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Results for “Cancer Biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

Differential effects of two HDAC inhibitors with distinct concomitant DNA hypermethylation or hypomethylation in breast cancer cells

DNA methylation and histone acetylation are the two important epigenetic phenomena that control the status of X-chromosome inactivation (XCI), a process of dosage compensation in mammals resulting in active X chromosome (Xa) and inactive X chromosome (Xi) in females. While DNA methyltransferases (DNMTs) are known to maintain the DNA hypermethylation of Xi, it remains to be determined how one or a few of 18 known histone deacetylases (HDACs) contribute(s) to Xi maintenance. Herein we found that HDAC1/2/4/6 were overexpressed in breast cancer cells, MDA-MB-231, with Xa/Xa status compared to normal breast epithelial cells, MCF10A, with Xa/Xi status. Inhibition of these overexpressed HDACs with two different drugs, sodium butyrate (SB) and Trichostatin A (TSA), caused surprisingly distinct effects on global DNA methylation: hypermethylation and hypomethylation, respectively, as well as distinct effects on a repressing histone mark H3K27me3 for heterochromatin and an active mark H3K56ac for DNA damage. Surveying three DNMTs through immunoblot analyses for insights revealed the up- or down-regulation of DNMT3A upon drug treatments in a concentration-dependent manner. These results correlated with the decreased XIST and increased TSIX expression in MDA-MB 231 as a possible mechanism of Xi loss and were reversed with SB treatment. Further RNA-seq analysis indicated differential gene expression correlating with the promoter methylation status of a few genes. Collectively, our results demonstrate a crosstalk between HDACs and DNMTs and the novel involvement of HDACs in skewed Xi in breast cancer.

cancer biology↗

bioRxiv2019

Oncogenic hijacking of a developmental transcription factor evokes therapeutic vulnerability for ROS-induction in Ewing sarcoma

Ewing sarcoma (EwS) is an aggressive childhood cancer likely originating from mesenchymal stem cells or osteo-chondrogenic progenitors. It is characterized by fusion oncoproteins involving EWSR1 and variable members of the ETS-family of transcription factors (in 85% FLI1). EWSR1-FLI1 can induce target genes by using GGAA-microsatellites (mSats) as enhancers.\n\nHere, we show that EWSR1-FLI1 hijacks the developmental transcription factor SOX6 - a physiological driver of proliferation of osteo-chondrogenic progenitors - by binding to an intronic GGAA-mSat, which promotes EwS growth in vitro and in vivo. Through integration of transcriptome-profiling, published drug-screening data, and functional in vitro and in vivo experiments, we discovered that SOX6 interferes with the antioxidant system resulting in constitutively elevated reactive oxygen species (ROS) levels that create a therapeutic vulnerability toward the ROS-inducing drug Elesclomol.\n\nCollectively, our results exemplify how aberrant activation of a developmental transcription factor by a dominant oncogene can promote malignancy, but provide opportunities for targeted therapy.

cancer biology↗

bioRxiv2019

Selection of a Malignant Subpopulation from a Colorectal Cancer Cell Line

Colorectal cancer (CRC) is a leading cause of death from cancer worldwide. Thus, there is an emerging need for new experimental models that allow identification and validation of biomarkers for CRC-specific progression. In this study, we propose a repeated sphere-forming assay as a strategy to select a malignant subpopulation from a CRC line, HCT116. We validated our assay by confirming that three canonical stemness markers, Nanog, Oct4, and Lgr5, were up-regulated in the sphere state at every generation of the selection assay. The resulting line, after eight rounds of selection, exhibited an increased sphere-forming capacity in vitro and tumorgenicity in vivo. Furthermore, dipeptidase 1 (DPEP1) was identified as the major differentially expressed gene in the selected clone, and depletion of DPEP1 suppressed the elevated sphere-forming capacity in vitro and tumorgenicity in vivo. Overall, we have established an experimental strategy for the isolation of a malignant subpopulation from a CRC cell line. Results from our model also suggested that DPEP1 can serve as a promising prognostic biomarker for CRC.

cancer biology↗

bioRxiv2019

Gene Expression Mediated Antiproliferative Potential and Safety of Selected Medicinal Plants Against Cancerous and Normal Cells

