Pim kinase inhibitors are examined and future directions are discussed. Current studies suggest that Pim kinase inhibition may be most valuable when accompanied by multi-drug targeting therapy.

Integrative Analysis of Germline Rare Variants in Clear and Non-Clear Cell Renal Cell Carcinoma

IMPORTANCE

RCC encompasses a set of histologically distinct cancers with a high estimated genetic heritability, of which only a portion is currently explained. Previous rare germline variant studies in RCC have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification that may significantly impact the interpretation and discovery of certain candidate risk genes.

OBJECTIVE

To evaluate the enrichment of germline PVs in established cancer-predisposing genes (CPGs) in clear cell and non-clear cell RCC patients compared to cancer-free controls using approaches that account for population stratification and to identify unconventional types of germline RCC risk variants that confer an increased risk of developing RCC.

DESIGN SETTING AND PARTICIPANTS

In 1,436 unselected RCC patients with sufficient data quality, we systematically identified rare germline PVs, cryptic splice variants, and copy number variants (CNVs). From this unselected cohort, 1,356 patients were ancestry-matched with 16,512 cancer-free controls, and gene-level enrichment of rare germline PVs were assessed in 143 CPGs, followed by an investigation of somatic events in matching tumor samples.

MAIN OUTCOMES AND MEASURES

Gene-level burden of rare germline PVs, identification of secondary somatic events accompanying the germline PVs, and characterization of less-explored types of rare germline PVs in RCC patients.

RESULTS

In clear cell RCC (n = 976 patients), patients exhibited significantly higher prevalence of PVs in VHL compared to controls (OR: 39.1, 95% CI: 7.01-218.07, p-value:4.95e-05, q-value:0.00584). In non-clear cell RCC (n = 380 patients), patients carried enriched burden of PVs in FH (OR: 77.9, 95% CI: 18.68-324.97, p-value:1.55e-08, q-value: 1.83e-06) and MET (OR: 1.98e11, 95% CI: 0-inf, p-value: 2.07e-05, q-value: 3.50e-07). In a CHEK2-focused analysis with European cases and controls, clear cell RCC patients (n=906 European patients) harbored nominal enrichment of the previously reported low-penetrance CHEK2 variants, p.Ile157Thr (OR:1.84, 95% CI: 1.00-3.36, p-value:0.049) and p.Ser428Phe (OR:5.20, 95% CI: 1.00-26.40, p-value:0.045) while non-clear cell RCC patients (n=295 European patients) exhibited nominal enrichment of CHEK2 LOF germline PVs (OR: 3.51, 95% CI: 1.10-11.10, p-value: 0.033). RCC patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset compared to patients without any germline PVs in CPGs (Mean: 46.0 vs 60.2 years old, Tukey adjusted p-value < 0.0001), and more than half had secondary somatic events affecting the same gene (n=10/15, 66.7%, 95% CI: 38.7-87.0%). Conversely, patients with rare germline PVs in CHEK2 exhibited a similar age of disease onset to patients without any identified germline PVs in CPGs (Mean: 60.1 vs 60.2 years old, Tukey adjusted p-value: 0.99), and only 30.4% of the patients carried secondary somatic events in CHEK2 (n=7/23, 95% CI: 14.1-53.0%). Finally, rare pathogenic germline cryptic splice variants underexplored in RCC were identified in SDHA and TSC1, and rare pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL.

CONCLUSIONS AND RELEVANCE

This systematic analysis supports the existing link between several RCC risk genes and elevated RCC risk manifesting in earlier age of RCC onset. Our analysis calls for caution when assessing the role of germline PVs in CHEK2 due to the burden of founder variants with varying population frequency in different ancestry groups. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants, such as cryptic splice variants and CNVs.

