A Pilot Analysis of Whole Transcriptome of Human Cryopreserved Sperm.

Sperm cryopreservation is a procedure widely used to store gametes for later use, to preserve fertility in patients prior to gonadotoxic treatments or surgery, and for sperm donation programs. The purpose of the study was to assess the impact of cryopreservation on human sperm transcriptome. Semen samples were collected from 13 normospermic men. Each sample was divided into two aliquots. The total RNA was immediately extracted from one aliquot. The second aliquot was frozen and total RNA was extracted after a week of storage in liquid nitrogen. The RNA samples were randomized in four pools, each of six donors, and analyzed by microarrays. The paired Significance Analysis of Microarray was performed. We found 219 lower abundant transcripts and 28 higher abundant transcripts in cryopreserved sperm than fresh sperm. The gene ontology analysis disclosed that cryopreservation alters transcripts of pathways important for fertility (i.e., spermatogenesis, sperm motility, mitochondria function, fertilization, calcium homeostasis, cell differentiation, and early embryo development), although the increase of some transcripts involved in immune response can compensate for the harmful effects of freezing.

Machine Learning Methods for Gene Selection in Uveal Melanoma.

Uveal melanoma (UM) is the most common primary intraocular malignancy with a limited five-year survival for metastatic patients. Limited therapeutic treatments are currently available for metastatic disease, even if the genomics of this tumor has been deeply studied using next-generation sequencing (NGS) and functional experiments. The profound knowledge of the molecular features that characterize this tumor has not led to the development of efficacious therapies, and the survival of metastatic patients has not changed for decades. Several bioinformatics methods have been applied to mine NGS tumor data in order to unveil tumor biology and detect possible molecular targets for new therapies. Each application can be single domain based while others are more focused on data integration from multiple genomics domains (as gene expression and methylation data). Examples of single domain approaches include differentially expressed gene (DEG) analysis on gene expression data with statistical methods such as SAM (significance analysis of microarray) or gene prioritization with complex algorithms such as deep learning. Data fusion or integration methods merge multiple domains of information to define new clusters of patients or to detect relevant genes, according to multiple NGS data. In this work, we compare different strategies to detect relevant genes for metastatic disease prediction in the TCGA uveal melanoma (UVM) dataset. Detected targets are validated with multi-gene score analysis on a larger UM microarray dataset.

Interdependence of Molecular Lesions That Drive Uveal Melanoma Metastasis.

The metastatic risk of uveal melanoma (UM) is defined by a limited number of molecular lesions, somatic mutations (SF3B1 and BAP1), and copy number alterations (CNA): monosomy of chromosome 3 (M3), chr8q gain (8q), chr6p gain (6p), yet the sequence of events is not clear. We analyzed data from three datasets (TCGA-UVM, GSE27831, GSE51880) with information regarding M3, 8q, 6p, SF3B1, and BAP1 status. We confirm that BAP1 mutations are always associated with M3 in high-risk patients. All other features (6p, 8q, M3, SF3B1 mutation) were present independently from each other. Chr8q gain was frequently associated with chr3 disomy. Hierarchical clustering of gene expression data of samples with different binary combinations of aggressivity factors shows that patients with 8q|M3, BAP1|M3 form one cluster enriched in samples that developed metastases. Patients with 6p combined with either 8q or SF3B1 are mainly represented in the other, low-risk cluster. Several gene expression events that show a non-significant association with outcome when considering single features become significant when analyzing combinations of risk features indicating additive action. The independence of risk factors is consistent with a random risk model of UM metastasis without an obligatory sequence.

Clonal Extinction Drives Tumorigenesis.

Before a tumor is diagnosed and surgically removed, it has been growing for many months or even years [...].

Targeting NOTCH1 in combination with antimetabolite drugs prolongs life span in relapsed pediatric and adult T-acute lymphoblastic leukemia xenografts.