Globally, approximately 13% of all deaths annually are attributed to cancer. Surgery, radiation and chemotherapy are the current treatment techniques for cancer, however these methods are expensive, have high failure rates and have been associated with detrimental side effects. Plant derived products could be good candidates in alleviating challenges being experienced with these current methods. This study aimed at evaluating the phytochemistry, antiproliferation potential, and probable mechanism of action of Albizia gummifera, Rhamnus staddo and Senna didymobotrya plant extracts. Phytochemical screening was done as per standard procedures. The common 3- (4, 5-dimethylthiazol-2-yl) -2, 5-diphenyltetrazolium (MTT) dye was used in the determination of the antiproliferative activity of the extracts. Extracts induction of VEGF (angiogenesis) and p53 (apoptosis) genes expression was evaluated using Real Time Polymerase Chain Reaction. Phytochemical screening revealed presence of alkaloids, tannins, glycosides, flavonoids, terpenes, phenolics and saponins in the plants extracts. A. gummiferas stem bark methanol: dichloromethane extract had the highest activity against the cancerous cell lines tested: HCC1395 (IC50 6.07{+/-}0.04g/ml), DU145 (IC50 3.34{+/-}0.05g/ml), CT26 (IC50 5.78{+/-}0.08g/ml) and Hep2 (IC50 7.02{+/-}0.01g/ml). R. staddo root bark methanol: dichloromethane extract had an IC50 value of 15.71{+/-}0.04g/ml on HCC, 9.81{+/-}0.09g/ml on Hep2 and 11.14{+/-}0.39g/ml on CT26. S. didymobotrya root bark methanol: dichloromethane extract inhibited HCC with an IC50 of 65.06{+/-}0.07g/ml, CT26 with an IC50 of 15.71{+/-}0.04g/ml and Hep2 with an IC50 of 62.10{+/-}0.11g/ml. From the results obtained, the plants exhibited selective toxicity to cancer cells while sparing the normal cells (SI [≥] 3). A. gummifera and S. didymobotrya and R. staddo plant extracts upregulated p53 and down-regulated VEGF genes. In conclusion, this study confirms that these plant extracts could be potential candidates for development of drugs for the management of breast, prostrate, colorectal and throat cancer.

cancer biology↗

bioRxiv2019

Analysis of patient derived xenograft studies in Oncology drug development: impact on design and interpretation of future studies

BackgroundPreclinical Oncology drug development is heavily reliant on xenograft studies to assess the anti-tumour effect of new compounds. Patient derived xenograft (PDX) have become popular as they may better represent the clinical disease, however variability is greater than in cell-line derived xenografts. The typical approach of analysing these studies involves performing an un-paired t-test on the mean tumour volumes between the treated and control group at the end of the study. This approach ignores the time-series and may result in false conclusions, especially when considering the increased variability of PDX studies.\n\nAimTo test the hypothesis that a model-based analysis provides increased power than analysis of final day volumes and to provide insights into more efficient PDX study designs.\n\nMethodsData was extracted from tumour xenograft time-series data from a large publicly available PDX drug treatment database released by Novartis. For all 2-arm studies the percent tumour growth inhibition (TGI) at two time-points, day 10 and day 14 was calculated. For each study, the effect of treatment was calculated using an un-paired t-test and also a model-based analysis using the likelihood ratio-test. In addition a simulation study was also performed to assess the difference in power between the two data-analysis approaches for different levels of TGI for PDX or standard cell-line derived xenografts (CDX).\n\nResultsThe model-based analysis had greater statistical power than the un-paired t-test approach within the PDX data-set. The model-based approach was able to detect TGI values as low as 25 percent whereas the un-paired t-test approach required at least 50 percent TGI. These findings were confirmed within the simulation study performed which also highlighted that CDX studies require less animals than PDX studies which show the equivalent level of TGI.\n\nConclusionThe analysis of 59 2-arm PDX studies highlighted that taking a model-based approach gave increased statistical power over simply performing an un-paired t-test on the final study day. Importantly the model-based approach was able to detect smaller size of effect compared to the un-paired t-test approach is which maybe common of such studies. These findings were confirmed within simulated studies which also highlighted the same sample size used for CDX studies would lead to inadequately powered PDX studies. Application of a model-based analysis should allow studies to use less animals and run experiments for a shorter period thus providing effective insight into compound anti-tumour activity

cancer biology↗

bioRxiv2019

PP2A inhibitor PME-1 suppresses anoikis, and is associated with therapy relapse of PTEN-deficient prostate cancers

