Biology subjects

Aldape, K.

Publications and source records attributed to Aldape, K..

24 records · Page 2Linked to original sources

bioRxiv2021

Cross-species identification of cancer-resistance associated genes uncovers their relevance to human cancer risk

Cancer is an evolutionarily conserved disease that occurs in a wide variety of species. We applied a comparative genomics approach to systematically characterize the genes whose conservation levels significantly correlates positively (PC) or negatively (NC) with a broad spectrum of cancer-resistance estimates, computed across almost 200 vertebrate species. PC genes are enriched in pathways relevant to tumor suppression including cell cycle, DNA repair, and immune response, while NC genes are enriched with a host of metabolic pathways. The conservation levels of the PC and NC genes in a species serve to build the first genomics-based predictor of its cancer resistance score. We find that PC genes are less tolerant to loss of function (LoF) mutations, are enriched in cancer driver genes and are associated with germline mutations that increase human cancer risk. Furthermore, their expression levels are associated with lifetime cancer risk across human tissues. Finally, their knockout in mice results in increased cancer incidence. In sum, we find that many genes associated with cancer resistance across species are implicated in human cancers, pointing to several additional candidate genes that may have a functional role in human cancer.

cancer biology↗

bioRxiv2021

Recurrent fusions in PLAGL1 define a distinct subset of pediatric-type supratentorial ependymoma

Ependymomas encompass a heterogeneous group of central nervous system (CNS) neoplasms that occur along the entire neuroaxis. In recent years, extensive (epi-)genomic profiling efforts have identified several molecular groups of ependymoma that are characterized by distinct molecular alterations and/or patterns. Based on unsupervised visualization of a large cohort of genome-wide DNA methylation data, we identified a highly distinct group of pediatric-type tumors (n = 40) forming a cluster separate from all established CNS tumor types, of which a high proportion were histopathologically diagnosed as ependymoma. RNA sequencing revealed recurrent fusions involving the pleomorphic adenoma gene-like 1 (PLAGL1) gene in 19 of 20 of the samples analyzed, with the most common fusion being EWSR1:PLAGL1 (n = 13). Five tumors showed a PLAGL1:FOXO1 fusion and one a PLAGL1:EP300 fusion. High transcript levels of PLAGL1 were noted in these tumors, with concurrent overexpression of the imprinted genes H19 and IGF2, which are regulated by PLAGL1. Histopathological review of cases with sufficient material (n = 16) demonstrated a broad morphological spectrum of largely ependymoma-like tumors. Immunohistochemically, tumors were GFAP-positive and OLIG2- and SOX10-negative. In 3/16 of the cases, a dot-like positivity for EMA was detected. Consistent with other fusion-positive ependymal groups, all tumors in our series were located in the supratentorial compartment. Median age of the patients at the time of diagnosis was 6.2 years. Analysis of time to progression or recurrence revealed survival times comparable to those of patients with ZFTA:RELA-fused ependymoma. In summary, our findings suggest the existence of a novel group of supratentorial ependymomas that are characterized by recurrent PLAGL1 fusions and enriched for pediatric patients.

cancer biology↗

bioRxiv2021

Epigenomic tumor evolution modeling with single-cell methylation data profiling

Recent studies exploring the impact of methylation in tumor evolution suggest that while the methylation status of many of the CpG sites are preserved across distinct lineages, others are altered as the cancer progresses. Since changes in methylation status of a CpG site may be retained in mitosis, they could be used to infer the progression history of a tumor via single-cell lineage tree reconstruction. In this work, we introduce the first principled distance-based computational method, Sgootr, for inferring a tumors single-cell methylation lineage tree and jointly identifying lineage-informative CpG sites which harbor changes in methylation status that are retained along the lineage. We apply Sgootr on the single-cell bisulfite-treated whole genome sequencing data of multiregionally-sampled tumor cells from 9 metastatic colorectal cancer patients made available by Bian et al., as well as multiregionally-sampled single-cell reduced-representation bisulfite sequencing data from a glioblastoma patient made available by Chaligne et al.. We demonstrate that the tumor lineages constructed reveal a simple model underlying colorectal tumor progression and metastatic seeding. A comparison of Sgootr against alternative approaches shows that Sgootr can construct lineage trees with fewer migration events and more in concordance with the sequential-progression model of tumor evolution, in time a fraction of that used in prior studies. Interestingly, lineage-informative CpG sites identified by Sgootr are in inter-CpG island (CGI) regions, as opposed to CGIs, which have been the main regions of interest in genomic methylation-related analyses. Sgootr is implemented as a Snakemake workflow, available at https://github.com/algo-cancer/Sgootr. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=63 SRC="FIGDIR/small/436475v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1d3920aorg.highwire.dtl.DTLVardef@11905d4org.highwire.dtl.DTLVardef@1cda90aorg.highwire.dtl.DTLVardef@114ea18_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