T-cell acute lymphoblastic leukemia (T-ALL) is a hematologic tumor, characterized by several genetic alterations, that constitutes 15% of pediatric and 25% of adult ALL. While with current therapeutic protocols children and adults' overall survival (OS) rates reach 85-90% and 40-50%, respectively, the outcome for both pediatric and adult T-ALL patients that relapse or are refractory to induction therapy, remains extremely poor, achieving around 25% OS for both patient groups. About 60% of T-ALL patients show increased NOTCH1 activity, due to activating NOTCH1 mutations or alterations in its ubiquitin ligase FBXW7. NOTCH signaling has been shown to contribute to chemotherapy resistance in some tumor models. Hence, targeting the NOTCH1 signaling pathway may be an effective option to overcome relapsed and refractory T-ALL.Here, we focused on the therapeutic activity of the NOTCH1-specific monoclonal antibody OMP-52M51 in combination either with drugs used during the induction, consolidation, or maintenance phase in mice xenografts established from pediatric and adult relapsed NOTCH1 mutated T-ALL samples. Interestingly, from RNAseq data we observed that anti-NOTCH1 treatment in vivo affects the purine metabolic pathway. In agreement, both in vitro and in vivo, the greatest effect on leukemia growth reduction was achieved by anti-NOTCH1 therapy in combination with antimetabolite drugs. This result was further corroborated by the longer life span of mice treated with the anti-NOTCH1 in combination with antimetabolites, indicating a novel Notch-targeted therapeutic approach that could ameliorate pediatric and adult T-ALL patients outcome with relapse disease for whom so far, no other therapeutic options are available.

Genes selection using deep learning and explainable artificial intelligence for chronic lymphocytic leukemia predicting the need and time to therapy.

Analyzing gene expression profiles (GEP) through artificial intelligence provides meaningful insight into cancer disease. This study introduces DeepSHAP Autoencoder Filter for Genes Selection (DSAF-GS), a novel deep learning and explainable artificial intelligence-based approach for feature selection in genomics-scale data. DSAF-GS exploits the autoencoder's reconstruction capabilities without changing the original feature space, enhancing the interpretation of the results. Explainable artificial intelligence is then used to select the informative genes for chronic lymphocytic leukemia prognosis of 217 cases from a GEP database comprising roughly 20,000 genes. The model for prognosis prediction achieved an accuracy of 86.4%, a sensitivity of 85.0%, and a specificity of 87.5%. According to the proposed approach, predictions were strongly influenced by CEACAM19 and PIGP, moderately influenced by MKL1 and GNE, and poorly influenced by other genes. The 10 most influential genes were selected for further analysis. Among them, FADD, FIBP, FIBP, GNE, IGF1R, MKL1, PIGP, and SLC39A6 were identified in the Reactome pathway database as involved in signal transduction, transcription, protein metabolism, immune system, cell cycle, and apoptosis. Moreover, according to the network model of the 3D protein-protein interaction (PPI) explored using the NetworkAnalyst tool, FADD, FIBP, IGF1R, QTRT1, GNE, SLC39A6, and MKL1 appear coupled into a complex network. Finally, all 10 selected genes showed a predictive power on time to first treatment (TTFT) in univariate analyses on a basic prognostic model including IGHV mutational status, del(11q) and del(17p), NOTCH1 mutations, ß2-microglobulin, Rai stage, and B-lymphocytosis known to predict TTFT in CLL. However, only IGF1R [hazard ratio (HR) 1.41, 95% CI 1.08-1.84, P=0.013), COL28A1 (HR 0.32, 95% CI 0.10-0.97, P=0.045), and QTRT1 (HR 7.73, 95% CI 2.48-24.04, P<0.001) genes were significantly associated with TTFT in multivariable analyses when combined with the prognostic factors of the basic model, ultimately increasing the Harrell's c-index and the explained variation to 78.6% (versus 76.5% of the basic prognostic model) and 52.6% (versus 42.2% of the basic prognostic model), respectively. Also, the goodness of model fit was enhanced (χ2 = 20.1, P=0.002), indicating its improved performance above the basic prognostic model. In conclusion, DSAF-GS identified a group of significant genes for CLL prognosis, suggesting future directions for bio-molecular research.

Guadecitabine increases response to combined anti-CTLA-4 and anti-PD-1 treatment in mouse melanoma in vivo by controlling T-cells, myeloid derived suppressor and NK cells.