While organ-confined PCa is mostly therapeutically manageable, metastatic progression of PCa remains an unmet clinical challenge. Resistance to anoikis, a form of cell death initiated by cell detachment from the surrounding extracellular matrix, is one of the cellular processes critical for PCa progression towards aggressive disease. Therefore, further understanding of anoikis regulation in PCa might provide therapeutic opportunities. Here, we discover that PCa tumors with concomitantly compromised function of two tumor suppressor phosphatases, PP2A and PTEN, are particularly aggressive, having less than 50% 5-year secondary-therapy free patient survival. Functionally, overexpression of PME-1, a PP2A inhibitor protein, inhibits anoikis in PTEN-deficient PCa cells. In vivo, PME-1 inhibition increased apoptosis in in ovo PCa tumor xenografts, and attenuated PCa cell survival in zebrafish circulation. Molecularly, PME-1 deficient PCa cells display increased trimethylation at lysines 9 and 27 of histone H3 (H3K9me3 and H3K27me3), a phenotype corresponding to increased apoptosis sensitivity. In summary, we discover that PME-1 overexpression supports anoikis resistance in PTEN-deficient PCa cells. Clinically, the results identify PME-1 as a candidate biomarker for a subset of particularly aggressive PTEN-deficient PCa.

cancer biology↗

bioRxiv2019

Tissue-specific MicroRNA Expression Alters Cancer Susceptibility Conferred by a TP53 Noncoding Variant

Patients carrying TP53 germline mutations develop Li-Fraumeni syndrome (LFS), a rare genetic disorder with high risk of several cancers, most notably breast cancer, sarcoma, and brain tumors. A noncoding polymorphism (rs78378222) in TP53, carried by scores of millions of people, was associated with moderate risk of brain, colon, and prostate tumors, and other neoplasms. We found a positive association between this variant and soft tissue sarcoma (odds ratio [OR] = 4.55, P = 3.3 x 10-5). In sharp contrast, this variant was protective against breast cancer (OR = 0.573, P = 0.0078). We generated a mouse line carrying this variant and found that this variant accelerated spontaneous tumorigenesis and tumor development at the brain, prostate, colon, and skeletal muscle, but strikingly, it significantly delayed mammary tumorigenesis. The variant created a miR-382 targeting site and compromised a miR-325 targeting site. Their differential expression resulted in p53 downregulation in the brain and several other tissues, but p53 upregulation in the mammary gland of the mutant mice compared to that of wild-type littermates. Thus, this TP53 variant is at odds with LFS mutants in breast cancer predisposition yet consistent with LFS mutants in susceptibility to soft tissue sarcoma and glioma. Our findings elucidate an underlying mechanism of cancer susceptibility that is conferred by genetic variation and yet altered by microRNA expression.

cancer biology↗

bioRxiv2019

ITGA2 is a target of miR-206 promoting cancer stemness and lung metastasis through enhanced ACLY and CCND1 expression in triple negative breast cancer

Accumulating evidence demonstrates that cancer stemness is essential for both tumor development and progression, regulated by multi-layer factors at genetic, epigenetic and micro-environmental levels. However, how to target stemness-driven plasticity and eliminate metastasis remains one of the biggest challenges in the clinic. We aim to identify novel molecular mechanisms underlying stemness of triple negative breast cancer (TNBC) which frequently metastasizes to the visceral organs but lacks targeted therapies. Following our previous discovery of miR-206 as an epigenetic suppressor of tumorigenesis and metastasis, we now report that the integrin receptor CD49b-encoding ITGA2 is an oncogenic target of miR-206 in TNBC. ITGA2 knockdown abolished cancer stemness (mammosphere formation, pluripotency marker expression, and FAK phosphorylation), inhibited cell cycling, compromised migration and invasion, and thereby decreasing lung metastasis of TNBC. RNA sequencing analyses of breast cancer cells revealed that ITGA2 knockdown inhibits gene expression essential for both classical integrin-regulated pathways (cell cycle, wounding response, protein kinase, etc) and newly identified pathways such as lipid metabolism. Notably, ACLY-encoded ATP citrate lyase is one of the top targets in CD49b-regulated lipid metabolism and CCND1-encoded Cyclin D1 represents regulation of cell cycle and many other pathways. ACLY, known to catalyze the formation of cytosolic acetyl-CoA for fatty acid biosynthesis, is indispensable for cancer stemness. Overexpression of CCND1 rescues the phenotype of ITGA2 knockdown-induced cell cycle arrest. High expression levels of the ITGA2/ACLY/CCND1 axis are correlated with an unfavorable relapse-free survival of patients with high grade breast cancer, in both basal-like and other subtypes. This study identifies ITGA2 as a potential therapeutic target of TNBC stemness and metastasis.

