Monitoring therapy responses at the leukemic subclone level by ultra-deep amplicon resequencing in acute myeloid leukemia

CDC27 gene expression patterns as a potential biomarker in Acute Leukemia

BACKGROUND

Treating Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) is difficult due to high relapse rates and drug resistance. Tumorigenesis is largely dependent on disruption of the cell cycle progression. While the role of Cell Division Cycle 27 (CDC27) in the anaphase-promoting complex/cyclosome is well-known, its significance in the pathophysiology of acute leukemia and its potential as a biomarker are less well understood.

METHODS AND RESULTS

This case-control study used samples from 100 leukemia patients (50 with ALL and 50 with AML) at Shariati Hospital in Tehran, Iran, along with 50 healthy individuals. The expression of CDC27 was analyzed using quantitative real-time PCR (RQ-PCR). Statistical analysis was done using the nonparametric Mann-Whitney U test. The results showed that AML and ALL patients had significantly higher levels of CDC27 expression compared to the control group. Although a weak correlation between CDC27 expression and hematological parameters was found, there was no significant correlation with sample type, demographics, clinical variables or prognosis.

CONCLUSIONS

This study highlights the potential of CDC27 as an oncogene, as well as a possible prognostic and diagnostic marker in acute leukemias. It suggests that CDC27 could be a valuable biomarker or therapeutic target in the treatment of AML and ALL.

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

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

SIGNIFICANCE

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

Ultra-deep sequencing mutation analysis of the BCR/ABL1 kinase domain in newly diagnosed chronic myeloid leukemia patients

Ultra-deep sequencing detects low-frequency genetic mutations with high sensitivity. We used this approach to prospectively examine mutations in the BCR/ABL1 tyrosine kinase from patients with newly diagnosed, chronic-phase chronic myeloid leukemia (CML) treated with the tyrosine kinase inhibitor nilotinib. Between May 2013 and November 2014, 50 patients from 18 institutions were enrolled in the study. We screened 103 somatic mutations and found that mutations in the P-loop domain were the most frequent (173/454 mutations in the P-loop) and noted the presence of the V299 L mutation (dasatinib-resistant/nilotinib-sensitive) in 98 % of patients (49/50). No patients had Y253H, E255 V, or F359 V/C/I mutations, which would recommend dasatinib rather than nilotinib treatment. The S417Y mutation was associated with lower achievement of a major molecular response (MMR) at 6 months, and the V371A mutation was associated with reduced MMR and MR^4.5 durations (MMR for 2 years: 100 % for no mutation vs. 75 % for mutation, P=0.039; MR^4.5 for 15 months: 94.1 % vs. 25 %, P=0.002). Patients with known nilotinib-resistant mutations had lower rates of MR^4.5 achievement. In conclusion, ultra-deep sequencing is a sensitive method for genetic-based treatment decisions. Based on the results of these mutational analyses, nilotinib treatment is a promising option for Korean patients with CML.

The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer

Evolutionary game theory mathematically conceptualizes and analyzes biological interactions where one's fitness not only depends on one's own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer's eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. Moreover, we discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with evolutionary game theory has medically useful implications that can inform and create a lockstep between empirical findings and mathematical modeling. We suggest that cancer progression is an evolutionary competition between different cell types and therefore needs to be viewed as an evolutionary game.

Harnessing Tumor Evolution to Circumvent Resistance

High-throughput sequencing can be used to measure changes in tumor composition across space and time. Specifically, comparisons of pre- and post-treatment samples can reveal the underlying clonal dynamics and resistance mechanisms. Here, we discuss evidence for distinct modes of tumor evolution and their implications for therapeutic strategies. In addition, we consider the utility of spatial tissue sampling schemes, single-cell analysis, and circulating tumor DNA to track tumor evolution and the emergence of resistance, as well as approaches that seek to forestall resistance by targeting tumor evolution. Ultimately, characterization of the (epi)genomic, transcriptomic, and phenotypic changes that occur during tumor progression coupled with computational and mathematical modeling of tumor evolutionary dynamics may inform personalized treatment strategies.

Multicenter validation of cancer gene panel-based next-generation sequencing for translational research and molecular diagnostics

The simultaneous detection of multiple somatic mutations in the context of molecular diagnostics of cancer is frequently performed by means of amplicon-based targeted next-generation sequencing (NGS). However, only few studies are available comparing multicenter testing of different NGS platforms and gene panels. Therefore, seven partner sites of the German Cancer Consortium (DKTK) performed a multicenter interlaboratory trial for targeted NGS using the same formalin-fixed, paraffin-embedded (FFPE) specimen of molecularly pre-characterized tumors (n = 15; each n = 5 cases of Breast, Lung, and Colon carcinoma) and a colorectal cancer cell line DNA dilution series. Detailed information regarding pre-characterized mutations was not disclosed to the partners. Commercially available and custom-designed cancer gene panels were used for library preparation and subsequent sequencing on several devices of two NGS different platforms. For every case, centrally extracted DNA and FFPE tissue sections for local processing were delivered to each partner site to be sequenced with the commercial gene panel and local bioinformatics. For cancer-specific panel-based sequencing, only centrally extracted DNA was analyzed at seven sequencing sites. Subsequently, local data were compiled and bioinformatics was performed centrally. We were able to demonstrate that all pre-characterized mutations were re-identified correctly, irrespective of NGS platform or gene panel used. However, locally processed FFPE tissue sections disclosed that the DNA extraction method can affect the detection of mutations with a trend in favor of magnetic bead-based DNA extraction methods. In conclusion, targeted NGS is a very robust method for simultaneous detection of various mutations in FFPE tissue specimens if certain pre-analytical conditions are carefully considered.

The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy

Treatment of chronic lymphocytic leukemia (CLL) has shifted from chemo-immunotherapy to targeted agents. To define the evolutionary dynamics induced by targeted therapy in CLL, we perform serial exome and transcriptome sequencing for 61 ibrutinib-treated CLLs. Here, we report clonal shifts (change >0.1 in clonal cancer cell fraction, Q < 0.1) in 31% of patients during the first year of therapy, associated with adverse outcome. We also observe transcriptional downregulation of pathways mediating energy metabolism, cell cycle, and B cell receptor signaling. Known and previously undescribed mutations in BTK and PLCG2, or uncommonly, other candidate alterations are present in seventeen subjects at the time of progression. Thus, the frequently observed clonal shifts during the early treatment period and its potential association with adverse outcome may reflect greater evolutionary capacity, heralding the emergence of drug-resistant clones.

In a subset of patients with chronic lymphocytic leukemia (CLL) treated with targeted agents, such as ibrutinib, drug resistant subclones emerge. Here, the authors report on transcriptional changes in CLL patients treated with ibrutinib and identify early clonal shifts associated with evolution of resistant clones.