DNA methylation and survival differences associated with the type of IDH mutation in 1p/19q non-codeleted astrocytomas

Somatic mutations in the isocitrate dehydrogenase genes IDH1 and IDH2 occur at high frequency in several tumour types. Even though these mutations are confined to distinct hotspots, we show that gliomas are the only tumour type with an exceptionally high percentage of IDH1R132H mutations. This high prevalence is important as IDH1R132H is presumed to be relatively poor at producing D-2-hydroxyglutarate (D-2HG) whereas high concentrations of this oncometabolite are required to inhibit TET2 DNA demethylating enzymes. Indeed, patients harbouring IDH1R132H mutated tumours have lower levels of genome-wide DNA-methylation, and an associated increased gene expression, compared to tumours with other IDH1/2 mutations ("non-R132H mutations"). This reduced methylation is seen in multiple tumour types and thus appears independent of site of origin. For 1p/19q non-codeleted glioma patients, we show that this difference is clinically relevant: in samples of the randomised phase III CATNON trial, patients harbouring non-R132H mutated tumours have better outcome (HR 0.41, 95% CI [0.24, 0.71], p=0.0013). Non-R132H mutated tumours also had a significantly lower proportion of tumours assigned to prognostically poor DNA-methylation classes (p<0.001). IDH mutation-type was independent in a multivariable model containing known clinical and molecular prognostic factors. To confirm these observations, we validated the prognostic effect of IDH mutation type on a large independent dataset. The observation that non-R132H mutated 1p/19q non-codeleted gliomas have a more favourable prognosis than their IDH1R132H mutated counterpart is clinically relevant and should be taken into account for patient prognostication. Single sentence summaryAstrocytoma patients with tumours harbouring IDH mutations other than p.R132H have increased DNA methylation levels and longer survival

cancer biology↗

bioRxiv2020

A simple, high-throughput method of protein and label removal from extracellular vesicle samples

Evidence continues to increase of the clinical utility extracellular vesicles (EVs) can provide as translational biomarkers. While a wide variety of EV isolation and purification methods have been implemented, few techniques are high-throughput and scalable for removing excess fluorescent reagents (e.g. dyes, antibodies). EVs are too small to be recovered from routine cell-processing procedures, such as filtration or centrifugation. The lack of suitable methods for removing unbound labels, especially in optical assays, is a major roadblock to accurate EV phenotyping and utilization of EV assays in a translational or clinical setting. Therefore, we developed a method for using a multi-modal resin, referred to as EV-Clean, to remove unbound labels from EV samples, and we demonstrate improvement in flow cytometric EV analysis with the use of this EV-Clean method.

biochemistry↗

bioRxiv2020

Whole exome precision oncology targeting synthetic lethal vulnerabilities across the tumor transcriptome

Precision oncology has made significant advances in the last few years, mainly by targeting actionable mutations in cancer driver genes. However, the proportion of patients whose tumors can be targeted therapeutically remains limited. Recent studies have begun to explore the benefit of analyzing tumor transcriptomics data to guide patient treatment, raising the need for new approaches for systematically accomplishing that. Here we show that computationally derived genetic interactions can successfully predict patient response. Assembling a broad repertoire of 32 datasets spanning more than 1,500 patients and including both tumor transcriptomics and response data, we predicted the response in 17 out of 21 targeted and 8 out of 11 checkpoint therapy datasets across 8 different cancer types with considerable accuracy, without ever training on these datasets. Analyzing the recently published multi-arm WINTHER trial, we show that the fraction of patients benefitting from transcriptomic-based treatments could potentially be markedly increased from 15% to about 85% by targeting synthetic lethal vulnerabilities in their tumors. In summary, this is the first computational approach to obtain considerable predictive performance across many different targeted and immunotherapy datasets, providing a promising new way for guiding cancer treatment based on the tumor transcriptomics of cancer patients.

cancer biology↗