cancer biology↗

bioRxiv2019

Breast cancer classification based on proteotypes obtained by SWATH mass spectrometry

Accurate breast cancer classification is vital for patient management decisions, and better tumour classification is expected to enable more precise and eventually personalized treatment to improve patient outcomes. Here, we present a novel quantitative proteotyping approach based on SWATH mass spectrometry and establish key proteins for breast tumour classification derived from proteotype data. The study was based on 96 tissue samples representing five breast cancer subtypes according to conventional classification. Correlation of SWATH proteotype patterns indicated groups that largely recapitulate these subtypes. However, the proteotype-based classification also revealed varying degrees of heterogeneity within the conventional subtypes, with triple negative tumours being the most heterogeneous. Proteins that contributed most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2, which are associated with oestrogen receptor status, tumour grade, and HER2 status, respectively. While these three key proteins exhibited high levels of correlation between protein and transcript levels (R>0.67), general correlation did not exceed R=0.29, indicating the value of protein-level measurements of biomarkers and disease-regulated genes. Overall, our data shows how large-scale protein-level measurements by next-generation proteomics can lead to improved patient stratification for precision medicine.

cancer biology↗

bioRxiv2019

Evaluation of PicoGreen variants for use in microscopy and flow cytometry

PicoGreen is a fluorescent probe that binds dsDNA and forms a highly luminescent complex when compared to the free dye in solution. This unique probe is widely used in DNA quantitation assays but has limited application in flow cytometry and microscopy. Here we have investigated various PicoGreen variants for the ability to stain low amounts of cytosolic DNA present in many tumor cells. Analysis of stained cells by flow cytometry and fluorescent microscopy showed that certain variants improved the ability to stain low levels of cytosolic DNA when compared to the commercially available PicoGreen molecule.

cancer biology↗

bioRxiv2019

An Exon Skipping Screen Identifies Antitumor Drugs That Are Potent Modulators of Pre-mRNA Splicing, Suggesting New Therapeutic Applications

Agents that modulate pre-mRNA splicing are of interest in multiple therapeutic areas, including cancer. We report our recent screening results with the application of a cell-based Triple Exon Skipping Luciferase Reporter (TESLR) using a library that is composed of FDA approved drugs, clinical compounds, and mechanistically characterized tool compounds. Confirmatory assays showed that three clinical antitumor therapeutic candidates (milciclib, PF-3758309 and PF-030871) are potent splicing modulators and that these drugs are, in fact, nanomolar inhibitors of multiple kinases involved in the regulation the spliceosome. We also report the identification of new SF3B1 antagonists (sudemycinol C and E) and show that these antagonists can be used to develop a displacement assay for SF3B1 small molecule ligands. These results further supports the broad potential for the development of agents that target the spliceosome for the treatment of cancer and other diseases, as well as new avenues for chemotherapeutic discovery.

cancer biology↗

bioRxiv2019

CCL5 promotes breast cancer recurrence through macrophage recruitment in residual tumors

Over half of breast cancer related deaths are due to recurrence five or more years after initial diagnosis and treatment. This latency suggests that a population of residual tumor cells can survive treatment and persist in a dormant state for many years. The role of the microenvironment in regulating the survival and proliferation of residual cells following therapy remains unexplored. Using a conditional mouse model for Her2-driven breast cancer, we identify interactions between residual tumor cells and their microenvironment as critical for promoting tumor recurrence. Her2 downregulation leads to an inflammatory program driven by TNF/NF{kappa}B signaling, which promotes immune cell infiltration in regressing and residual tumors. The cytokine CCL5 is elevated following Her2 downregulation and remains high in residual tumors. CCL5 promotes tumor recurrence by recruiting CCR5-expressing macrophages, which may contribute to collagen deposition in residual tumors. Blocking this TNF-CCL5-macrophage axis may be efficacious in preventing breast cancer recurrence.

