Genetic Ancestry-specific Molecular and Survival Differences in Admixed Patients With Breast Cancer

OBJECTIVE

We aim to determine whether incremental changes in genetic ancestry percentages influence molecular and clinical outcome characteristics of breast cancer in an admixed population.

BACKGROUND

Patients with breast cancer are predominantly characterized as "Black" or "White" based on self-identified race/ethnicity or arbitrary genetic ancestry cutoffs. This limits scientific discovery in populations that are admixed or of mixed race/ethnicity as they cannot be classified based on historical race/ethnicity boxes or genetic ancestry cutoffs.

METHODS

We used The Cancer Genome Atlas cohort and focused on genetically admixed patients that had less than 90% European, African, Asian, or Native American ancestry.

RESULTS

Genetically admixed patients with breast cancer exhibited improved 10-year overall survival relative to those with >90% European ancestry. Within the luminal A subtype, patients with lower African ancestry had longer 10-year overall survival compared to those with higher African ancestry. The correlation of genetic ancestry with gene expression and DNA methylation in the admixed cohort revealed novel ancestry-specific intrinsic PAM50 subtype patterns. In luminal A tumors, genetic ancestry was correlated with both the expression and methylation of signaling genes, while in basal-like tumors, genetic ancestry was correlated with stemness genes. In addition, we took a machine-learning approach to estimate genetic ancestry from gene expression or DNA methylation and were able to accurately calculate ancestry values from a reduced set of 10 genes or 50 methylation sites that were specific for each molecular subtype.

CONCLUSIONS

Our results suggest that incremental changes in genetic ancestry percentages result in ancestry-specific molecular differences even between well-established PAM50 subtypes which may influence disparities in breast cancer survival outcomes. Accounting for incremental changes in ancestry will be important in future research, prognostication, and risk stratification, particularly in ancestrally diverse populations.

The transcriptional trajectories of pluripotency and differentiation comprise genes with antithetical architecture and repetitive-element content

Background

Extensive molecular differences exist between proliferative and differentiated cells. Here, we conduct a meta-analysis of publicly available transcriptomic datasets from preimplantation and differentiation stages examining the architectural properties and content of genes whose abundance changes significantly across developmental time points.

Results

Analysis of preimplantation embryos from human and mouse showed that short genes whose introns are enriched in Alu (human) and B (mouse) elements, respectively, have higher abundance in the blastocyst compared to the zygote. These highly expressed genes encode ribosomal proteins or metabolic enzymes. On the other hand, long genes whose introns are depleted in repetitive elements have lower abundance in the blastocyst and include genes from signaling pathways. Additionally, the sequences of the genes that are differentially expressed between the blastocyst and the zygote contain distinct collections of pyknon motifs that differ between up- and down-regulated genes. Further examination of the genes that participate in the stem cell-specific protein interaction network shows that their introns are short and enriched in Alu (human) and B (mouse) elements. As organogenesis progresses, in both human and mouse, we find that the primarily short and repeat-rich expressed genes make way for primarily longer, repeat-poor genes. With that in mind, we used a machine learning-based approach to identify gene signatures able to classify human adult tissues: we find that the most discriminatory genes comprising these signatures have long introns that are repeat-poor and include transcription factors and signaling-cascade genes. The introns of widely expressed genes across human tissues, on the other hand, are short and repeat-rich, and coincide with those with the highest expression at the blastocyst stage.

Conclusions

Protein-coding genes that are characteristic of each trajectory, i.e., proliferation/pluripotency or differentiation, exhibit antithetical biases in their intronic and exonic lengths and in their repetitive-element content. While the respective human and mouse gene signatures are functionally and evolutionarily conserved, their introns and exons are enriched or depleted in organism-specific repetitive elements. We posit that these organism-specific repetitive sequences found in exons and introns are used to effect the corresponding genes’ regulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-020-00928-8.

IsoMiRmap-fast, deterministic, and exhaustive mining of isomiRs from short RNA-seq datasets

MOTIVATION

MicroRNA (miRNA) precursor arms give rise to multiple isoforms simultaneously called "isomiRs." IsomiRs from the same arm typically differ by a few nucleotides at either their 5´ or 3´ termini, or both. In humans, the identities and abundances of isomiRs depend on a person's sex, population of origin, race/ethnicity, and on tissue type, tissue state, and disease type/subtype. Moreover, nearly half of the time the most abundant isomiR differs from the miRNA sequence found in public databases. Accurate mining of isomiRs from deep sequencing data is thus important.

RESULTS

We developed isoMiRmap, a fast, standalone, user-friendly mining tool that identifies and quantifies all isomiRs by directly processing short RNA-seq datasets. IsoMiRmap is a portable "plug-and-play" tool, requires minimal setup, has modest computing and storage requirements, and can process an RNA-seq dataset with 50 million reads in just a few minutes on an average laptop. IsoMiRmap deterministically and exhaustively reports all isomiRs in a given deep sequencing dataset and quantifies them accurately (no double-counting). IsoMiRmap comprehensively reports all miRNA precursor locations from which an isomiR may be transcribed, tags as 'ambiguous' isomiRs whose sequences exist both inside and outside of the space of known miRNA sequences and reports the public identifiers of common single-nucleotide polymorphisms and documented somatic mutations that may be present in an isomiR. IsoMiRmap also identifies isomiRs with 3´ non-templated post-transcriptional additions. Compared to similar tools, isoMiRmap is the fastest, reports more bona fide isomiRs, and provides the most comprehensive information related to an isomiR's transcriptional origin.

