Evolution and impact of subclonal mutations in chronic lymphocytic leukemia

A high-throughput splicing assay identifies new classes of inhibitors of human and yeast spliceosomes

The spliceosome is the macromolecular machine responsible for pre-mRNA splicing, an essential step in eukaryotic gene expression. During splicing, myriad subunits join and leave the spliceosome as it works on the pre-mRNA substrate. Strikingly, there are very few small molecules known to interact with the spliceosome. Splicing inhibitors are needed to capture transient spliceosome conformations and probe important functional components. Such compounds may also have chemotherapeutic applications, as links between splicing and cancer are increasingly uncovered. To identify new splicing inhibitors, we developed a high-throughput assay for in vitro splicing using a reverse transcription followed by quantitative PCR readout. In a pilot screen of 3080 compounds, we identified three small molecules that inhibit splicing in HeLa extract by interfering with different stages of human spliceosome assembly. Two of the compounds similarly affect spliceosomes in yeast extracts, suggesting selective targeting of conserved components. By examining related molecules, we identified chemical features required for the activity of two of the splicing inhibitors. In addition to verifying our assay procedure and paving the way to larger screens, these studies establish new compounds as chemical probes for investigating the splicing machinery.

SF3B1 mutations in chronic lymphocytic leukemia

SF3B1 is a critical component of the splicing machinery, which catalyzes the removal of introns from precursor messenger RNA (mRNA). Next-generation sequencing studies have identified mutations in SF3B1 in chronic lymphocytic leukemia (CLL) at high frequency. In CLL, SF3B1 mutation is associated with more aggressive disease and shorter survival, and recent studies suggest that it can be incorporated into prognostic schema to improve the prediction of disease progression. Mutations in SF3B1 are predominantly subclonal genetic events in CLL, and hence are likely later events in the progression of CLL. Evidence of altered pre-mRNA splicing has been detected in CLL cases with SF3B1 mutations. Although the causative link between SF3B1 mutation and CLL pathogenesis remains unclear, several lines of evidence suggest SF3B1 mutation might be linked to genomic stability and epigenetic modification.

Clinical application of targeted and genome-wide technologies: can we predict treatment responses in chronic lymphocytic leukemia?

Chronic lymphocytic leukemia (CLL) is low-grade lymphoma of mature B cells and it is considered to be the most common type of hematological malignancy in the western world. CLL is characterized by a chronically relapsing course and clinical and biological heterogeneity. Many patients do not require any treatment for years. Although important progress has been made in the treatment of CLL, none of the conventional treatment options are curative. Recurrent chromosomal abnormalities have been identified and are associated with prognosis and pathogenesis of the disease. More recently, unbiased genome-wide technologies have identified multiple additional recurrent aberrations. The precise predictive value of these has not been established, but it is likely that the genetic heterogeneity observed at least partly reflects the clinical variability. The present article reviews our current knowledge of predictive markers in CLL using whole-genome technologies.

Chronic lymphocytic leukemia: molecular heterogeneity revealed by high-throughput genomics

Chronic lymphocytic leukemia (CLL) has been consistently at the forefront of genetic research owing to its prevalence and the accessibility of sample material. Recently, genome-wide technologies have been intensively applied to CLL genetics, with remarkable progress. Single nucleotide polymorphism arrays have identified recurring chromosomal aberrations, thereby focusing functional studies on discrete genomic lesions and leading to the first implication of somatic microRNA disruption in cancer. Next-generation sequencing (NGS) has further transformed our understanding of CLL by identifying novel recurrently mutated putative drivers, including the unexpected discovery of somatic mutations affecting spliceosome function. NGS has further enabled in-depth examination of the transcriptional and epigenetic changes in CLL that accompany genetic lesions, and has shed light on how different driver events appear at different stages of disease progression and clonally evolve with relapsed disease. In addition to providing important insights into disease biology, these discoveries have significant translational potential. They enhance prognosis by highlighting specific lesions associated with poor clinical outcomes (for example, driver events such as mutations in the splicing factor subunit gene SF3B1) or with increased clonal heterogeneity (for example, the presence of subclonal driver mutations). Here, we review new genomic discoveries in CLL and discuss their possible implications in the era of precision medicine.

Lessons from the cancer genome

Systematic studies of the cancer genome have exploded in recent years. These studies have revealed scores of new cancer genes, including many in processes not previously known to be causal targets in cancer. The genes affect cell signaling, chromatin, and epigenomic regulation; RNA splicing; protein homeostasis; metabolism; and lineage maturation. Still, cancer genomics is in its infancy. Much work remains to complete the mutational catalog in primary tumors and across the natural history of cancer, to connect recurrent genomic alterations to altered pathways and acquired cellular vulnerabilities, and to use this information to guide the development and application of therapies.

The genomic landscape of chronic lymphocytic leukemia: clinical implications

A precise understanding of the genomic and epigenomic features of chronic lymphocytic leukemia (CLL) may benefit the study of the disease's staging and treatment. While recent reports have shed some light on these aspects, several challenges need to be addressed before translating this research into clinical practice. Thus, even the best candidate driver genes display low mutational rates compared to other tumors. This means that a large percentage of cases do not display clear tumor-driving point mutations, or show candidate driving point mutations with no obvious biochemical relationship to the more frequently mutated genes. This genomic landscape probably reflects either an unknown underlying biochemical mechanism playing a key role in CLL or multiple biochemical pathways independently driving the development of this tumor. The elucidation of either scenario will have important consequences on the clinical management of CLL. Herein, we review the recent advances in the definition of the genomic landscape of CLL and the ongoing research to characterize the underlying biochemical events that drive this disease.