cancer biology↗

bioRxiv2019

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations from exponential growth only at higher densities due to limited resources such as space and nutrients. However, recent pre-clinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models however, tumor growth data is limited by the lower limit of detection (i.e. a measurable lesion) and confounding variables, such as tumor microenvironment and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to consider the small number of cells in this low-density regime and use the moment approach for stochastic parameter estimation to calibrate the stochastic growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells depends on cell number. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging tumors and relapse.\n\nAuthor SummaryThe growth kinetics of cancer cells at very low cell densities are of utmost clinical importance as the ability of a small number of newly transformed or surviving cells to grow exponentially and thus, to \"take off\" underlies tumor formation and relapse after treatment. Mathematical models of stochastic tumor cell growth typically assume a stochastic birth-death process of cells impacted by limited nutrients and space when cells reach high density, resulting in the widely accepted logistic growth model. Here we present an in-depth investigation of alternate growth models adopted from ecology to describe potential deviations from a simple cell autonomous birth-death model at low cell densities. We show that our stochastic modeling framework is robust and can be used to identify the underlying structure of stochastic growth trajectories from both simulated and experimental data taken from a controlled in vitro setting in which we can capture data from the relevant low cell density regime. This work suggests that the assumption of cell autonomous proliferation via a constant exponential growth rate at low cell densities may not be appropriate for all cancer cell growth dynamics. Consideration of cooperative behavior amongst tumor cells in this regime is critical for elucidating strategies for controlling tumor cell growth.

cancer biology↗

bioRxiv2019

PFA ependymoma-associated protein EZHIP inhibits PRC2 activity through a H3 K27M-like mechanism

Polycomb group (PcG) proteins are essential for development and are frequently misregulated in human cancers. Polycomb Repressive Complexes (PRC1, PRC2) function in a collaborative epigenetic cross-talk with H3K27me3 to initiate and maintain transcriptional silencing. Diffuse intrinsic pontine gliomas (DIPGs) have extremely low H3K27me3 levels mediated by H3 K27M oncohistone. Posterior fossa type A (PFA) ependymomas also exhibit very low H3K27 methylation but lack the K27M oncohistone. Instead, PFA tumors express high levels of EZHIP (Enhancer of Zeste Homologs Inhibitory Protein, also termed CXORF67). We find that a highly conserved sequence within the C-terminus of EZHIP is necessary and sufficient to inhibit the catalytic activity of PRC2 in vitro and in vivo. Our biochemical experiments indicate that EZHIP directly interacts with the active site of the EZH2 subunit in a mechanism that is remarkably similar to the K27M oncohistone. Furthermore, expression of H3 K27M or EZHIP in cells promote similar chromatin profiles: loss of broad H3K27me3 domains, but retention of H3K27me3 at the sites of PRC2 recruitment. Importantly, we find that H3K27me3-mediated allosteric activation of PRC2 substantially increases the inhibition potential of EZHIP and H3 K27M, providing a potential mechanism for loss of H3K27me3 spreading from CpG islands in vivo. Our data indicate that PFA ependymoma and DIPG are driven in part by the action of peptidyl PRC2 inhibitors- the K27M oncohistone and the EZHIP oncohistone-mimic- that dysregulate gene silencing to promote tumorigenesis.

cancer biology↗

bioRxiv2019

Distinct immune evasion in APOBEC-enriched, HPV-negative HNSCC

Immune checkpoint inhibition leads to response in some patients with head and neck squamous cell carcinoma (HNSCC). Robust biomarkers are lacking to date.\n\nWe analyzed viral status, gene expression signatures, mutational load and mutational signatures in whole exome and RNA-sequencing data of the HNSCC TCGA dataset (N = 496) and a validation set (DKTK MASTER cohort, N = 10). Public single-cell gene expression data from 17 HPV-negative HNSCC were separately re-analyzed.\n\nAmong HPV-negative HNSCC, APOBEC3-associated TCW motif mutations but not total single nucleotide variant burden were significantly associated with inflammation. APOBEC3-enriched HPV-negative HNSCC showed higher T-cell inflammation and immune checkpoint expression. Mutations in immune-evasion pathways were enriched in these tumors. APOBEC3B and 3C expression was identified in tumor cells and correlated with tumor inflammation.\n\nWe identified an APOBEC-enriched subgroup of HPV-negative HNSCC with a distinct immunogenic phenotype, potentially mediating response to immunotherapy.

