Glioma-Parvovirus Interactions: Molecular Insights and Therapeutic Potential

This work was supported by grants from the Spanish Ministerio de Ciencia e Innovación (SAF2008-03238) and Comunidad de Madrid (S-SAL/0185/2006) to the laboratory of J.M.A.The Centro de Biología Molecular "Severo Ochoa" (CSIC-UAM) is in part supported by an institutional grant from Fundación Ramón Areces.Peer reviewe

From mouse to human: cellular morphometric subtype learned from mouse mammary tumors provides prognostic value in human breast cancer

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.This work was supported by the Department of Defense (DoD)BCRP: BC190820 (J-HM); and the National Cancer Institute (NCI) at the National Institutes of Health (NIH): R01CA184476 (HC). Lawrence Berkeley National Laboratory (LBNL) is a multi-program national laboratory operated by the University of California for the DOE under contract DE AC02-05CH1123

Evolutionary origins of metabolic reprogramming in cancer

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. These changes are not specific to tumors but also take place during the physiological growth of tissues. Indeed, the cellular and tissue mechanisms present in the tumor have their physiological counterpart in the repair of tissue lesions and wound healing. These molecular mechanisms have been acquired during metazoan evolution, first to eliminate the infection of the tissue injury, then to enter an effective regenerative phase. Cancer itself could be considered a phenomenon of antagonistic pleiotropy of the genes involved in effective tissue repair. Cancer and tissue repair are complex traits that share many intermediate phenotypes at the molecular, cellular, and tissue levels, and all of these are integrated within a Systems Biology structure. Complex traits are influenced by a multitude of common genes, each with a weak effect. This polygenic component of complex traits is mainly unknown and so makes up part of the missing heritability. Here, we try to integrate these different perspectives from the point of view of the metabolic changes observed in cancer.This work was supported in JPL’s lab by Grant PID2020-118527RB-I00 funded by MCIN/AEI/10.13039/501100011039; Grant PDC2021-121735-I00 funded by MCIN/AEI/10.13039/501100011039 and by the “European Union Next Generation EU/PRTR.”, the Regional Government of Castile and León (CSI234P18 and CSI144P20). SCLl was the recipient of a Ramón y Cajal research contract from the Spanish Ministry of Economy and Competitiveness and was supported by grant RTI2018-094130-B-100 funded by MCIN/AEI/10.13039/501100011039 and by “ERDF A way of making Europe.” RCC and AJN are funded by fellowships from the Spanish Regional Government of Castile and León. NGS is a recipient of an FPU fellowship (MINECO/FEDER). MJPB is funded by grant PID2020-118527RB-I00 funded by MCIN/AEI/10.13039/501100011039. J.C. is partially supported by grant GRS2139/A/20 (Gerencia Regional de Salud de Castilla y León) and by the Instituto de Salud Carlos III (PI18/00587 and PI21/01207), co-financed by FEDER funds, and by the “Programa de Intensificación” of the ISCIII, grant number INT20/00074. We thank Phil Mason for English language support

Image_1_From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.pdf [Dataset]

Supplementary Figure 1. Representative examples of 256 CMB learned from Trp53-null mouse mammary tumors. Supplementary Figure 2. Consensus clustering on the Trp53-null mouse mammary tumors with different number of clusters (K) and the corresponding Kaplan–Meier curves for tumor growth. A-B. Consensus matrix with 3 and 4 clusters, respectively; C-D Kaplan–Meier curves for 3 and 4 subtypes, respectively. Supplementary Figure 3. Representative example of CMB_13 (A), CMB_249 (D), CMB_120 (G), and CMB_105 (J), and their significant and consistent difference in relative abundance between metastasis ground truth (B, E, H, and K) and low/high metastasis risk groups (i.e., LMRG and HMRG defined by CMS-1 and CMS-2, respectively) (C, F, I, and L). Supplementary Figure 4. BRCA patient subtypes in triple-negative (TNBC) and non-triplenegative (Non-TNBC) groups. A-B. KM curves for representative CMBs show consistent and significant impact on OS in Non-TNBC and TNBC groups, respectively; C. Subtype-specific patients in TCGA-BRCA cohort form distinct clusters in patient-level cellular morphometric context space in Non-TNBC and TNBC groups, respectively; D. Subtype-specific patients in TCGA-BRCA cohort show significant difference in survival in Non-TNBC and TNBC groups, respectively. Supplementary Figure 5. A. BRCA patient heatmap with mouse CMS model on the TCGABRCA cohort; B. BRCA patient heatmap with BC-CMS model on the TCGA-BRCA cohort. C. ROC curves for the prediction of 5-,10-, and 20-year overall survival of BRCA patients using all significant prognostic factors as listed in E; D. Comparison of predictive power between BC-CMS model and mouse CMS model using bootstrapping strategy with 80% sampling rate and 1000 iterations; E. Similar to patient subtype from BC-CMS model as shown in Figure 3F, patient subtype directly predicted from the mouse CMS model is also a significant and independent prognostic factor in the TCGA-BRCA cohort. Supplementary Figure 6. BC-CMS in triple-negative (TNBC) and non-triple-negative (NonTNBC) groups in the TCGA-BRCA cohort show significant difference in tumor microenvironments.Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.Peer reviewe