DeteX: A highly accurate software for detecting SNV and InDel in single and paired NGS data in cancer research

Background: Genetic testing is becoming more and more accepted in the auxiliary diagnosis and treatment of tumors. Due to the different performance of the existing bioinformatics software and the different analysis results, the needs of clinical diagnosis and treatment cannot be met. To this end, we combined Bayesian classification model (BC) and fisher exact test (FET), and develop an efficient software DeteX to detect SNV and InDel mutations. It can detect the somatic mutations in tumor-normal paired samples as well as mutations in a single sample. Methods: Combination of Bayesian classification model (BC) and fisher exact test (FET). Results: We detected SNVs and InDels in 11 TCGA glioma samples, 28 clinically targeted capture samples and 2 NCCL-EQA standard samples with DeteX, VarDict, Mutect, VarScan and GatkSNV. The results show that, among the three groups of samples, DeteX has higher sensitivity and precision whether it detects SNVs or InDels than other callers and the F1 value of DeteX is the highest. Especially in the detection of substitution and complex mutations, only DeteX can accurately detect these two kinds of mutations. In terms of single-sample mutation detection, DeteX is much more sensitive than the HaplotypeCaller program in Gatk. In addition, although DeteX has higher mutation detection capabilities, its running time is only .609 of VarDict, which is .704 and .343 longer than VarScan and MuTect, respectively. Conclusion: In this study, we developed DeteX to detect SNV and InDel mutations in single and paired samples. DeteX has high sensitivity and precision especially in the detection of substitution and complex mutations. In summary, DeteX from NGS data is a good SNV and InDel caller.

Grave-to-cradle: human embryonic lineage tracing from the postmortem body

Curiosity concerning the process of human creation has been around for a long time. Relevant questions seemed to be resolved with the knowledge of how cells divide after fertilization obtained through in vitro fertilization experiments. However, we still do not know how human life is created at the cellular level. Recently, the value of cadavers as a resource from which to obtain "normal" cells and tissues has been established, and human research using postmortem bodies has attracted growing scientific attention. As the human genome can be analyzed at the level of nucleotides through whole-genome sequencing, individual cells in a postmortem body can be traced back to determine what developmental processes have transpired from fertilization. These retrospective lineage tracing studies have answered several unsolved questions on how humans are created. This review covers the methodologies utilized in lineage tracing research in a historical context and the conceptual basis for reconstructing the division history of cells in a retrospective manner using postzygotic somatic variants in postmortem tissue. We further highlight answers that postmortem research could potentially address and discuss issues that wait to be solved in the future.

Cancer Chemoresistance; Recent Challenges and Future Considerations

Cancer remains one of the serious health hazards and major causes of human mortality across the world. Despite the development of many typical antineoplastic drugs and introduction of novel targeted agents, chemoresistance constitutes a major challenge in the effective therapeutic management of cancer. Drug inactivation, efflux of anticancer agents, modification of target sites, enhanced repair of DNA damage, apoptosis failure and induction of epithelial-mesenchymal transition are the principal mechanisms of cancer chemoresistance. Moreover, epigenetics, cell signaling, tumor heterogeneity, stem cells, microRNAs, endoplasmic reticulum, tumor microenvironment and exosomes have also been implicated in the multifaceted phenomenon of anticancer drug resistance. The tendency of resistance is either intrinsically possessed or subsequently acquired by cancerous cells. From clinical oncology standpoint, therapeutic failure and tumor progression are the most probable consequences of cancer chemoresistance. Combination therapy can help to overcome the issue of drug resistance, and therefore, the development of such treatment regimens is recommended for counteracting the emergence and dissemination of cancer chemoresistance. This chapter outlines the current knowledge on underlying mechanisms, contributory biological factors and likely consequences of cancer chemoresistance. Besides, prognostic biomarkers, diagnostic methods and potential approaches to overcome the emergence of antineoplastic drug resistance have also been described.

The prognostic impact of subclonal IDH1 mutation in grade 2-4 astrocytomas

Background

Isocitrate dehydrogenase (IDH) mutations are thought to represent an early oncogenic event in glioma evolution, found with high penetrance across tumor cells; however, in rare cases, IDH mutation may exist only in a small subset of the total tumor cells (subclonal IDH mutation).