BACKGROUND: The combination of Programmed Cell Death 1 (PD-1) and Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) blockade has dramatically improved the overall survival rate for malignant melanoma. Immune checkpoint blockers (ICBs) limit the tumor's immune escape yet only for approximately a third of all tumors and, in most cases, for a limited amount of time. Several approaches to overcome resistance to ICBs are being investigated among which the addition of epigenetic drugs that are expected to act on both immune and tumor cells. Guadecitabine, a dinucleotide prodrug of a decitabine linked via phosphodiester bond to a guanosine, showed promising results in the phase-1 clinical trial, NIBIT-M4 (NCT02608437). METHODS: We used the syngeneic B16F10 murine melanoma model to study the effects of immune checkpoint blocking antibodies against CTLA-4 and PD-1 in combination, with and without the addition of Guadecitabine. We comprehensively characterized the tumor's and the host's responses under different treatments by flow cytometry, multiplex immunofluorescence and methylation analysis. RESULTS: In combination with ICBs, Guadecitabine significantly reduced subcutaneous tumor growth as well as metastases formation compared to ICBs and Guadecitabine treatment. In particular, Guadecitabine greatly enhanced the efficacy of combined ICBs by increasing effector memory CD8+ T cells, inducing effector NK cells in the spleen and reducing tumor infiltrating regulatory T cells and myeloid derived suppressor cells (MDSC), in the tumor microenvironment (TME). Guadecitabine in association with ICBs increased serum levels of IFN-γ and IFN-γ-induced chemokines with anti-angiogenic activity. Guadecitabine led to a general DNA-demethylation, in particular of sites of intermediate methylation levels. CONCLUSIONS: These results indicate Guadecitabine as a promising epigenetic drug to be added to ICBs therapy.

Cerivastatin Synergizes with Trametinib and Enhances Its Efficacy in the Therapy of Uveal Melanoma.

BACKGROUND: Metastatic uveal melanoma (MUM) is a highly aggressive, therapy-resistant disease. Driver mutations in Gα-proteins GNAQ and GNA11 activate MAP-kinase and YAP/TAZ pathways of oncogenic signalling. MAP-kinase and MEK-inhibitors do not significantly block MUM progression, likely due to persisting YAP/TAZ signalling. Statins inhibit YAP/TAZ activation by blocking the mevalonate pathway, geranyl-geranylation, and subcellular localisation of the Rho-GTPase. We investigated drugs that affect the YAP/TAZ pathway, valproic acid, verteporfin and statins, in combination with MEK-inhibitor trametinib. METHODS: We established IC50 values of the individual drugs and monitored the effects of their combinations in terms of proliferation. We selected trametinib and cerivastatin for evaluation of cell cycle and apoptosis. Synergism was detected using isobologram and Chou-Talalay analyses. The most synergistic combination was tested in vivo. RESULTS: Synergistic concentrations of trametinib and cerivastatin induced a massive arrest of proliferation and cell cycle and enhanced apoptosis, particularly in the monosomic, BAP1-mutated UPMM3 cell line. The combined treatment reduced ERK and AKT phosphorylation, increased the inactive, cytoplasmatic form of YAP and significantly impaired the growth of UM cells with monosomy of chromosome 3 in NSG mice. CONCLUSION: Statins can potentiate the efficacy of MEK inhibitors in the therapy of UM.

Evaluation and Comparison of Multi-Omics Data Integration Methods for Subtyping of Cutaneous Melanoma.

There is a growing number of multi-domain genomic datasets for human tumors. Multi-domain data are usually interpreted after separately analyzing single-domain data and integrating the results post hoc. Data fusion techniques allow for the real integration of multi-domain data to ideally improve the tumor classification results for the prognosis and prediction of response to therapy. We have previously described the joint singular value decomposition (jSVD) technique as a means of data fusion. Here, we report on the development of these methods in open source code based on R and Python and on the application of these data fusion methods. The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) dataset was used as a benchmark to evaluate the potential of the data fusion approaches to improve molecular classification of cancers in a clinically relevant manner. Our data show that the data fusion approach does not generate classification results superior to those obtained using single-domain data. Data from different domains are not entirely independent from each other, and molecular classes are characterized by features that penetrate different domains. Data fusion techniques might be better suited for response prediction, where they could contribute to the identification of predictive features in a domain-independent manner to be used as biomarkers.