AVAILABILITY

The codes for isoMiRmap are freely available at https://cm.jefferson.edu/isoMiRmap/ and https://github.com/TJU-CMC-Org/isoMiRmap/. IsomiR profiles for the datasets of the 1000 Genomes Project, spanning five population groups, and The Cancer Genome Atlas (TCGA), spanning 33 cancer studies, are also available at https://cm.jefferson.edu/isoMiRmap/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

MOTIVATION

MicroRNAs (miRNAs) are small RNA molecules (∼22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods.

RESULTS

To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification.

AVAILABILITY AND IMPLEMENTATION

https://github.com/miRTop/mirGFF3/ and https://github.com/miRTop/mirtop.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Lactate Efflux From Intervertebral Disc Cells Is Required for Maintenance of Spine Health

Maintenance of glycolytic metabolism is postulated to be required for health of the spinal column. In the hypoxic tissues of the intervertebral disc and glycolytic cells of vertebral bone, glucose is metabolized into pyruvate for ATP generation and reduced to lactate to sustain redox balance. The rise in intracellular H⁺ /lactate concentrations are balanced by plasma-membrane monocarboxylate transporters (MCTs). Using MCT4 null mice and human tissue samples, complemented with genetic and metabolic approaches, we determine that H⁺ /lactate efflux is critical for maintenance of disc and vertebral bone health. Mechanistically, MCT4 maintains glycolytic and tricarboxylic acid (TCA) cycle flux and intracellular pH homeostasis in the nucleus pulposus compartment of the disc, where hypoxia-inducible factor 1α (HIF-1α) directly activates an intronic enhancer in SLC16A3. Ultimately, our results provide support for research into lactate as a diagnostic biomarker for chronic, painful, disc degeneration. © 2019 American Society for Bone and Mineral Research.

MINTbase v2.0: a comprehensive database for tRNA-derived fragments that includes nuclear and mitochondrial fragments from all The Cancer Genome Atlas projects

MINTbase is a repository that comprises nuclear and mitochondrial tRNA-derived fragments ('tRFs') found in multiple human tissues. The original version of MINTbase comprised tRFs obtained from 768 transcriptomic datasets. We used our deterministic and exhaustive tRF mining pipeline to process all of The Cancer Genome Atlas datasets (TCGA). We identified 23 413 tRFs with abundance of ≥ 1.0 reads-per-million (RPM). To facilitate further studies of tRFs by the community, we just released version 2.0 of MINTbase that contains information about 26 531 distinct human tRFs from 11 719 human datasets as of October 2017. Key new elements include: the ability to filter tRFs on-the-fly by minimum abundance thresholding; the ability to filter tRFs by tissue keywords; easy access to information about a tRF's maximum abundance and the datasets that contain it; the ability to generate relative abundance plots for tRFs across cancer types and convert them into embeddable figures; MODOMICS information about modifications of the parental tRNA, etc. Version 2.0 of MINTbase contains 15x more datasets and nearly 4x more distinct tRFs than the original version, yet continues to offer fast, interactive access to its contents. Version 2.0 is available freely at http://cm.jefferson.edu/MINTbase/.

tRNA Fragments Show Intertwining with mRNAs of Specific Repeat Content and Have Links to Disparities

tRNA-derived fragments (tRF) are a class of potent regulatory RNAs. We mined the datasets from The Cancer Genome Atlas (TCGA) representing 32 cancer types with a deterministic and exhaustive pipeline for tRNA fragments. We found that mitochondrial tRNAs contribute disproportionally more tRFs than nuclear tRNAs. Through integrative analyses, we uncovered a multitude of statistically significant and context-dependent associations between the identified tRFs and mRNAs. In many of the 32 cancer types, these associations involve mRNAs from developmental processes, receptor tyrosine kinase signaling, the proteasome, and metabolic pathways that include glycolysis, oxidative phosphorylation, and ATP synthesis. Even though the pathways are common to multiple cancers, the association of specific mRNAs with tRFs depends on and differs from cancer to cancer. The associations between tRFs and mRNAs extend to genomic properties as well; specifically, tRFs are positively correlated with shorter genes that have a higher density in repeats, such as ALUs, MIRs, and ERVLs. Conversely, tRFs are negatively correlated with longer genes that have a lower repeat density, suggesting a possible dichotomy between cell proliferation and differentiation. Analyses of bladder, lung, and kidney cancer data indicate that the tRF-mRNA wiring can also depend on a patient's sex. Sex-dependent associations involve cyclin-dependent kinases in bladder cancer, the MAPK signaling pathway in lung cancer, and purine metabolism in kidney cancer. Taken together, these findings suggest diverse and wide-ranging roles for tRFs and highlight the extensive interconnections of tRFs with key cellular processes and human genomic architecture. SIGNIFICANCE: Across 32 TCGA cancer contexts, nuclear and mitochondrial tRNA fragments exhibit associations with mRNAs that belong to concrete pathways, encode proteins with particular destinations, have a biased repeat content, and are sex dependent.