Methods

We present 2 institutional cases with subclonal IDH1 R132H mutation. In addition, 2 large publicly available cohorts of IDH-mutant astrocytomas were mined for cases harboring subclonal IDH mutations (defined as tumor cell fraction with IDH mutation ≤0.67) and the clinical and molecular features of these subclonal cases were compared to clonal IDH-mutant astrocytomas.

Results

Immunohistochemistry (IHC) performed on 2 institutional World Health Organization grade 4 IDH-mutant astrocytomas revealed only a minority of tumor cells in each case with IDH1 R132H mutant protein, and next-generation sequencing (NGS) revealed remarkably low IDH1 variant allele frequencies compared to other pathogenic mutations, including TP53 and/or ATRX. DNA methylation classified the first tumor as high-grade IDH-mutant astrocytoma with high confidence (0.98 scores). In the publicly available datasets, subclonal IDH mutation was present in 3.9% of IDH-mutant astrocytomas (18/466 tumors). Compared to clonal IDH-mutant astrocytomas (n = 156), subclonal cases demonstrated worse overall survival in grades 3 (P = .0106) and 4 (P = .0184).

Conclusions

While rare, subclonal IDH1 mutations are present in a subset of IDH-mutant astrocytomas of all grades, which may lead to a mismatch between IHC results and genetic/epigenetic classification. These findings suggest a possible prognostic role of IDH mutation subclonality, and highlight the potential clinical utility of quantitative IDH1 mutation evaluation by IHC and NGS.

Clonal transcriptomics identifies mechanisms of chemoresistance and empowers rational design of combination therapies

Tumour heterogeneity is thought to be a major barrier to successful cancer treatment due to the presence of drug resistant clonal lineages. However, identifying the characteristics of such lineages that underpin resistance to therapy has remained challenging. Here, we utilise clonal transcriptomics with WILD-seq; Wholistic Interrogation of Lineage Dynamics by sequencing, in mouse models of triple-negative breast cancer (TNBC) to understand response and resistance to therapy, including BET bromodomain inhibition and taxane-based chemotherapy. These analyses revealed oxidative stress protection by NRF2 as a major mechanism of taxane resistance and led to the discovery that our tumour models are collaterally sensitive to asparagine deprivation therapy using the clinical stage drug L-asparaginase after frontline treatment with docetaxel. In summary, clonal transcriptomics with WILD-seq identifies mechanisms of resistance to chemotherapy that are also operative in patients and pin points asparagine bioavailability as a druggable vulnerability of taxane-resistant lineages.

Integrated analysis of racial disparities in genomic architecture identifies a trans-ancestry prognostic subtype in bladder cancer

The incidence of bladder cancer and patient survival vary greatly among different populations, but the influence of the associated molecular features and evolutionary processes on its clinical treatment and prognostication remains unknown. Here, we analyze the genomic architectures of 505 bladder cancer patients from Asian/Black/White populations. We identify a previously unknown association between AHNAK mutations and activity of the APOBEC-a mutational signature, the activity of which varied substantially across populations. All significantly mutated genes but only half of arm-level somatic copy number alterations (SCNAs) are enriched with clonal events, indicating large-scale SCNAs as rich sources of bladder cancer clonal diversities. The prevalence of TP53 and ATM clonal mutations as well as the associated burden of SCNAs is significantly higher in Whites/Blacks than in Asians. We identify a trans-ancestry prognostic subtype of bladder cancer characterized by enrichment of non-muscle-invasive patients and muscle-invasive patients with good prognosis, increased CREBBP/FGFR3/HRAS/NFE2L2 mutations, decreased intra-tumor heterogeneity and genome instability, and an activated tumor microenvironment.

