Evidence for hypoxia increasing the tempo of evolution in glioblastoma

BACKGROUND

Tumour hypoxia is associated with metastatic disease, and while there have been many mechanisms proposed for why tumour hypoxia is associated with metastatic disease, it remains unclear whether one precise mechanism is the key reason or several in concert. Somatic evolution drives cancer progression and treatment resistance, fuelled not only by genetic and epigenetic mutation but also by selection from interactions between tumour cells, normal cells and physical micro-environment. Ecological habitats influence evolutionary dynamics, but the impact on tempo of evolution is less clear.

METHODS

We explored this complex dialogue with a combined clinical-theoretical approach by simulating a proliferative hierarchy under heterogeneous oxygen availability with an agent-based model. Predictions were compared against histology samples taken from glioblastoma patients, stained to elucidate areas of necrosis and TP53 expression heterogeneity.

RESULTS

Results indicate that cell division in hypoxic environments is effectively upregulated, with low-oxygen niches providing avenues for tumour cells to spread. Analysis of human data indicates that cell division is not decreased under hypoxia, consistent with our results.

CONCLUSIONS

Our results suggest that hypoxia could be a crucible that effectively warps evolutionary velocity, making key mutations more likely. Thus, key tumour ecological niches such as hypoxic regions may alter the evolutionary tempo, driving mutations fuelling tumour heterogeneity.

A new model isolates glioblastoma clonal interactions and reveals unexpected modes for regulating motility, proliferation, and drug resistance

Tumor clonal heterogeneity drives treatment resistance. But robust models are lacking that permit eavesdropping on the basic interaction network of tumor clones. We developed an in vitro, functional model of clonal cooperation using U87MG glioblastoma cells, which isolates fundamental clonal interactions. In this model pre-labeled clones are co-cultured to track changes in their individual motility, growth, and drug resistance behavior while mixed. This highly reproducible system allowed us to address a new class of fundamental questions about clonal interactions. We demonstrate that (i) a single clone can switch off the motility of the entire multiclonal U87MG cell line in 3D culture, (ii) maintenance of clonal heterogeneity is an intrinsic and influential cancer cell property, where clones coordinate growth rates to protect slow growing clones, and (iii) two drug sensitive clones can develop resistance de novo when cooperating. Furthermore, clonal communication for these specific types of interaction did not require diffusible factors, but appears to depend on cell-cell contact. This model constitutes a straightforward but highly reliable tool for isolating the complex clonal interactions that make up the fundamental "hive mind" of the tumor. It uniquely exposes clonal interactions for future pharmacological and biochemical studies.

Switching and loss of cellular cytokine producing capacity characterize in vivo viral infection and malignant transformation in human T- lymphotropic virus type 1 infection

Adult T-cell leukaemia/lymphoma (ATL) arises from chronic non-malignant human T lymphotropic virus type-1 (HTLV-1) infection which is characterized by high plasma pro-inflammatory cytokines whereas ATL is characterized by high plasma anti-inflammatory (IL-10) concentrations. The poor prognosis of ATL is partly ascribed to disease-associated immune suppression. ATL cells have a CD4+CCR4+CD26-CD7- immunophenotype but infected cells with this immunophenotype (‘ATL-like’ cells) are also present in non-malignant HTLV-1 infection. We hypothesized that ‘ATL-like’ and ATL cells have distinct cytokine producing capacity and a switch in the cytokines produced occurs during leukemogenesis. Seventeen asymptomatic carriers (ACs), 28 patients with HTLV-1-associated myelopathy (HAM) and 28 with ATL were studied. Plasma IL-10 concentration and the absolute frequency of IL-10-producing CD4+ T cells were significantly higher in patients with ATL compared to AC. IL-10-producing ATL cells were significantly more frequent than ‘ATL-like’ cells. The cytokine-producing cells were only a small fraction of ATL cells. Clonality analysis revealed that even in patients with ATL the ATL cells were composed not only of a single dominant clone (putative ATL cells) but also tens of non-dominant infected clones (‘ATL-like’ cells). The frequency of cytokine-producing cells showed a strong inverse correlation with the relative abundance of the largest clone in ATL cells suggesting that the putative ATL cells were cytokine non-producing and that the ‘ATL-like’ cells were the primary cytokine producers. These findings were confirmed by RNAseq with cytokine mRNA expression in ATL cells in patients with ATL (confirmed to be composed of both putative ATL and ‘ATL-like’ cells by TCR analysis) significantly lower compared to ‘ATL-like’ cells in patients with non-malignant HTLV-1 infection (confirmed to be composed of hundreds of non-dominant clones by TCR analysis). A significant inverse correlation between the relative abundance of the largest clone and cytokine mRNA expression was also confirmed. Finally, ‘ATL-like’ cells produced less pro- and more anti-inflammatory cytokines than non ‘ATL-like’ CD4+ cells (which are predominantly HTLV uninfected). In summary, HTLV-1 infection of CD4+ T cells is associated with a change in cytokine producing capacity and dominant malignant clonal growth is associated with loss of cytokine producing capacity. Non-dominant clones with ‘ATL-like’ cells contribute to plasma cytokine profile in patients with non-malignant HTLV-1 infection and are also present in patient with ATL.