Table_4_From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.docx [Dataset]

Supplementary Table 4. Clinical characteristics of patients in TCGA-BRCA cohortMouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.Peer reviewe

An Off-Target Nucleostemin RNAi Inhibits Growth in Human Glioblastoma-Derived Cancer Stem Cells

Glioblastomas (GBM) may contain a variable proportion of active cancer stem cells (CSCs) capable of self-renewal, of aggregating into CD133+ neurospheres, and to develop intracranial tumors that phenocopy the original ones. We hypothesized that nucleostemin may contribute to cancer stem cell biology as these cells share characteristics with normal stem cells. Here we report that nucleostemin is expressed in GBM-CSCs isolated from patient samples, and that its expression, conversely to what it has been described for ordinary stem cells, does not disappear when cells are differentiated. The significance of nucleostemin expression in CSCs was addressed by targeting the corresponding mRNA using lentivirally transduced short hairpin RNA (shRNA). In doing so, we found an off-target nucleostemin RNAi (shRNA22) that abolishes proliferation and induces apoptosis in GBM-CSCs. Furthermore, in the presence of shRNA22, GBM-CSCs failed to form neurospheres in vitro or grow on soft agar. When these cells are xenotransplanted into the brains of nude rats, tumor development is significantly delayed. Attempts were made to identify the primary target/s of shRNA22, suggesting a transcription factor involved in one of the MAP-kinases signaling-pathways or multiple targets. The use of this shRNA may contribute to develop new therapeutic approaches for this incurable type of brain tumor

Combination Therapy of Intraperitoneal Rapamycin and Convection- Enhanced Delivery of Nanoliposomal CPT-11 in Rodent Orthotopic Brain Tumor Xenografts.

BACKGROUND: Glioblastoma multiforme (GBM) is the most malignant histological type of glioma. It exhibits an extremely aggressive action including invasion of large zones of brain parenchyma. Even after the application of surgery, radio and chemotherapy, the effect and survival for patients with GBM continue to be very poor. The PI3K/AKT/mTOR is a key pathway in the regulation of the proliferation of cancer cells. This is the reason to consider the mTOR inhibitors such as rapamycin analogs as an encouraging therapy for malignant glioma, but current investigations suggest that single inhibition of mTOR may be insufficient. For this reason, there is a need for the use of more than one agent rationally combined. METHODS: In this study, we have evaluated the therapeutic potential of the combination of two different drugs: intraperitoneal rapamycin and convection enhanced delivery of nanoliposomes containing the topoisomerase I inhibitor CPT-11. The effect was analyzed by flow cytometry, cell growth, immunocytochemistry and immunohistochemistry, and rodent orthotopic xenograft survival analysis. RESULTS: The combination presented remarkable efficacy in a survival study. We present an increase in survival of 6-fold in xenotransplanted animals without rise in toxicity. CONCLUSION: In summary, we propose a very powerful new combination therapy for glioma

Circular troughs in tessera terrain on Venus: Morphometry, structural analysis and possible formation model