Clonal relationship and alcohol consumption-associated mutational signature in synchronous hypopharyngeal tumours and oesophageal squamous cell carcinoma

BACKGROUND

The patients with dual oesophageal squamous cell carcinoma (ESCC) and hypopharyngeal cancer (HPC) have poor prognosis; their underlying genetic pathogenesis is unclear. We hypothesise that development of synchronous ESCC/HPC depends on multicentricity or independent origin, rather than multifocality due to local or lateral spreading.

METHOD

Multiple region whole-exome sequencing (M-WES) and clonality analysis were used to assess clonal relationship and spatial inter- or intra-tumour heterogeneity (ITH) in 62 tumour regions from eight dual ESCC/HPC and ten ESCC patients.

RESULTS

All synchronous ESCC/HPC patients had COSMIC 16 mutation signatures, compared to only 40% ESCC in the current study (p = 0.013) and public data set (n = 165, p = 0.003). This alcohol consumption-related mutation signature 16, commonly involved in multiple alcohol-related cancers, was significantly associated with drinking and alcohol metabolism-related ADH1B rs1229984. The mutational landscape and copy number profiles were completely distinct between the two primary tumours; clonality analysis further suggested the two primary tumours shared no or only one clone accompanying independent subclone evolution. M-WES strategy demonstrated higher sensitivity and accuracy for detection of mutational prevalence and the late branch mutations among different regions in the ESCC tumours, compared to traditional sequencing analysis based on single biopsy strategy. Patients with high ITH assessed by cancer cell fraction analysis after M-WES were significantly associated with both relapse and survival.

CONCLUSIONS

Our hypothesis-generating M-WES ITH assessment data have implications for prognostication. Collectively, our findings support multicentric independent clonal evolution, the field cancerisation theory, and suggest novel insights implicating an aetiologic role of alcohol metabolism in dual ESCC/HPC carcinogenesis.

Tissue and liquid biopsy profiling reveal convergent tumor evolution and therapy evasion in breast cancer

Pathological and genomic profiling have transformed breast cancer care by matching patients to targeted treatments. However, tumors evolve and evade therapeutic interventions often through the acquisition of genomic mutations. Here we examine patients profiled with tissue (TBx) and liquid biopsy (LBx) as part of routine clinical care, to characterize the tumor evolutionary landscape and identify potential vulnerabilities in the relapsed setting. Real-world evidence demonstrates that LBx is utilized later in care and identifies associations with intervening therapy. While driver events are frequently shared, acquired LBx alterations are detected in a majority of patients, with the highest frequency in ER+ disease and in patients with longer biopsy intervals. Acquired mutations are often polyclonal and present at lower allelic fractions, suggesting multi-clonal convergent evolution. In addition to well-characterized resistance mutations (e.g., ESR1, NF1, RB1, ERBB2), we observe a diversity of rarer but potentially targetable mutations (e.g., PIK3CA, HRAS/NRAS/KRAS, FGFR1/2/3, BRAF) and fusions (e.g., FGFR1/2, ERBB2, RET), as well as BRCA1/2 reversions through a variety of mechanisms, including splice alterations and structural deletions. This study provides insights on treatment and selection-driven tumor evolution and identifies potential combinatorial treatment options in advanced breast cancer.

The spectrum of subclonal TP53 mutations in chronic lymphocytic leukemia: A next generation sequencing retrospective study