Clonal evolution, genomic drivers, and effects of therapy in chronic lymphocytic leukemia

PURPOSE

The identification of gene mutations and structural genomic aberrations that are critically involved in chronic lymphocytic leukemia (CLL) pathogenesis is still evolving. One may postulate that genomic driver lesions with effects on CLL cell proliferation, apoptosis thresholds, or chemotherapy resistance should increase in frequency over time when measured sequentially in a large CLL cohort.

EXPERIMENTAL DESIGN

We sequentially sampled a large well-characterized CLL cohort at a mean of 4 years between samplings and measured acquired copy number aberrations (aCNA) and LOH using single-nucleotide polymorphism (SNP) 6.0 array profiling and the mutational state of TP53, NOTCH1, and SF3B1 using Sanger sequencing. The paired analysis included 156 patients, of whom 114 remained untreated and 42 received intercurrent therapies, predominantly potent chemoimmunotherapy, during the sampling interval.

RESULTS

We identify a strong effect of intercurrent therapies on the frequency of acquisition of aCNAs in CLL. Importantly, the spectrum of acquired genomic changes was largely similar in patients who did or did not receive intercurrent therapies; therefore, various genomic changes that become part of the dominant clones are often already present in CLL cell populations before therapy. Furthermore, we provide evidence that therapy of CLL with preexisting TP53 mutations results in outgrowth of genomically very complex clones, which dominate at relapse.

CONCLUSIONS

Using complementary technologies directed at the detection of genomic events that are present in substantial proportions of the clinically relevant CLL disease bulk, we capture aspects of genomic evolution in CLL over time, including increases in the frequency of genomic complexity, specific recurrent aCNAs, and TP53 mutations.

ATM mutations uniformly lead to ATM dysfunction in chronic lymphocytic leukemia: application of functional test using doxorubicin

ATM abnormalities are frequent in chronic lymphocytic leukemia and represent an important prognostic factor. Sole 11q deletion does not result in ATM inactivation by contrast to biallelic defects involving mutations. Therefore, the analysis of ATM mutations and their functional impact is crucial. In this study, we analyzed ATM mutations in predominantly high-risk patients using: i) resequencing microarray and direct sequencing; ii) Western blot for total ATM level; iii) functional test based on p21 gene induction after parallel treatment of leukemic cells with fludarabine and doxorubicin. ATM dysfunction leads to impaired p21 induction after doxorubicin exposure. We detected ATM mutation in 16% (22 of 140) of patients, and all mutated samples manifested demonstrable ATM defect (impaired p21 upregulation after doxorubicin and/or null protein level). Loss of ATM function in mutated samples was also evidenced through defective p53 pathway activation after ionizing radiation exposure. ATM mutation frequency was 34% in patients with 11q deletion, 4% in the TP53-defected group, and 8% in wild-type patients. Our functional test, convenient for routine use, showed high sensitivity (80%) and specificity (97%) for ATM mutations prediction. Only cells with ATM mutation, but not those with sole 11q deletion, were resistant to doxorubicin. As far as fludarabine is concerned, this difference was not observed. Interestingly, patients from both these groups experienced nearly identical time to first treatment. In conclusion, ATM mutations either alone or in combination with 11q deletion uniformly led to demonstrable ATM dysfunction in patients with chronic lymphocytic leukemia and mutation presence can be predicted by the functional test using doxorubicin.

Oral squamous cell carcinoma in relation to field precancerisation: pathobiology

Squamous cell carcinoma of the oral cavity evolves within a field of precancerized oral epithelium containing keratinocytes at different stages of transformation. Following acquisition of additional genetic alterations, these precancerous keratinocytes may become cancerous.Persons with apparently successfully treated oral squamous cell carcinoma are at high risk of developing a new carcinoma at, or close to the site of the treated tumour. This second carcinoma may have developed either from malignant keratinocytes left behind at surgery (recurrence), or from transformed keratinocytes within the field of precancerized epithelium from which the primary carcinoma had arisen (new carcinoma).The cells of the new carcinoma may have genetic changes in common with the cells of the original carcinoma because both are descended from a proliferating monoclone within the precancerized field; but if the new cancer originates from a different clone, it may have a dissimilar genetic profile even if the original and the new carcinoma are closely contiguous.The purpose of this article is to review the pathobiology of oral squamous cell carcinoma in relation to fields of precancerised oral epithelium.

Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples

Detection of somatic point substitutions is a key step in characterizing the cancer genome. Mutations in cancer are rare (0.1–100/Mb) and often occur only in a subset of the sequenced cells, either due to contamination by normal cells or due to tumor heterogeneity. Consequently, mutation calling methods need to be both specific, avoiding false positives, and sensitive to detect clonal and sub-clonal mutations. The decreased sensitivity of existing methods for low allelic fraction mutations highlights the pressing need for improved and systematically evaluated mutation detection methods. Here we present MuTect, a method based on a Bayesian classifier designed to detect somatic mutations with very low allele-fractions, requiring only a few supporting reads, followed by a set of carefully tuned filters that ensure high specificity. We also describe novel benchmarking approaches, which use real sequencing data to evaluate the sensitivity and specificity as a function of sequencing depth, base quality and allelic fraction. Compared with other methods, MuTect has higher sensitivity with similar specificity, especially for mutations with allelic fractions as low as 0.1 and below, making MuTect particularly useful for studying cancer subclones and their evolution in standard exome and genome sequencing data.