Abstract B64: Race and prostate cancer: miRNA isoforms and tRNA fragments could hold some of the answers

Prostate cancer is the most frequently occurring cancer in men. Compared to White (Wh) men, Black/African American (B/Aa) men exhibit higher mortality and higher incidence rates of prostate cancer. This difference remains even after modifiable factors are taken into account, which suggests an underlying cause. Recent studies greatly improved our understanding of the biochemistry of prostate cancer. Nonetheless, many open questions remain, especially with regard to the molecular underpinnings of the observed race disparities.

In this study, we analyzed 526 transcriptomic datasets from prostate adenocarcinoma (PRAD) patients. We obtained the data from The Cancer Genome Atlas (TCGA) repository. We focused on two categories of noncoding RNAs that regulate messenger RNA (mRNA) and protein abundance: (1) microRNAs (miRNAs) and their isoforms (isomiRs) and (2) tRNA-derived fragments (tRFs). Both tRFs and isomiRs regulate mRNAs and their proteins through the RNA induced silencing complex (RISC). Furthermore, tRFs have a number of other regulatory roles in healthy and diseased cells, including direct physical interactions with ribosomal proteins and initiation factors. Notably, we have demonstrated and reported previously that isomiRs and tRFs are constitutive and transcribed in a manner that depends strongly on a person's gender, race, and population origin, as well as on tissue type, tissue state, and disease type/subtype.

Our analyses of the TCGA PRAD datasets revealed that both isomiRs and tRFs are disrupted in PRAD. By extension, the regulatory networks that link isomiRs and tRFs to mRNAs are also disrupted. We also uncovered transcriptomic differences and differential regulatory relationships that are aligned with patient race. Moreover, we found that the molecular differences between B/Aa and Wh PRAD patients extend to normal prostate tissue as well. These findings mirror earlier results that we obtained from both healthy individuals and cancer patients.

The race-dependent regulatory profiles highlight differences in the underlying biology in B/Aa and Wh individuals that have yet to be explored. For example, the corresponding molecules could potentially be leveraged as novel biomarkers or alternative therapeutic targets. This study represents the first characterization of isomiRs and tRFs in a large cohort of PRAD patients.

Citation Format: Rogan G. Magee, Aristeidis G. Telonis, Phillipe Loher, Eric Londin, Isidore Rigoutsos. Race and prostate cancer: miRNA isoforms and tRNA fragments could hold some of the answers [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr B64.

Abstract B63: Race and triple-negative breast cancer: Advances in noncoding RNA research together with a systems-biology-level analysis uncover key molecular differences

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is characterized by marked differences between Black/African-American (B/Aa) and White (Wh) women. Despite the great progress that has been achieved towards understanding the causes of race disparities in TNBC, there have been no system-level investigations of the problem from the standpoint of molecular oncology.

We used the transcriptomic data from The Cancer Genome Atlas (TCGA) repository to study the normal breast and TNBC samples from Wh and B/Aa TNBC individuals that are contained in it. Specifically, our analysis integrated transcriptomic data from messenger RNAs (mRNAs), microRNAs (miRNAs), miRNA isoforms (isomiRs), and tRNA-derived fragments (tRFs). IsomiRs and tRFs are constitutive regulatory molecules that target genes and pathways through RNA interference (RNAi). In addition to RNAi, isomiRs and tRFs also have other modes of action that are not yet understood. IsomiRs and tRFs represent recent and very important advances in our understanding of post-transcriptional regulation in the cell. What makes them particularly relevant for this study is our having shown that the “footprint” of isomiRs and tRFs that are active in a cell depends strongly on a person's gender, race, and population origin, as well as on tissue type, tissue state, and disease type/subtype.

We analyzed and compared TCGA samples from normal breast and TNBC and did so separately for B/Aa and Wh donors. As expected, we found many mRNAs to be differentially expressed. More importantly, when we compared B/Aa and Wh TNBC patients we found many mRNAs to be differentially wired. By this we mean that, even though the two groups of patients have many regulators and effectors in common, there are very extensive differences in the manner regulators interact with effectors in B/Aa and in Wh TNBC patients, respectively. Our accumulated evidence suggests strongly that this differential wiring is an important driver of the phenotypic differences that we observe between B/Aa and Wh TNBC patients.

Our studies show that there is a multitude of regulatory molecules that are involved in this rewiring and the racial disparities in TNBC. Among isomiRs, we identified numerous isomiRs that arise from the mir-200c and mir-21 miRNA precursors, and from the oncogenic miR-17/92 and miR-183/96/182 clusters. Among tRFs, we identified many tRFs that arise from nuclear (e.g., Glycine, Leucine) and mitochondrial tRNAs (e.g., Valine, Proline). We showcase this race-specific rewiring with the help of MAPK and Wnt signaling, two metastasis-related pathways.

The data-driven approaches that we employed in the analysis enabled us to carry out comprehensive studies of the transcriptomes of two states (normal and cancer) and two races (B/Aa and Wh). Our methodology allowed us to dissect the complex regulatory events that are mediated by isomiRs and tRFs. It also helped us unravel the significant roles that isomiRs and tRFs have in reshaping mRNA expression differentially in the two races. Collectively, our findings suggest that systems biology-level avenues may prove fruitful in the study of disparities in TNBC and in other cancers.

Citation Format: Aristeidis G. Telonis, Isidore Rigoutsos. Race and triple-negative breast cancer: Advances in noncoding RNA research together with a systems-biology-level analysis uncover key molecular differences [abstract]. In: Proceedings of the Tenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2017 Sep 25-28; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2018;27(7 Suppl):Abstract nr B63.