Chronic lymphocytic leukemia (CLL) is a hematological disorder with complex clinical and biological behavior. TP53 mutational status and cytogenetic assessment of the deletion of the corresponding locus (17p13.1) are considered the most relevant biomarkers associated with pharmaco-predictive response, chemo-refractoriness, and worse prognosis in CLL patients. The implementation of Next Generation Sequencing (NGS) methodologies in the clinical laboratory allows for comprehensively analyzing the TP53 gene and detecting mutations with allele frequencies ≤10%, that is, "subclonal mutations". We retrospectively studied TP53 gene mutational status by NGS in 220 samples from 171 CLL patients. TP53 mutations were found in 60/220 (27.3%) samples and 47/171 (27.5%) patients. Interestingly, subclonal mutations could be detected in 31/60 samples (51.7%) corresponding to 25 patients (25/47, 53.2%). We identified 44 distinct subclonal TP53 mutations clustered in the central DNA-binding domain of p53 protein (exons 5-8, codons 133-286). Missense mutations were predominant (>80%), whereas indels, nonsense, and splice site variants were less represented. All subclonal TP53 variants but one [p.(Pro191fs)] were already described in NCI and/or Seshat databases as "damaging" and/or "probably damaging" mutations (38/44, 86% and 6/44, 14%, respectively). Longitudinal samples were available for 37 patients. Almost half of them displayed at least one TP53 mutant subclone, which could be alone (4/16, 25%) or concomitant with other TP53 mutant clonal ones (12/16, 75%); different patterns of mutational dynamics overtimes were documented. In conclusion, utilization of NGS in our "real-life" cohort of CLL patients demonstrated an elevated frequency of subclonal TP53 mutations. This finding indicates the need for precisely identifying these mutations during disease since the clones carrying them may become predominant and be responsible for therapy failures.

Revealing the functions of clonal driver gene mutations in patients based on evolutionary dependencies

The clonal mutations in driver genes enable cells to gradually acquire growth advantage in tumor development. Therefore, revealing the functions of clonal driver gene mutations is important. Here, we proposed the method FCMP that considered evolutionary dependencies to analyze the functions of clonal driver gene mutations in a single patient. Applying our method to five cancer types from The Cancer Genome Atlas, we identified specific functions and common functions of clonal driver gene mutations. We found that the clonal driver gene mutations in the same patient played multiple functions. We also found that clonal mutations in the same driver gene performed different functions in different patients. These findings suggested that the clonal driver gene mutations showed strong tumor heterogeneity. In the pan-cancer analysis, the immune-related functions for clonal driver gene mutations were shared by multiple cancer types. In addition, clonal mutations in some driver genes predicted the survival of patients in cancers.

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.

Genomic profiling for clinical decision making in lymphoid neoplasms

With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

Maximum Somatic Allele Frequency-Adjusted Blood-Based Tumor Mutational Burden Predicts the Efficacy of Immune Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer

INTRODUCTION

Recent studies exhibited the unstable prediction ability of blood-based tumor mutational burden (bTMB) when predicting the response of immune checkpoint inhibitors (ICIs) therapy in patients with non-small cell lung cancer (NSCLC). Circulating tumor DNA (ctDNA) abundance, usually represented by maximum somatic allele frequency (MSAF), was one possible confounding factor influencing bTMB ability in ICIs response prediction.

METHODS

MSAF-adjusted bTMB (Ma-bTMB) was established and validated in patients with advanced NSCLC among Geneplus Cancer Genome Database (GCGD, n = 1679), Zhuo (n = 35), Wang (n = 45), POPLAR (NCT01903993, n = 211) and OAK (NCT02008227, n = 642) cohorts.

RESULTS

MSAF demonstrated a modest positive correlation with bTMB and a negative one with survival benefit. Improved survival outcomes of ICIs therapy have been observed among patients with high-Ma-bTMB compared to those with low-Ma-bTMB in Zhuo and Wang cohorts. In addition, compared to low-Ma-bTMB, high-Ma-bTMB was associated with more positive clinical benefits from ICIs therapy than chemotherapy both in POPLAR and OAK cohorts. Further exploration suggested that Ma-bTMB could precisely identify more potential ICIs beneficiaries compared to bTMB and LAF-bTMB, complementary to PD-L1 expression.

CONCLUSIONS

We developed Ma-bTMB, a convenient, readily available, non-invasive predictive biomarker effectively differentiates beneficiaries of ICIs therapy in advanced NSCLC, warranting future clinical trials.