Spontaneous NLRP3 inflammasome-driven IL-1-ß secretion is induced in severe COVID-19 patients and responds to anakinra treatment.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may result in a severe pneumonia associated with elevation of blood inflammatory parameters, reminiscent of cytokine storm syndrome. Steroidal anti-inflammatory therapies have shown efficacy in reducing mortality in critically ill patients; however, the mechanisms by which SARS-CoV-2 triggers such an extensive inflammation remain unexplained. OBJECTIVES: To dissect the mechanisms underlying SARS-CoV-2-associated inflammation in patients with severe coronavirus disease 2019 (COVID-19), we studied the role of IL-1ß, a pivotal cytokine driving inflammatory phenotypes, whose maturation and secretion are regulated by inflammasomes. METHODS: We analyzed nod-like receptor protein 3 pathway activation by means of confocal microscopy, plasma cytokine measurement, cytokine secretion following in vitro stimulation of blood circulating monocytes, and whole-blood RNA sequencing. The role of open reading frame 3a SARS-CoV-2 protein was assessed by confocal microscopy analysis following nucleofection of a monocytic cell line. RESULTS: We found that circulating monocytes from patients with COVID-19 display ASC (adaptor molecule apoptotic speck like protein-containing a CARD) specks that colocalize with nod-like receptor protein 3 inflammasome and spontaneously secrete IL-1ß in vitro. This spontaneous activation reverts following patient's treatment with the IL-1 receptor antagonist anakinra. Transfection of a monocytic cell line with cDNA coding for the ORF3a SARS-CoV-2 protein resulted in ASC speck formation. CONCLUSIONS: These results provide further evidence that IL-1ß targeting could represent an effective strategy in this disease and suggest a mechanistic explanation for the strong inflammatory manifestations associated with COVID-19.

In uveal melanoma Gα-protein GNA11 mutations convey a shorter disease-specific survival and are more strongly associated with loss of BAP1 and chromosomal alterations than Gα-protein GNAQ mutations.

BACKGROUND AND AIM OF THE STUDY: Mutations in the Gα-genes GNAQ and GNA11 are found in 85-90% of uveal melanomas (UM). Aim of the study is to understand whether the mutations in both genes differentially affect tumor characteristics and outcome and if so, to identify potential mechanisms. METHODS: We analyzed the association between GNAQ and GNA11 mutations with disease-specific survival, gene expression profiles, and cytogenetic alterations in 219 UMs. We used tandem-affinity-purification, mass spectrometry and immunoprecipitation to identify protein interaction partners of the two G-proteins and analyzed their impact on DNA-methylation. RESULTS: GNA11 mutation was associated with: i) an increased frequency of loss of BRCA1-associated protein 1 (BAP1) expression (p = 0.0005), ii) monosomy of chromosome 3 (p < 0.001), iii) amplification of chr8q (p = 0.038), iv) the combination of the latter two (p = 0.0002), and inversely with v) chr6p gain (p = 0.003). Our analysis also showed a shorter disease-specific survival of GNA11-mutated cases as compared to those carrying a GNAQ mutation (HR = 1.97 [95%CI 1.12-3.46], p = 0.02). GNAQ and GNA11 encoded G-proteins have different protein interaction partners. Specifically, the Tet Methylcytosine Dioxygenase 2 (TET2), a protein that is involved in DNA demethylation, physically interacts with the GNAQ protein but not with GNA11, as confirmed by immunoprecipitation analyses. High-risk UM cases show a clearly different DNA-methylation pattern, suggesting that a different regulation of DNA methylation by the two G-proteins might convey a different risk of progression. CONCLUSIONS: GNA11 mutated uveal melanoma has worse prognosis and is associated with high risk cytogenetic, mutational and molecular tumor characteristics that might be determined at least in part by differential DNA-methylation.

Uveal Melanoma Metastasis.