Profiles of miRNA Isoforms and tRNA Fragments in Prostate Cancer

MicroRNA (miRNA) isoforms (“isomiRs”) and tRNA-derived fragments (“tRFs”) are powerful regulatory non-coding RNAs (ncRNAs). In human tissues, both types of molecules are abundant, with expression patterns that depend on a person’s race, sex and population origin. Here, we present our analyses of the Prostate Cancer (PRAD) datasets of The Cancer Genome Atlas (TCGA) from the standpoint of isomiRs and tRFs. This study represents the first simultaneous examination of isomiRs and tRFs in a large cohort of PRAD patients. We find that isomiRs and tRFs have extensive correlations with messenger RNAs (mRNAs). These correlations are disrupted in PRAD, which suggests disruptions of the regulatory network in the disease state. Notably, we find that the profiles of isomiRs and tRFs differ in patients belonging to different races. We hope that the presented findings can lay the groundwork for future research efforts aimed at elucidating the functional roles of the numerous and distinct members of these two categories of ncRNAs that are present in PRAD.

Race Disparities in the Contribution of miRNA Isoforms and tRNA-Derived Fragments to Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a breast cancer subtype characterized by marked differences between White and Black/African-American women. We performed a systems-level analysis on datasets from The Cancer Genome Atlas to elucidate how the expression patterns of mRNAs are shaped by regulatory noncoding RNAs (ncRNA). Specifically, we studied isomiRs, that is, isoforms of miRNAs, and tRNA-derived fragments (tRF). In normal breast tissue, we observed a marked cohesiveness in both the ncRNA and mRNA layers and the associations between them. This cohesiveness was widely disrupted in TNBC. Many mRNAs become either differentially expressed or differentially wired between normal breast and TNBC in tandem with isomiR or tRF dysregulation. The affected pathways included energy metabolism, cell signaling, and immune responses. Within TNBC, the wiring of the affected pathways with isomiRs and tRFs differed in each race. Multiple isomiRs and tRFs arising from specific miRNA loci (e.g., miR-200c, miR-21, the miR-17/92 cluster, the miR-183/96/182 cluster) and from specific tRNA loci (e.g., the nuclear tRNA^Gly and tRNA^Leu, the mitochondrial tRNA^Val and tRNA^Pro) were strongly associated with the observed race disparities in TNBC. We highlight the race-specific aspects of transcriptome wiring by discussing in detail the metastasis-related MAPK and the Wnt/β-catenin signaling pathways, two of the many key pathways that were found differentially wired. In conclusion, by employing a data- and knowledge-driven approach, we comprehensively analyzed the normal and cancer transcriptomes to uncover novel key contributors to the race-based disparities of TNBC.Significance: This big data-driven study comparing normal and cancer transcriptomes uncovers RNA expression differences between Caucasian and African-American patients with triple-negative breast cancer that might help explain disparities in incidence and aggressive character. Cancer Res; 78(5); 1140-54. ©2017 AACR.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs

Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes.

Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types

Isoforms of human miRNAs (isomiRs) are constitutively expressed with tissue- and disease-subtype-dependencies. We studied 10 271 tumor datasets from The Cancer Genome Atlas (TCGA) to evaluate whether isomiRs can distinguish amongst 32 TCGA cancers. Unlike previous approaches, we built a classifier that relied solely on ‘binarized’ isomiR profiles: each isomiR is simply labeled as ‘present’ or ‘absent’. The resulting classifier successfully labeled tumor datasets with an average sensitivity of 90% and a false discovery rate (FDR) of 3%, surpassing the performance of expression-based classification. The classifier maintained its power even after a 15× reduction in the number of isomiRs that were used for training. Notably, the classifier could correctly predict the cancer type in non-TCGA datasets from diverse platforms. Our analysis revealed that the most discriminatory isomiRs happen to also be differentially expressed between normal tissue and cancer. Even so, we find that these highly discriminating isomiRs have not been attracting the most research attention in the literature. Given their ability to successfully classify datasets from 32 cancers, isomiRs and our resulting ‘Pan-cancer Atlas’ of isomiR expression could serve as a suitable framework to explore novel cancer biomarkers.

Abstract 5438: Knowledge of which miRNA isoforms are expressed in a sample can successfully discriminate amongst the 32 TCGA cancer types

Background: Next-generation sequencing (NGS) technologies made possible the generation of large amounts of data quickly and inexpensively process. As a result, the challenge nowadays is how best to manipulate and analyze Big Data. Among non-coding RNAs, microRNAs (miRNAs) are the best studied to date. MiRNAs have attracted a lot of attention because they are centrally involved in homeostasis and can regulate thousands of coding and non-coding transcripts. The complexity of miRNA-mediated regulation increased further with the recent discovery that miRNA isoforms (isomiRs) are produced constitutively and that isomiR expression depends on a person’s sex, population origin, race and also on tissue type, tissue state, and disease subtype.

Methods: We computed and analyzed isomiR profiles across 10,271 short RNA-seq datasets from The Cancer Genome Atlas (TCGA) repository, which represent 32 cancer types. Focusing on the isomiRs of each dataset, we built a classifier that relied solely on “binarized” isomiR profiles: in a dataset, an isomiR was labeled ‘present,’ if its expression exceeded a threshold that depended on the depth of sequencing, and ‘absent’ otherwise. This differs radically from previous methods in that it attempts to classify by relying on the presence or absence of isomiRs, intentionally discarding all information about the isomiRs’ expression level. We also built a classifier that relied solely on “binarized” miRNA arm profiles: a miRNA arm was labeled ‘present’ if at least one of the isomiRs it produces is ‘present’ in the same dataset.