cancer biology↗

bioRxiv2019

Effective clustering for Single Cell Sequencing cancer data

Single cell sequencing (SCS) technologies provide a level of resolution that makes it indispensable for inferring from a sequenced tumor, evolutionary trees or phylogenies representing an accumulation of cancerous mutations. A drawback of SCS is elevated false negative and missing value rates, resulting in a large space of possible solutions, which in turn makes it difficult, sometimes infeasible using current approaches and tools. One possible solution is to reduce the size of an SCS instance -- usually represented as a matrix of presence, absence, and uncertainty of the mutations found in the different sequenced cells -- and to infer the tree from this reduced-size instance. In this work, we present a new clustering procedure aimed at clustering such categorical vector, or matrix data -- here representing SCS instances, called celluloid. We show that celluloid clusters mutations with high precision: never pairing too many mutations that are unrelated in the ground truth, but also obtains accurate results in terms of the phylogeny inferred downstream from the reduced instance produced by this method. We demonstrate the usefulness of a clustering step by applying the entire pipeline (clustering + inference method) to a real dataset, showing a significant reduction in the runtime, raising considerably the upper bound on the size of SCS instances which can be solved in practice. Our approach, celluloid: clustering single cell sequencing data around centroids is available at https://github.com/AlgoLab/celluloid/ under an MIT license, as well as on the Python Package Index (PyPI) at https://pypi.org/project/celluloid-clust/

cancer biology↗

bioRxiv2019

Clinical and molecular characterization of virus-positive and virus-negative Merkel cell carcinoma

Merkel cell carcinoma (MCC) is a highly aggressive neuroendocrine carcinoma of the skin mediated by the integration of Merkel cell polyomavirus (MCPyV) and expression of viral T antigens or by ultraviolet induced damage to the tumor genome from excessive sunlight exposure. An increasing number of deep sequencing studies of MCC have identified significant differences between the number and types of point mutations, copy number alterations, and structural variants between virus-positive and virus-negative tumors. In this study, we assembled a cohort of 71 MCC patients and performed deep sequencing with OncoPanel, a next-generation sequencing assay targeting over 400 cancer-associated genes. To improve the accuracy and sensitivity for virus detection compared to traditional PCR and IHC methods, we developed a hybrid capture baitset against the entire MCPyV genome. The viral baitset identified integration junctions in the tumor genome and generated assemblies that strongly support a model of a hybrid, virus-host, circular DNA intermediate during integration that promotes focal amplification of host DNA. Using the clear delineation between virus-positive and virus-negative tumors from this method, we identified recurrent somatic alterations common across MCC and alterations specific to each class of tumor, associated with differences in overall survival. Comparing the molecular and clinical data from these patients revealed a surprising association of immunosuppression with virus-negative MCC and significantly shortened overall survival. These results demonstrate the value of high-confidence virus detection for identifying clinically important features in MCC that impact patient outcome.

cancer biology↗

bioRxiv2019

Serum Flt3 ligand is a biomarker of progenitor cell mass and prognosis in acute myeloid leukemia

Fms-like tyrosine kinase 3 (Flt3) is a hematopoietic growth factor receptor expressed on lymphomyeloid progenitors and frequently, by AML blasts. Its ligand, Flt3L, has non-hematopoietic and lymphoid origins, is detectable during homeostasis and increases to high levels in states of hypoplasia due to genetic defects or treatment with cytoreductive agents. Measurement of Flt3L by ELISA reveals that Flt3+AML, is associated with depletion of Flt3L to undetectable levels. After induction chemotherapy, Flt3L is restored in patients entering CR, but remains depressed in those with refractory disease. Weekly sampling reveals marked differences in the kinetics of Flt3L response during the first 6 weeks of treatment, proportionate to the clearance of blasts and cellularity of the BM. In the UK NCRI AML17 trial, Flt3L was measured at day 26 in a subgroup of 135 patients with Flt3 mutation randomized to the tyrosine kinase inhibitor lestaurtinib. In these patients, attainment of CR was associated with higher Flt3L at day 26 (Mann-Whitney p < 0.0001). Day 26 Flt3L was also associated with survival: Flt3L [≤] 291pg/ml was associated with inferior event-free survival; and, Flt3L >1185pg/ml was associated with higher overall survival (p = 0.0119). Serial measurement of Flt3L in patients who had received a hematopoietic stem cell transplant for AML further illustrated the potential value of declining Flt3L to identify relapse. Together these observations suggest that measurement of Flt3L provides a non-invasive estimate of progenitor cell mass in most patients with AML, with the potential to inform clinical decisions.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=151 HEIGHT=200 SRC=\"FIGDIR/small/588319_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@132f3f3org.highwire.dtl.DTLVardef@2e033eorg.highwire.dtl.DTLVardef@d70598org.highwire.dtl.DTLVardef@b0648a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