Human T-cell lymphotropic virus type-1 (HTLV-1) infection of CD4+ T cells is associated with a change in their cytokine producing capacity and is responsible for the different plasma cytokine profiles in patients with adult T-cell leukaemia/Lymphoma (ATL) and non-malignant HTLV-1 infection. Dominant malignant clonal growth of the infected CD4+ T cells is associated with loss of cytokine producing capacity. ACs, patients with HAM and patients with ATL have a common cytokine cluster with positive correlations between pro- (TNFα and IL-6) and anti- (IL-10) inflammatory cytokines. Plasma IL-10 was higher in the HAM and ATL states compared to AC whilst there was no difference in pro-inflammatory cytokines. Patients with HAM have raised plasma concentrations of IFNγ, IL-10 and IL-17 suggesting a complex interaction between these cytokine in HAM which was not seen in ATL. Aggressive ATL is associated with raised plasma concentrations of pro- and anti-inflammatory cytokines compared to indolent ATL. This cytokine profile did not precede or predict aggressive ATL. The ‘ATL-like’ infected cells in ACs and in patients with HAM have lower pro- and higher anti-inflammatory cytokine secretion than non- ‘ATL-like’ cells which are predominantly HTLV-1 uninfected. Putative ATL cells have little or no cytokine producing capacity. ‘ATL-like’ infected cells from non-dominant infected clones were present not only in patients with non-malignant HTLV-1 infection but also ATL. ‘ATL-like’ cells have cytokine producing capacity and contribute to plasma cytokine profile in patients with non-malignant HTLV-1 infection and possibly also in ATL.

High Throughput Sequencing Analysis of the Immunoglobulin Heavy Chain Gene from Flow-Sorted B Cell Sub-Populations Define the Dynamics of Follicular Lymphoma Clonal Evolution

Understanding the dynamics of evolution of Follicular Lymphoma (FL) clones during disease progression is important for monitoring and targeting this tumor effectively. Genetic profiling of serial FL biopsies and examples of FL transmission following bone marrow transplant suggest that this disease may evolve by divergent evolution from a common ancestor cell. However where this ancestor cell resides and how it evolves is still unclear. The analysis of the pattern of somatic hypermutation of the immunoglobulin gene (Ig) is traditionally used for tracking the physiological clonal evolution of B cells within the germinal center and allows to discriminate those cells that have just entered the germinal center and display features of ancestor cells from those B cells that keep re-circulating across different lymphoid organs. Here we investigated the pattern of somatic hypermutation of the heavy chain of the immunoglobulin gene (IgH-VH) in 4 flow-sorted B cells subpopulations belonging to different stages of differentiation, from sequential lymph node biopsies of cases displaying diverse patterns of evolution, using the GS-FLX Titanium sequencing platform. We observed an unexpectedly high level of clonality, with hundreds of distinct tumor subclones in the different subpopulations from the same sample, the majority detected at a frequency <10-2. By using a lineage trees analysis we observed in all our FL and t-FL cases that the oligoclonal FL population was trapped in a narrow intermediate stage of maturation that maintains the capacity to undergo SHM, but was unable to further differentiate. The presence of such a complex architecture highlights challenges currently encountered in finding a cure for this disease.