Results: The classifier we built using binarized isomiR profiles discriminated among all 32 TCGA cancer types and classified datasets with sensitivity >90% and a false discovery rate (FDR) < 3.0%. The ability of this classifier to correctly distinguish among the 32 cancers persisted even after a 15x reduction in the number of isomiRs used. The classifier we built using binarized miRNA arm profiles could also discriminate among all 32 TCGA cancers albeit with a lower sensitivity (83%) and a slightly higher FDR (6%). We also examined how well the various miRNA loci have been studied over time by measuring the corresponding number of published articles. Surprisingly, the miRNAs whose isoforms have the highest ability to classify tumors are not those with the most articles in PubMed.

Conclusions: The presence or absence of a specific isomiR provides adequate discriminatory power to accurately classify a sample as belonging to one of the 32 TCGA cancers. The findings suggest that isomiRs can be used as potent, novel, cancer-specific biomarkers. By ignoring the expression levels of isomiRs, we effectively show that the same miRNA produces different clouds of isoforms in each cancer type. And, since distinct isomiRs target distinct mRNAs, it follows that a miRNA locus will target different mRNAs in different cancers simply by expressing different clouds of isoforms each time.

Citation Format: Aristeidis G. Telonis, Rogan Magee, Phillipe Loher, Inna Chervoneva, Eric Londin, Isidore Rigoutsos. Knowledge of which miRNA isoforms are expressed in a sample can successfully discriminate amongst the 32 TCGA cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5438. doi:10.1158/1538-7445.AM2017-5438

N-BLR, a primate-specific non-coding transcript leads to colorectal cancer invasion and migration

Background

Non-coding RNAs have been drawing increasing attention in recent years as functional data suggest that they play important roles in key cellular processes. N-BLR is a primate-specific long non-coding RNA that modulates the epithelial-to-mesenchymal transition, facilitates cell migration, and increases colorectal cancer invasion.

Results

We performed multivariate analyses of data from two independent cohorts of colorectal cancer patients and show that the abundance of N-BLR is associated with tumor stage, invasion potential, and overall patient survival. Through in vitro and in vivo experiments we found that N-BLR facilitates migration primarily via crosstalk with E-cadherin and ZEB1. We showed that this crosstalk is mediated by a pyknon, a short ~20 nucleotide-long DNA motif contained in the N-BLR transcript and is targeted by members of the miR-200 family. In light of these findings, we used a microarray to investigate the expression patterns of other pyknon-containing genomic loci. We found multiple such loci that are differentially transcribed between healthy and diseased tissues in colorectal cancer and chronic lymphocytic leukemia. Moreover, we identified several new loci whose expression correlates with the colorectal cancer patients’ overall survival.

Conclusions

The primate-specific N-BLR is a novel molecular contributor to the complex mechanisms that underlie metastasis in colorectal cancer and a potential novel biomarker for this disease. The presence of a functional pyknon within N-BLR and the related finding that many more pyknon-containing genomic loci in the human genome exhibit tissue-specific and disease-specific expression suggests the possibility of an alternative class of biomarkers and therapeutic targets that are primate-specific.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1224-0) contains supplementary material, which is available to authorized users.

MINTmap: fast and exhaustive profiling of nuclear and mitochondrial tRNA fragments from short RNA-seq data

Transfer RNA fragments (tRFs) are an established class of constitutive regulatory molecules that arise from precursor and mature tRNAs. RNA deep sequencing (RNA-seq) has greatly facilitated the study of tRFs. However, the repeat nature of the tRNA templates and the idiosyncrasies of tRNA sequences necessitate the development and use of methodologies that differ markedly from those used to analyze RNA-seq data when studying microRNAs (miRNAs) or messenger RNAs (mRNAs). Here we present MINTmap (for MItochondrial and Nuclear TRF mapping), a method and a software package that was developed specifically for the quick, deterministic and exhaustive identification of tRFs in short RNA-seq datasets. In addition to identifying them, MINTmap is able to unambiguously calculate and report both raw and normalized abundances for the discovered tRFs. Furthermore, to ensure specificity, MINTmap identifies the subset of discovered tRFs that could be originating outside of tRNA space and flags them as candidate false positives. Our comparative analysis shows that MINTmap exhibits superior sensitivity and specificity to other available methods while also being exceptionally fast. The MINTmap codes are available through https://github.com/TJU-CMC-Org/MINTmap/ under an open source GNU GPL v3.0 license.

Abstract P4-08-01: IsomiRs and tRNA fragments are race-dependent regulators in breast cancer

This abstract was not presented at the symposium.

Abstract B79: Integrative quantitative analysis of pancreatic ductal adenocarcinoma mRNA, miRNA, and methylation profiles reveals interactions that are dependent on tumor cellularity

The Cancer Genome Atlas (TCGA) Pancreatic Adenocarcinoma (PAAD) consortium has conducted multilevel molecular profiling of 150 PAAD cases, including mRNA, miRNA, and methylation profiles. PAAD tumors are highly heterogeneous characterized by the significant presence of stromal cells and therefore by low tumor cellularity or tumor purity. This high tumor heterogeneity complicates genomic analysis of the tumor. Here, we investigated whether there are purity-specific interactions in the PAAD cohort of samples integrating mRNA, miRNA and methylation information.

