Osteosarcoma: Cells-of-Origin, Cancer stem cells, and targeted therapies

Osteosarcoma (OS) is the most common type of primary solid tumor that develops in bone. Although standard chemotherapy has significantly improved long-term survival over the past few decades, the outcome for those patients with metastatic or recurrent OS remains dismally poor and, therefore, novel agents and treatment regimens are urgently required. A hypothesis to explain the resistance of OS to chemotherapy is the existence of drug resistant CSCs with progenitor properties that are responsible of tumor relapses and metastasis. These subpopulations of CSCs commonly emerge during tumor evolution from the cell-of-origin, which are the normal cells that acquire the first cancer-promotingmutations to initiate tumor formation. In OS, several cell types along the osteogenic lineage have been proposed as cell-of-origin. Both the cell-of-origin and their derived CSC subpopulations are highly influenced by environmental and epigenetic factors and, therefore, targeting the OS-CSC environment and niche is the rationale for many recently postulated therapies. Likewise, some strategies for targeting CSC-associated signaling pathways have already been tested in both preclinical and clinical settings. This review recapitulates current OS cell-of-origin models, the properties of the OS-CSC and its niche, and potential new therapies able to target OS-CSCs

Estimating Stand and Fire-Related Surface and Canopy Fuel Variables in Pine Stands Using Low-Density Airborne and Single-Scan Terrestrial Laser Scanning Data

In this study, we used data from a thinning trial conducted on 34 different sites and 102 sample plots established in pure and even-aged Pinus radiata and Pinus pinaster stands, to test the potential use of low-density airborne laser scanning (ALS) metrics and terrestrial laser scanning (TLS) metrics to provide accurate estimates of variables related to surface and canopy fires. An exhaustive field inventory was carried out in each plot to estimate the main stand variables and the main variables related to fire hazard: surface fuel loads by layers, fuel strata gap, surface fuel height, stand mean height, canopy base height, canopy fuel load and canopy bulk density. In addition, the point clouds from low-density ALS and single-scan TLS of each sample plot were used to calculate metrics related to the vertical and horizontal distribution of forest fuels. The comparative performance of the following three non-parametric machine learning techniques used to estimate the main stand- and fire-related variables from those metrics was evaluated: (i) multivariate adaptive regression splines (MARS), (ii) support vector machine (SVM), and (iii) random forest (RF). The selection of the best modeling approach was based on a comparison of the root mean square error (RMSE), obtained by optimizing the parameters of each technique and performing cross-validation. Overall, the best results were obtained with the MARS techniques for data from both sensors. The TLS data provided the best results for variables associated with the internal characteristics of canopy structure and understory fuel but were less reliable for estimating variables associated with the upper canopy, due to occlusion by mid-canopy foliage. The combination of ALS and TLS metrics improved the accuracy of estimates for all variables analyzed, except the height and the biomass of the understory shrubs. The variability demonstrated by the combined use of both types of metrics ranged from 43.11% for the biomass of duff litter layers to 94.25% for dominant height. The results suggest that the combination of machine learning techniques and metrics derived from low-density ALS data, drawn from a single-scan TLS or a combination of both metrics, may represent a promising alternative to traditional field inventories for obtaining valuable information about surface and canopy fuel variables at large scalesinfo:eu-repo/semantics/publishedVersio

Urinary Cytokines Reflect Renal Inflammation in Acute Tubulointerstitial Nephritis: A Multiplex Bead-Based Assay Assessment