Clonal expansion analysis of transposon insertions by high-throughput sequencing identifies candidate cancer genes in a PiggyBac mutagenesis screen

Somatic transposon mutagenesis in mice is an efficient strategy to investigate the genetic mechanisms of tumorigenesis. The identification of tumor driving transposon insertions traditionally requires the generation of large tumor cohorts to obtain information about common insertion sites. Tumor driving insertions are also characterized by their clonal expansion in tumor tissue, a phenomenon that is facilitated by the slow and evolving transformation process of transposon mutagenesis. We describe here an improved approach for the detection of tumor driving insertions that assesses the clonal expansion of insertions by quantifying the relative proportion of sequence reads obtained in individual tumors. To this end, we have developed a protocol for insertion site sequencing that utilizes acoustic shearing of tumor DNA and Illumina sequencing. We analyzed various solid tumors generated by PiggyBac mutagenesis and for each tumor >10⁶ reads corresponding to >10⁴ insertion sites were obtained. In each tumor, 9 to 25 insertions stood out by their enriched sequence read frequencies when compared to frequencies obtained from tail DNA controls. These enriched insertions are potential clonally expanded tumor driving insertions, and thus identify candidate cancer genes. The candidate cancer genes of our study comprised many established cancer genes, but also novel candidate genes such as Mastermind-like1 (Mamld1) and Diacylglycerolkinase delta (Dgkd). We show that clonal expansion analysis by high-throughput sequencing is a robust approach for the identification of candidate cancer genes in insertional mutagenesis screens on the level of individual tumors.

Elevated tolerance to aneuploidy in cancer cells: estimating the fitness effects of chromosome number alterations by in silico modelling of somatic genome evolution

An unbalanced chromosome number (aneuploidy) is present in most malignant tumours and has been attributed to mitotic mis-segregation of chromosomes. However, recent studies have shown a relatively high rate of chromosomal mis-segregation also in non-neoplastic human cells, while the frequency of aneuploid cells remains low throughout life in most normal tissues. This implies that newly formed aneuploid cells are subject to negative selection in healthy tissues and that attenuation of this selection could contribute to aneuploidy in cancer. To test this, we modelled cellular growth as discrete time branching processes, during which chromosome gains and losses were generated and their host cells subjected to selection pressures of various magnitudes. We then assessed experimentally the frequency of chromosomal mis-segregation as well as the prevalence of aneuploid cells in human non-neoplastic cells and in cancer cells. Integrating these data into our models allowed estimation of the fitness reduction resulting from a single chromosome copy number change to an average of ≈30% in normal cells. In comparison, cancer cells showed an average fitness reduction of only 6% (p = 0.0008), indicative of aneuploidy tolerance. Simulations based on the combined presence of chromosomal mis-segregation and aneuploidy tolerance reproduced distributions of chromosome aberrations in >400 cancer cases with higher fidelity than models based on chromosomal mis-segregation alone. Reverse engineering of aneuploid cancer cell development in silico predicted that aneuploidy intolerance is a stronger limiting factor for clonal expansion of aneuploid cells than chromosomal mis-segregation rate. In conclusion, our findings indicate that not only an elevated chromosomal mis-segregation rate, but also a generalised tolerance to novel chromosomal imbalances contribute to the genomic landscape of human tumours.

Evolutionary dynamics of carcinogenesis and why targeted therapy does not work

All malignant cancers, whether inherited or sporadic, are fundamentally governed by Darwinian dynamics. The process of carcinogenesis requires genetic instability and highly selective local microenvironments, the combination of which promotes somatic evolution. These microenvironmental forces, specifically hypoxia, acidosis and reactive oxygen species, are not only highly selective, but are also able to induce genetic instability. As a result, malignant cancers are dynamically evolving clades of cells living in distinct microhabitats that almost certainly ensure the emergence of therapy-resistant populations. Cytotoxic cancer therapies also impose intense evolutionary selection pressures on the surviving cells and thus increase the evolutionary rate. Importantly, the principles of Darwinian dynamics also embody fundamental principles that can illuminate strategies for the successful management of cancer.