The 150 subjects analyzed comprised of two almost equally sized tumor groups defined as having “low” (n=74) or “high” (n=76) purity and were analyzed separately to identify purity-specific interactions. Leveraging the TCGA transcriptomic and epigenomic data from these groups, we conducted correlation analyses to identify statistically significant miRNA-mRNA anti-correlations as well as among all miRNAs/mRNAs and the methylation probes in close proximity. Using computational miRNA target predictions, we identified potential miRNA:mRNA interactions between the miRNA-mRNA anti-correlated pairs.

Our findings describe a distinct regulatory landscape in each of the two purity groups. The interaction networks followed power-law distributions with specific miRNAs serving as the hubs of the scale-free networks. In the “low” purity group, miR-21-5p was identified to be a major hub, while the “high” purity network had miRNAs from both arms of miR-192 and miR-194 serving as the main hubs. These miRNAs were differentially regulating the transcriptome in each tumor group, as the differentially expressed transcripts between the two tumor groups were important components of the networks. The methylome impact on the transcriptome was found to have two components: one that is tumor-purity-dependent and one that is not dependent on purity. The former was the strongest as the majority of the methylation-mRNA/miRNA anti-correlations were distinct in the two groups.

The above results describe a purity-specific interaction map and highlight the importance of the stroma cells as regulators of the tumor genomic regulatory landscape. They further shed light on the dynamics of the pancreatic adenocarcinomas as they designate purity-specific regulatory axes that can be targetable. These signatures can increase our understanding pancreatic ductal adenocarcinoma and lead to improved patient outcomes.

Citation Format: Aristeidis G. Telonis, on behalf of The Cancer Genome Atlas Research Network.{Authors}. Integrative quantitative analysis of pancreatic ductal adenocarcinoma mRNA, miRNA, and methylation profiles reveals interactions that are dependent on tumor cellularity. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B79.

Targeting the mRNA-binding protein HuR impairs malignant characteristics of pancreatic ductal adenocarcinoma cells

Post-transcriptional regulation is a powerful mediator of gene expression, and can rapidly alter the expression of numerous transcripts involved in tumorigenesis. We have previously shown that the mRNA-binding protein HuR (ELAVL1) is elevated in human pancreatic ductal adenocarcinoma (PDA) specimens compared to normal pancreatic tissues, and its cytoplasmic localization is associated with increased tumor stage. To gain a better insight into HuR’s role in PDA biology and to assess it as a candidate therapeutic target, we altered HuR expression in PDA cell lines and characterized the resulting phenotype in preclinical models. HuR silencing by short hairpin and small interfering RNAs significantly decreased cell proliferation and anchorage-independent growth, as well as impaired migration and invasion. In comparison, HuR overexpression increased migration and invasion, but had no significant effects on cell proliferation and anchorage-independent growth. Importantly, two distinct targeted approaches to HuR silencing showed marked impairment in tumor growth in mouse xenografts. NanoString nCounter^® analyses demonstrated that HuR regulates core biological processes, highlighting that HuR inhibition likely thwarts PDA viability through post-transcriptional regulation of diverse signaling pathways (e.g. cell cycle, apoptosis, DNA repair). Taken together, our study suggests that targeted inhibition of HuR may be a novel, promising approach to the treatment of PDA.

Dissecting tRNA-derived fragment complexities using personalized transcriptomes reveals novel fragment classes and unexpected dependencies

We analyzed transcriptomic data from 452 healthy men and women representing five different human populations and two races, and, 311 breast cancer samples from The Cancer Genome Atlas. Our studies revealed numerous constitutive, distinct fragments with overlapping sequences and quantized lengths that persist across dozens of individuals and arise from the genomic loci of all nuclear and mitochondrial human transfer RNAs (tRNAs). Surprisingly, we discovered that the tRNA fragments' length, starting and ending points, and relative abundance depend on gender, population, race and also on amino acid identity, anticodon, genomic locus, tissue, disease, and disease subtype. Moreover, the length distribution of mitochondrially-encoded tRNAs differs from that of nuclearly-encoded tRNAs, and the specifics of these distributions depend on tissue. Notably, tRNA fragments from the same anticodon do not have correlated abundances. We also report on a novel category of tRNA fragments that significantly contribute to the differences we observe across tissues, genders, populations, and races: these fragments, referred to as i-tRFs, are abundant in human tissues, wholly internal to the respective mature tRNA, and can straddle the anticodon. HITS-CLIP data analysis revealed that tRNA fragments are loaded on Argonaute in a cell-dependent manner, suggesting cell-dependent functional roles through the RNA interference pathway. We validated experimentally two i-tRF molecules: the first was found in 21 of 22 tested breast tumor and adjacent normal samples and was differentially abundant between health and disease whereas the second was found in all eight tested breast cancer cell lines.