Uveal melanoma (UM) is characterized by relatively few, highly incident molecular alterations and their association with metastatic risk is deeply understood. Nevertheless, this knowledge has so far not led to innovative therapies for the successful treatment of UM metastases or for adjuvant therapy, leaving survival after diagnosis of metastatic UM almost unaltered in decades. The driver mutations of UM, mainly in the G-protein genes GNAQ and GNA11, activate the MAP-kinase pathway as well as the YAP/TAZ pathway. At present, there are no drugs that target the latter and this likely explains the failure of mitogen activated kinase kinase inhibitors. Immune checkpoint blockers, despite the game changing effect in cutaneous melanoma (CM), show only limited effects in UM probably because of the low mutational burden of 0.5 per megabase and the unavailability of antibodies targeting the main immune checkpoint active in UM. The highly pro-tumorigenic microenvironment of UM also contributes to therapy resistance. However, T-cell redirection by a soluble T-cell receptor that is fused to an anti-CD3 single-chain variable fragment, local, liver specific therapy, new immune checkpoint blockers, and YAP/TAZ specific drugs give new hope to repeating the success of innovative therapy obtained for CM.

Identification of a Prognostic Signature Based on the Expression of Genes Related to the Insulin Pathway in Early Breast Cancer.

INTRODUCTION: Insulin and the insulin-like growth factor (IGF) family play a key role in breast cancer (BC). OBJECTIVE: In this study, we evaluated on a genomic scale the potential prognostic value of insulin signaling in early BC. METHODS: Candidate genes were selected from the published literature and gene expression profiling experiments. Three publicly available BC datasets, containing gene expression data on 502 cases, were used to test the prognostic ability of the score. The gene signature was developed on GSE1456, containing microarray data from 159 patients, split into a training set (102 breast tumors) and a validation set (n = 57). GSE3494 and GSE2990 (350 patients) were used for external validation. Univariate Mann-Whitney test was used to identify genes differentially expressed between relapsed and nonrelapsed patients. Expression of genes significantly correlated with relapse was combined in a linear score. Patients were classified as low or high risk with respect to the median value. RESULTS: On the training set, 15 genes turned out to be differentially expressed: 8-year disease-free survival (DFS) was 51 and 91% in the high- and low-risk group (p < 0.001), respectively. In the validation set, DFS was 97 and 54% (p = 0.009), respectively. External validation: 8-year DFS was 72 and 61%, respectively, in GSE3494 (p = 0.03) and 74 and 55% in GSE2990 (p = 0.03). By multivariate analyses, the insulin signature was significantly associated with DFS, independently of age, hormone receptor status, nodal status, and grade. CONCLUSIONS: Our findings indicate that the insulin pathway is involved in BC prognosis at a genomic level and provide a window of selectivity for preventive and treatment strategies targeting the insulin/IGF pathway in BC patients.

How to Make Immunotherapy an Effective Therapeutic Choice for Uveal Melanoma.

Uveal melanoma (UM), though a rare form of melanoma, is the most common intraocular tumor in adults. Conventional therapies of primary tumors lead to an excellent local control, but 50% of patients develop metastases, in most cases with lethal outcome. Somatic driver mutations that act on the MAP-kinase pathway have been identified, yet targeted therapies show little efficacy in the clinics. No drugs are currently available for the G protein alpha subunitsGNAQ and GNA11, which are the most frequent driver mutations in UM. Drugs targeting the YAP-TAZ pathway that is also activated in UM, the tumor-suppressor gene BRCA1 Associated Protein 1 (BAP1) and the Splicing Factor 3b Subunit 1 gene (SF3B1) whose mutations are associated with metastatic risk, have not been developed yet. Immunotherapy is highly effective in cutaneous melanoma but yields only poor results in the treatment of UM: anti-PD-1 and anti-CTLA-4 blocking antibodies did not meet the expectations except for isolated cases. Here, we discuss how the improved knowledge of the tumor microenvironment and of the cross-talk between tumor and immune cells could help to reshape anti-tumor immune responses to overcome the intrinsic resistance to immune checkpoint blockers of UM. We critically review the dogma of low mutational load, the induction of immune-suppressive cells, and the expression of alternative immune checkpoint molecules. We argue that immunotherapy might still be an option for the treatment of UM.

EZH1/2 Inhibitors Favor ILC3 Development from Human HSPC-CD34+ Cells.