Background: Acute tubulointerstitial nephritis (ATIN) diagnosis lays on histological assessment through a kidney biopsy, given the absence of accurate non-invasive biomarkers. The aim of this study was to evaluate the accuracy of different urinary inflammation-related cytokines for the diagnostic of ATIN and its distinction from acute tubular necrosis (ATN). Methods: We included 33 patients (ATIN (n = 21), ATN (n = 12)), and 6 healthy controls (HC). We determined the urinary levels of 10 inflammation-related cytokines using a multiplex bead-based Luminex assay at the time of biopsy and after therapy, and registered main clinical, analytical and histological data. Results: At the time of biopsy, urinary levels of I-TAC/CXCL11, CXCL10, IL-6, TNF alpha and MCP-1 were significantly higher in ATIN compared to HC. A positive correlation between the extent of the tubulointerstitial cellular infiltrates in kidney biopsies and the urinary concentration of I-TAC/CXCL11, MIG/CXCL9, CXCL10, IL17, IFN alpha, MCP1 and EGF was observed. Notably, I-TAC/CXCL11, IL-6 and MCP-1 were significantly higher in ATIN than in ATN, with I-TAC/CXCL11 as the best discriminative classifier AUC (0.77, 95% CI 0.57-0.95, p = 0.02). A combinatory model of these three urinary cytokines increased the accuracy in the distinction of ATIN/ATN compared to the individual biomarkers. The best model resulted when combining the three cytokines with blood eosinophil and urinary leukocyte counts (LR = 9.76). Follow-up samples from 11ATIN patients showed a significant decrease in I-TAC/CXCL11, MIG/CXCL9 and CXCL10 levels. Conclusions: Urinary I-TAC/CXCL11, CXCL10, IL6 and MCP-1 levels accurately distinguish patients developing ATIN from ATN and healthy individuals and may serve as novel non-invasive biomarkers in this disease

SOX2 Expression and Transcriptional Activity Identifies a Subpopulation of Cancer Stem Cells in Sarcoma with Prognostic Implications

Stemness in sarcomas is coordinated by the expression of pluripotency factors, like SOX2, in cancer stem cells (CSC). The role of SOX2 in tumor initiation and progression has been well characterized in osteosarcoma. However, the pro-tumorigenic features of SOX2 have been scarcely investigated in other sarcoma subtypes. Here, we show that SOX2 depletion dramatically reduced the ability of undifferentiated pleomorphic sarcoma (UPS) cells to form tumorspheres and to initiate tumor growth. Conversely, SOX2 overexpression resulted in increased in vivo tumorigenicity. Moreover, using a reporter system (SORE6) which allows to monitor viable cells expressing SOX2 and/or OCT4, we found that SORE6+ cells were significantly more tumorigenic than the SORE6- subpopulation. In agreement with this findings, SOX2 expression in sarcoma patients was associated to tumor grade, differentiation, invasive potential and lower patient survival. Finally, we studied the effect of a panel of anti-tumor drugs on the SORE6+ cells of the UPS model and patient-derived chondrosarcoma lines. We found that the mithramycin analogue EC-8042 was the most efficient in reducing SORE6+ cells in vitro and in vivo. Overall, this study demonstrates that SOX2 is a pro-tumorigenic factor with prognostic potential in sarcoma. Moreover, SORE6 transcriptional activity is a bona fide CSC marker in sarcoma and constitutes an excellent biomarker for evaluating the efficacy of anti-tumor treatments on CSC subpopulations.This work was supported by the Agencia Estatal de Investigación (AEI) [MINECO/Fondo Europeo de Desarrollo Regional (FEDER) (SAF-2016-75286-R to R.R.), ISC III/FEDER (Miguel Servet Program CPII16/00049 to R.R., Sara Borrell Program CD16/00103 to S.T.M. and PI16/00280 and PI19/00560 to J.M.G-P) and Consorcio CIBERONC CB16/12/00390)] and the Plan de Ciencia Tecnología e Innovación del Principado de Asturias/FEDER (IDI/2018/155) to J.P.R and Predoctoral Fellowship Severo Ochoa (BP-17-108) to O.E.S

Reconstructing Native American Migrations from Whole-Genome and Whole-Exome Data

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern America ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.Facultad de Ciencias Naturales y MuseoInstituto Multidisciplinario de Biología Celula

Reconstructing the Population Genetic History of the Caribbean

The Caribbean basin is home to some of the most complex interactions in recent history among previously diverged human populations. Here, by making use of genome-wide SNP array data, we characterize ancestral components of Caribbean populations on a sub-continental level and unveil fine-scale patterns of population structure distinguishing insular from mainland Caribbean populations as well as from other Hispanic/Latino groups. We provide genetic evidence for an inland South American origin of the Native American component in island populations and for extensive pre-Columbian gene flow across the Caribbean basin. The Caribbean-derived European component shows significant differentiation from parental Iberian populations, presumably as a result of founder effects during the colonization of the New World. Based on demographic models, we reconstruct the complex population history of the Caribbean since the onset of continental admixture. We find that insular populations are best modeled as mixtures absorbing two pulses of African migrants, coinciding with early and maximum activity stages of the transatlantic slave trade. These two pulses appear to have originated in different regions within West Africa, imprinting two distinguishable signatures in present day Afro-Caribbean genomes and shedding light on the genetic impact of the dynamics occurring during the slave trade in the Caribbean.Comment: 26 pages, 6 figures, and supporting informatio