GPRC5A is a potential oncogene in pancreatic ductal adenocarcinoma cells that is upregulated by gemcitabine with help from HuR

GPRC5A is an orphan G-protein coupled receptor with an intriguing dual behavior, acting as an oncogene in some cancers and as a tumor suppressor in other cancers. In the pancreatic cancer context, very little is known about GPRC5A. By analyzing messenger RNA (mRNA) expression data from 675 human cancer cell lines and 10 609 samples from The Cancer Genome Atlas (TCGA) we found that GPRC5A's abundance in pancreatic cancer is highest (cell lines) or second highest (TCGA) among all tissues and cancer types. Further analyses of an independent set of 252 pancreatic normal and cancer samples showed GPRC5A mRNA to be more than twofold upregulated in primary tumor samples compared with normal pancreas (P-value<10⁻⁵), and even further upregulated in pancreatic cancer metastases to various organs (P-value=0.0021). Immunostaining of 208 cores (103 samples) of a tissue microarray showed generally low expression of GPRC5A protein in normal pancreatic ductal cells; on the other hand, in primary and metastatic samples, GPRC5A protein levels were dramatically increased in pancreatic ductal cells. In vitro studies of multiple pancreatic cancer cell lines showed that an increase in GPRC5A protein levels promoted pancreatic cancer cell growth and migration. Unexpectedly, when we treated pancreatic cancer cell lines with gemcitabine (2′,2′-difluorodeoxycytidine), we observed an increase in GPRC5A protein abundance. On the other hand, when we knocked down GPRC5A we sensitized pancreatic cancer cells to gemcitabine. Through further experimentation we showed that the monotonic increase in GPRC5A protein levels that we observe for the first 18 h following gemcitabine treatment results from interactions between GPRC5A's mRNA and the RNA-binding protein HuR, which is an established key mediator of gemcitabine's efficacy in cancer cells. As we discovered, the interaction between GPRC5A and HuR is mediated by at least one HuR-binding site in GPRC5A's mRNA. Our findings indicate that GPRC5A is part of a complex molecular axis that involves gemcitabine and HuR, and, possibly, other genes. Further work is warranted before it can be established unequivocally that GPRC5A is an oncogene in the pancreatic cancer context.

MINTbase: a framework for the interactive exploration of mitochondrial and nuclear tRNA fragments

Motivation: It has been known that mature transfer RNAs (tRNAs) that are encoded in the nuclear genome give rise to short molecules, collectively known as tRNA fragments or tRFs. Recently, we reported that, in healthy individuals and in patients, tRFs are constitutive, arise from mitochondrial as well as from nuclear tRNAs, and have composition and abundances that depend on a person’s sex, population origin and race as well as on tissue, disease and disease subtype. Our findings as well as similar work by other groups highlight the importance of tRFs and presage an increase in the community’s interest in elucidating the roles of tRFs in health and disease.

Results: We created MINTbase, a web-based framework that serves the dual-purpose of being a content repository for tRFs and a tool for the interactive exploration of these newly discovered molecules. A key feature of MINTbase is that it deterministically and exhaustively enumerates all possible genomic locations where a sequence fragment can be found and indicates which fragments are exclusive to tRNA space, and thus can be considered as tRFs: this is a very important consideration given that the genomes of higher organisms are riddled with partial tRNA sequences and with tRNA-lookalikes whose aberrant transcripts can be mistaken for tRFs. MINTbase is extremely flexible and integrates and presents tRF information from multiple yet interconnected vantage points (‘vistas’). Vistas permit the user to interactively personalize the information that is returned and the manner in which it is displayed. MINTbase can report comparative information on how a tRF is distributed across all anticodon/amino acid combinations, provides alignments between a tRNA and multiple tRFs with which the user can interact, provides details on published studies that reported a tRF as expressed, etc. Importantly, we designed MINTbase to contain all possible tRFs that could ever be produced by mature tRNAs: this allows us to report on their genomic distributions, anticodon/amino acid properties, alignments, etc. while giving users the ability to at-will investigate candidate tRF molecules before embarking on focused experimental explorations. Lastly, we also introduce a new labeling scheme that is tRF-sequence-based and allows users to associate a tRF with a universally unique label (‘tRF-license plate’) that is independent of a genome assembly and does not require any brokering mechanism.

Availability and Implementation: MINTbase is freely accessible at http://cm.jefferson.edu/MINTbase/. Dataset submissions to MINTbase can be initiated at http://cm.jefferson.edu/MINTsubmit/.

Contact:isidore.rigoutsos@jefferson.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Consequential considerations when mapping tRNA fragments

We examine several of the choices that went into the design of tDRmapper, a recently reported tool for identifying transfer RNA (tRNA) fragments in deep sequencing data, evaluate them in the context of currently available knowledge, and discuss their potential impact on the output that the tool generates.

Abstract PR04: The molecular biology of nuclear and mitochondrial regulatory noncoding RNAs differs between white and African American patients with triple-negative breast cancer

Noncoding RNAs (ncRNAs) are molecules that do not code for proteins but regulate cell physiology via multiple mechanisms. Through studies of hundreds of human datasets from healthy individuals and patients we found for two categories of ncRNAs that their composition and abundances depend on a person's gender, population, race, and several other variables. These two categories are: a) isoforms of microRNAs (miRNAs), also known as isomiRs; and, b) fragments derived from transfer RNAs (tRNAs), also known as tRNA fragments or tRFs.