The dysregulation of epigenetic modifications has a well-established role in the development and progression of hematological malignancies and of solid tumors. In this context, EZH1/2 inhibitors have been designed to interfere with EZH1/2 enzymes involved in histone methylation (e.g., H3K27me3), leading to tumor growth arrest or the restoration of tumor suppressor gene transcription. However, these compounds also affect normal hematopoiesis, interfering with self-renewal and differentiation of CD34+-Hematopoietic Stem/Progenitor Cells (HSPC), and, in turn, could modulate the generation of potential anti-tumor effector lymphocytes. Given the important role of NK cells in the immune surveillance of tumors, it would be useful to understand whether epigenetic drugs can modulate NK cell differentiation and functional maturation. CD34+-HSPC were cultured in the absence or in the presence of the EZH1/2 inhibitor UNC1999 and EZH2 inhibitor GSK126. Our results show that UNC1999 and GSK126 increased CD56+ cell proliferation compared to the control condition. However, UNC1999 and GSK 126 favored the proliferation of no-cytotoxic CD56+ILC3, according to the early expression of the AHR and ROR-γt transcription factors. Our results describe novel epigenetic mechanisms involved in the modulation of NK cell maturation that may provide new tools for designing NK cell-based immunotherapy.

Potential Onco-Suppressive Role of miR122 and miR144 in Uveal Melanoma through ADAM10 and C-Met Inhibition.

Uveal melanoma (UM) is a rare tumor of the eye that leads to deadly metastases in about half of the patients. ADAM10 correlates with c-Met expression in UM and high levels of both molecules are related to the development of metastases. MiR122 and miR144 modulate ADAM10 and c-Met expression in different settings. We hypothesized a potential onco-suppressive role for miR122 and miR144 through modulation of ADAM10 and c-Met in UM. We analyzed the UM Cancer Genome Atlas data portal (TCGA) dataset, two other cohorts of primary tumors and five human UM cell lines for miR122 and miR144 expression by miR microarray, RT-qPCR, Western blotting, miR transfection and luciferase reporter assay. Our results indicate that miR122 and miR144 are expressed at low levels in the UM cell lines and in the TCGA UM dataset and were down-modulated in a cohort of seven UM samples, compared to normal choroid. Both miR122 and miR144 directly targeted ADAM10 and c-Met. Overexpression of miR122 and miR144 led to reduced expression of ADAM10 and c-Met in the UM cell lines and impaired cell proliferation, migration, cell cycle and shedding of c-Met ecto-domain. Our results show that miR122 and miR144 display an onco-suppressive role in UM through ADAM10 and c-Met modulation.

Combined Replenishment of miR-34a and let-7b by Targeted Nanoparticles Inhibits Tumor Growth in Neuroblastoma Preclinical Models.

Neuroblastoma (NB) tumor substantially contributes to childhood cancer mortality. The design of novel drugs targeted to specific molecular alterations becomes mandatory, especially for high-risk patients burdened by chemoresistant relapse. The dysregulated expression of MYCN, ALK, and LIN28B and the diminished levels of miR-34a and let-7b are oncogenic in NB. Due to the ability of miRNA-mimics to recover the tumor suppression functions of miRNAs underexpressed into cancer cells, safe and efficient nanocarriers selectively targeted to NB cells and tested in clinically relevant mouse models are developed. The technology exploits the nucleic acids negative charges to build coated-cationic liposomes, then functionalized with antibodies against GD2 receptor. The replenishment of miR-34a and let-7b by NB-targeted nanoparticles, individually and more powerfully in combination, significantly reduces cell division, proliferation, neoangiogenesis, tumor growth and burden, and induces apoptosis in orthotopic xenografts and improves mice survival in pseudometastatic models. These functional effects highlight a cooperative down-modulation of MYCN and its down-stream targets, ALK and LIN28B, exerted by miR-34a and let-7b that reactivate regulatory networks leading to a favorable therapeutic response. These findings demonstrate a promising therapeutic efficacy of miR-34a and let-7b combined replacement and support its clinical application as adjuvant therapy for high-risk NB patients.

Dissecting molecular mechanisms of resistance to NOTCH1-targeted therapy in T-cell acute lymphoblastic leukemia xenografts.