Development and clinical validation of a necroptosis-related gene signature for prediction of prognosis and tumor immunity in lung adenocarcinoma

Necroptosis is a new programmed formation of necrotizing cell death, which plays important role in tumor biological regulation, including tumorigenesis and immunity. In this study, we aimed to establish and validate a prediction model based on necroptosis-related genes (NRGs) for lung adenocarcinoma (LUAD) prognosis and tumor immunity. The training set consisted of samples from The Cancer Genome Atlas (TCGA) dataset (n = 334), and the validation sets consisted of samples from the Gene Expression Omnibus (GEO) (n = 439) and clinical (n = 20) datasets. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that 28 necroptosis-related differentially expressed genes (DEGs) were enriched in cell death and immune regulation. RT-qPCR and western blot results showed the low expression of necroptosis markers in LUAD cells. A prognostic gene signature based on 6 NRGs (PYGB, IL1A, IFNAR2, BIRC3, H2AFY2, and H2AFX) was constructed and the risk score was calculated. Multivariate Cox regression analysis showed that the risk score was an independent risk factor [hazard ratio (HR) = 1.220, 95% confidence interval (CI): 1.154-1.290, P<0.001]. In the TCGA cohort, a high-risk score was associated with poor prognosis, weak immune infiltration, and low expression at immune checkpoints, which was validated in the GEO and clinical cohorts. Our findings showed that the patients in the low-risk group had a better progression-free survival (PFS) [not reached vs. 8.5 months, HR = 0.18, 95% CI: 0.04-0.72, P<0.001] than those in the high-risk score group. Immunotherapy tolerance was found to be correlated with the high-risk score, and the risk score combined with PD-L1 (AUC = 0.808, 95% CI: 0.613-1.000) could better predict the immunotherapy response of LUAD. A nomogram was shown to have a strong ability to predict the individual survival rate of patients with LUAD in the TCGA and GSE68465 cohorts. We constructed and validated a potential prognostic signature consisting of 6 NRGs to predict the prognosis and tumor immunity of LUAD, which may be helpful to guide the individualized immunotherapy of LUAD.

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.

Targeting the DNA damage response and repair in cancer through nucleotide metabolism

The exploitation of the DNA damage response and DNA repair proficiency of cancer cells is an important anticancer strategy. The replication and repair of DNA are dependent upon the supply of deoxynucleoside triphosphate (dNTP) building blocks, which are produced and maintained by nucleotide metabolic pathways. Enzymes within these pathways can be promising targets to selectively induce toxic DNA lesions in cancer cells. These same pathways also activate antimetabolites, an important group of chemotherapies that disrupt both nucleotide and DNA metabolism to induce DNA damage in cancer cells. Thus, dNTP metabolic enzymes can also be targeted to refine the use of these chemotherapeutics, many of which remain standard of care in common cancers. In this review article, we will discuss both these approaches exemplified by the enzymes MTH1, MTHFD2 and SAMHD1. © 2022 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

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.

Viral transduction of primary human lymphoma B cells reveals mechanisms of NOTCH-mediated immune escape

Hotspot mutations in the PEST-domain of NOTCH1 and NOTCH2 are recurrently identified in B cell malignancies. To address how NOTCH-mutations contribute to a dismal prognosis, we have generated isogenic primary human tumor cells from patients with Chronic Lymphocytic Leukemia (CLL) and Mantle Cell Lymphoma (MCL), differing only in their expression of the intracellular domain (ICD) of NOTCH1 or NOTCH2. Our data demonstrate that both NOTCH-paralogs facilitate immune-escape of malignant B cells by up-regulating PD-L1, partly dependent on autocrine interferon-γ signaling. In addition, NOTCH-activation causes silencing of the entire HLA-class II locus via epigenetic regulation of the transcriptional co-activator CIITA. Notably, while NOTCH1 and NOTCH2 govern similar transcriptional programs, disease-specific differences in their expression levels can favor paralog-specific selection. Importantly, NOTCH-ICD also strongly down-regulates the expression of CD19, possibly limiting the effectiveness of immune-therapies. These NOTCH-mediated immune escape mechanisms are associated with the expansion of exhausted CD8+ T cells in vivo.