History Shaped the Geographic Distribution of Genomic Admixture on the Island of Puerto Rico

Contemporary genetic variation among Latin Americans human groups reflects population migrations shaped by complex historical, social and economic factors. Consequently, admixture patterns may vary by geographic regions ranging from countries to neighborhoods. We examined the geographic variation of admixture across the island of Puerto Rico and the degree to which it could be explained by historic and social events. We analyzed a census-based sample of 642 Puerto Rican individuals that were genotyped for 93 ancestry informative markers (AIMs) to estimate African, European and Native American ancestry. Socioeconomic status (SES) data and geographic location were obtained for each individual. There was significant geographic variation of ancestry across the island. In particular, African ancestry demonstrated a decreasing East to West gradient that was partially explained by historical factors linked to the colonial sugar plantation system. SES also demonstrated a parallel decreasing cline from East to West. However, at a local level, SES and African ancestry were negatively correlated. European ancestry was strongly negatively correlated with African ancestry and therefore showed patterns complementary to African ancestry. By contrast, Native American ancestry showed little variation across the island and across individuals and appears to have played little social role historically. The observed geographic distributions of SES and genetic variation relate to historical social events and mating patterns, and have substantial implications for the design of studies in the recently admixed Puerto Rican population. More generally, our results demonstrate the importance of incorporating social and geographic data with genetics when studying contemporary admixed populations

Reconstructing Native American Migrations from Whole-Genome and Whole-Exome Data

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern America ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.Facultad de Ciencias Naturales y MuseoInstituto Multidisciplinario de Biología Celula

A central support system can facilitate implementation and sustainability of a Classroom-based Undergraduate Research Experience (CURE) in Genomics

In their 2012 report, the President\u27s Council of Advisors on Science and Technology advocated replacing standard science laboratory courses with discovery-based research courses -a challenging proposition that presents practical and pedagogical difficulties. In this paper, we describe our collective experiences working with the Genomics Education Partnership, a nationwide faculty consortium that aims to provide undergraduates with a research experience in genomics through a scheduled course (a classroom-based undergraduate research experience, or CURE). We examine the common barriers encountered in implementing a CURE, program elements of most value to faculty, ways in which a shared core support system can help, and the incentives for and rewards of establishing a CURE on our diverse campuses. While some of the barriers and rewards are specific to a research project utilizing a genomics approach, other lessons learned should be broadly applicable. We find that a central system that supports a shared investigation can mitigate some shortfalls in campus infrastructure (such as time for new curriculum development, availability of IT services) and provides collegial support for change. Our findings should be useful for designing similar supportive programs to facilitate change in the way we teach science for undergraduates

A course-based research experience: how benefits change with increased investment in instructional time

There is widespread agreement that science, technology, engineering, and mathematics programs should provide undergraduates with research experience. Practical issues and limited resources, however, make this a challenge. We have developed a bioinformatics project that provides a course-based research experience for students at a diverse group of schools and offers the opportunity to tailor this experience to local curriculum and institution-specific student needs. We assessed both attitude and knowledge gains, looking for insights into how students respond given this wide range of curricular and institutional variables. While different approaches all appear to result in learning gains, we find that a significant investment of course time is required to enable students to show gains commensurate to a summer research experience. An alumni survey revealed that time spent on a research project is also a significant factor in the value former students assign to the experience one or more years later. We conclude: 1) implementation of a bioinformatics project within the biology curriculum provides a mechanism for successfully engaging large numbers of students in undergraduate research; 2) benefits to students are achievable at a wide variety of academic institutions; and 3) successful implementation of course-based research experiences requires significant investment of instructional time for students to gain full benefit