Despite substantial progress in treatment of T-cell acute lymphoblastic leukemia (T-ALL), mortality remains relatively high, mainly due to primary or acquired resistance to chemotherapy. Further improvements in survival demand better understanding of T-ALL biology and development of new therapeutic strategies. The Notch pathway has been involved in the pathogenesis of this disease and various therapeutic strategies are currently under development, including selective targeting of NOTCH receptors by inhibitory antibodies. We previously demonstrated that the NOTCH1-specific neutralizing antibody OMP52M51 prolongs survival in TALL patient-derived xenografts bearing NOTCH1/FBW7 mutations. However, acquired resistance to OMP52M51 eventually developed and we used patient-derived xenografts models to investigate this phenomenon. Multi-level molecular characterization of T-ALL cells resistant to NOTCH1 blockade and serial transplantation experiments uncovered heterogeneous types of resistance, not previously reported with other Notch inhibitors. In one model, resistance appeared after 156 days of treatment, it was stable and associated with loss of Notch inhibition, reduced mutational load and acquired NOTCH1 mutations potentially affecting the stability of the heterodimerization domain. Conversely, in another model resistance developed after only 43 days of treatment despite persistent down-regulation of Notch signaling and it was accompanied by modulation of lipid metabolism and reduced surface expression of NOTCH1. Our findings shed light on heterogeneous mechanisms adopted by the tumor to evade NOTCH1 blockade and support clinical implementation of antibody-based target therapy for Notch-addicted tumors.

Secondary Somatic Mutations in G-Protein-Related Pathways and Mutation Signatures in Uveal Melanoma.

BACKGROUND: Uveal melanoma (UM), a rare cancer of the eye, is characterized by initiating mutations in the genes G-protein subunit alpha Q (GNAQ), G-protein subunit alpha 11 (GNA11), cysteinyl leukotriene receptor 2 (CYSLTR2), and phospholipase C beta 4 (PLCB4) and by metastasis-promoting mutations in the genes splicing factor 3B1 (SF3B1), serine and arginine rich splicing factor 2 (SRSF2), and BRCA1-associated protein 1 (BAP1). Here, we tested the hypothesis that additional mutations, though occurring in only a few cases ("secondary drivers"), might influence tumor development. METHODS: We analyzed all the 4125 mutations detected in exome sequencing datasets, comprising a total of 139 Ums, and tested the enrichment of secondary drivers in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that also contained the initiating mutations. We searched for additional mutations in the putative secondary driver gene protein tyrosine kinase 2 beta (PTK2B) and we developed new mutational signatures that explain the mutational pattern observed in UM. RESULTS: Secondary drivers were significantly enriched in KEGG pathways that also contained GNAQ and GNA11, such as the calcium-signaling pathway. Many of the secondary drivers were known cancer driver genes and were strongly associated with metastasis and survival. We identified additional mutations in PTK2B. Sparse dictionary learning allowed for the identification of mutational signatures specific for UM. CONCLUSIONS: A considerable part of rare mutations that occur in addition to known driver mutations are likely to affect tumor development and progression.

Data Fusion Techniques for the Integration of Multi-Domain Genomic Data from Uveal Melanoma.

Uveal melanoma (UM) is a rare cancer that is well characterized at the molecular level. Two to four classes have been identified by the analyses of gene expression (mRNA, ncRNA), DNA copy number, DNA-methylation and somatic mutations yet no factual integration of these data has been reported. We therefore applied novel algorithms for data fusion, joint Singular Value Decomposition (jSVD) and joint Constrained Matrix Factorization (jCMF), as well as similarity network fusion (SNF), for the integration of gene expression, methylation and copy number data that we applied to the Cancer Genome Atlas (TCGA) UM dataset. Variant features that most strongly impact on definition of classes were extracted for biological interpretation of the classes. Data fusion allows for the identification of the two to four classes previously described. Not all of these classes are evident at all levels indicating that integrative analyses add to genomic discrimination power. The classes are also characterized by different frequencies of somatic mutations in putative driver genes (GNAQ, GNA11, SF3B1, BAP1). Innovative data fusion techniques confirm, as expected, the existence of two main types of uveal melanoma mainly characterized by copy number alterations. Subtypes were also confirmed but are somewhat less defined. Data fusion allows for real integration of multi-domain genomic data.