Detailed observations on Venus tessera terrain reveal the presence of tectonic structures, characterized by a subcircular trough, limiting an internal area with the average elevation of the surrounding terrain. We named this new type of tectonic structures Circular Troughs. Here we show the results of a morphometric study and a structural analysis based on data from 609 structures obtained through a global survey on Venus. Circular Troughs have an average outer radius of 12 ± 4.4 km, an average inner radius of 9 ± 3.9 km and an average trough width of 3 ± 1.2 km. A comparison with other tectonovolcanic structures on Venus shows that they are smaller and their size-distribution is more bounded. Although Circular Troughs show morphological similarities with some corona types, their size distribution is significantly smaller than coronae indicating a shallower geodynamic formation process. A shape preferred orientation analysis shows that Circular Troughs in Western Ovda are elongated parallel to long-wavelength tessera folds indicating that they are at least partially deformed by them, thus Circular Trough formation predates or it is contemporary with folding. A detailed structural analysis suggests that they were generated by small scale diapirism exclusively developed in tessera terrain. Several hypotheses could explain this small scale diapirism inside tessera terrain including volcanically driven compositional diapirism, small scale thermal diapirism or compositional cold diapirism, considering that the probable dessication of an ancient ocean would have generated evaporitic deposits in the past later buried by younger geological units

Glioma-Parvovirus Interactions: Molecular Insights and Therapeutic Potential

This work was supported by grants from the Spanish Ministerio de Ciencia e Innovación (SAF2008-03238) and Comunidad de Madrid (S-SAL/0185/2006) to the laboratory of J.M.A.The Centro de Biología Molecular "Severo Ochoa" (CSIC-UAM) is in part supported by an institutional grant from Fundación Ramón Areces.Peer reviewe

Midkine signaling maintains the self-renewal and tumorigenic capacity of glioma initiating cells

Glioblastoma (GBM) is one of the most aggressive forms of cancer. It has been proposed that the presence within these tumors of a population of cells with stem-like features termed Glioma Initiating Cells (GICs) is responsible for the relapses that take place in the patients with this disease. Targeting this cell population is therefore an issue of great therapeutic interest in neuro-oncology. We had previously found that the neurotrophic factor MIDKINE (MDK) promotes resistance to glioma cell death. The main objective of this work is therefore investigating the role of MDK in the regulation of GICs. Methods: Assays of gene and protein expression, self-renewal capacity, autophagy and apoptosis in cultures of GICs derived from GBM samples subjected to different treatments. Analysis of the growth of GICs-derived xenografts generated in mice upon blockade of the MDK and its receptor the ALK receptor tyrosine kinase (ALK) upon exposure to different treatments. Results: Genetic or pharmacological inhibition of MDK or ALK decreases the self-renewal and tumorigenic capacity of GICs via the autophagic degradation of the transcription factor SOX9. Blockade of the MDK/ALK axis in combination with temozolomide depletes the population of GICs in vitro and has a potent anticancer activity in xenografts derived from GICs. Conclusions: The MDK/ALK axis regulates the self-renewal capacity of GICs by controlling the autophagic degradation of the transcription factor SOX9. Inhibition of the MDK/ALK axis may be a therapeutic strategy to target GICs in GBM patients.This work has been funded by the PI18/00442 grant integrated into the State Plan for R & D + I 2017-2020 and funded by the Instituto de Salud Carlos III (ISCIII) and confounded by the European Regional Development Fund (ERDF), “A way to make Europe” and by grants from ISCIII and ERDF, a way to make Europe (PS09/01401; PI12/02248 and PI15/00339 to GV, PI16/01580 to AM, PI16/01278 to JMS) by Ministerio de Economía y Competitividad (grant SAF2015-65175-R/ERDF to PSG), by Fundación Mutua Madrileña (AP101042012 to GV), “Fundació La Marató de TV3” (20134031 to GV), Voices Against Brain Cancer (US) (to GV), and donations by The Medical Cannabis Bike Tour Foundation (The Netherlands to GV) and Jeff Ditchfield (to GV). G Velasco's group is part of the COST Action CA15138 (Transautophagy). Israel López-Valero was supported by a predoctoral P-FIS contract from ISCIII, Cristina Sáiz was supported by a “Juan de la Cierva formación” contract of the Spanish Ministry of Economy and Competitiveness, Ander Matheu was recipient of a Miguel Servet contract (CP16/00039) from ISCIII. Work in JM Sepulveda group is supported by a grant from “Asociación Española contra el Cancer” (AECC) (GCTRA16015SEDA). Part of the work at G Velasco laboratory was funded by LYRAMID and Pfizer.S