Traditionally, a miRNA genomic locus was thought to give rise to a single mature miRNA (archetype). The archetype's sequence was recorded in public databases and used to design reagents and experiments. Advances in sequencing technology have revealed that miRNA loci simultaneously give rise to multiple isomiRs, i.e. isoforms of the archetype miRNAs, with distinct endpoints and abundances. Importantly, isoforms are loaded on the RNA-induced silencing complex (RISC) thereby entering the RNA interference (RNAi) pathway where they guide sequence-based RISC interactions with specifically targeted messenger RNAs (mRNAs) and ncRNAs, thusly controlling the abundance of those transcripts. Moreover, miRNAs have been linked to a multitude of cellular processes in health and disease.

Analogously, the genomic loci harboring tRNAs were thought to give rise to only the mature tRNA sequence, the latter being an integral part of the translation of mRNAs into amino acid sequences. As with isomiRs, modern sequencing technology revealed the existence of tRNA fragments that co-exist with the corresponding full-length mature tRNAs. Fast accumulating evidence has already linked tRFs to cell growth, cell proliferation, response to DNA damage, translation initiation, response to stress, etc. Some tRFs have also been found on RISC and to participate in RNAi, similarly to isomiRs.

We investigated isomiRs and tRFs in human samples, in health and disease. Specifically, we used public transcriptomic datasets from the 1,000 Genomes Project and from The Cancer Genome Atlas (TCGA) repository at the National Institutes of Health. By analyzing samples from nearly five hundred healthy individuals we found that both the isomiR profiles and the tRF profiles depend on a person's gender, population, race, tissue and tissue state. In the case of tRNA fragments, we found that they derive from nuclear and from mitochondrial tRNAs.

By focusing on data from cancer patients we found that the dependencies we uncovered extend to the disease context as well. In particular, our analysis of samples from White and African-American triple negative breast cancer (TNBC) patients showed that there exist extensive and significant differences in the isomiR and tRF profiles between the two races. More specifically, we identified many isomiRs and tRFs that are differentially abundant in TNBC samples from White patients vs. TNBC samples from African-American patients. We also found that analogous isomiR and tRF differences distinguish the normal breast samples of White and African American subjects. When we integrated the isomiR information with mRNA expression values from the corresponding TCGA TNBC samples we found that the molecular biology differences in the isomiR and tRF profiles were indeed reflected in the abundance of protein coding genes, a result that could serve as a starting point for deeper research activities towards explaining health disparities in this breast cancer subtype.

Our studies suggest that miRNA isoforms and tRNA fragments are active novel members of the molecular biology of TNBC. Future studies of this disease will need to also consider these molecules given that they represent a component of the cell's regulatory layer that depends on the patient's race.

This abstract is also presented as Poster C62.

Citation Format: Aristeidis G. Telonis, Phillipe Loher, Yi Jing, Eric Londin, Isidore Rigoutsos. The molecular biology of nuclear and mitochondrial regulatory noncoding RNAs differs between white and African American patients with triple-negative breast cancer. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr PR04.

Four-leaf clover qRT-PCR: A convenient method for selective quantification of mature tRNA

Transfer RNAs (tRNAs) play a central role in translation and also recently appear to have a variety of other functions in biological processes beyond translation. Here we report the development of Four-Leaf clover qRT-PCR (FL-PCR), a convenient PCR-based method, which can specifically quantify individual mature tRNA species. In FL-PCR, T4 RNA ligase 2 specifically ligates a stem-loop adapter to mature tRNAs but not to precursor tRNAs or tRNA fragments. Subsequent TaqMan qRT-PCR amplifies only unmodified regions of the tRNA-adapter ligation products; therefore, FL-PCR quantification is not influenced by tRNA post-transcriptional modifications. FL-PCR has broad applicability for the quantification of various tRNAs in different cell types, and thus provides a much-needed simple method for analyzing tRNA abundance and heterogeneity.

Mitochondrial tRNA-lookalikes in nuclear chromosomes: could they be functional?

The presence in human nuclear chromosomes of multiple sequences that are highly similar to human mitochondrial tRNAs (tRNA-lookalikes) raises intriguing questions about the possible functionality of these genomic loci. In this perspective, we explore the significance of the mitochondrial tRNA-lookalikes based on a series of properties that argue for their non-accidental nature. We particularly focus on the possibility of transcription as well as on potential functional roles for these sequences that can range from their acting as DNA regulatory elements to forming functional mature tRNAs or tRNA-derived fragments. Extension of our analysis to other simians (chimp, gorilla, rhesus, and squirrel monkey), 2 rodents (mouse and rat), a marsupial (opossum) and 3 invertebrates (fruit-fly, worm, and sponge) revealed that mitochondrial tRNA-lookalikes are prevalent in primates and the opossum but absent from the other analyzed organisms.

Beyond the one-locus-one-miRNA paradigm: microRNA isoforms enable deeper insights into breast cancer heterogeneity

Here we describe our study of miRNA isoforms (isomiRs) in breast cancer (BRCA) and normal breast data sets from the Cancer Genome Atlas (TCGA) repository. We report that the full isomiR profiles, from both known and novel human-specific miRNA loci, are particularly rich in information and can distinguish tumor from normal tissue much better than the archetype miRNAs. IsomiR expression is also dependent on the patient's race, exemplified by miR-183-5p, several isomiRs of which are upregulated in triple negative BRCA in white but not black women. Additionally, we find that an isomiR's 5′ endpoint and length, but not the genomic origin, are key determinants of the regulation of its expression. Overexpression of distinct miR-183-5p isomiRs in MDA-MB-231 cells followed by microarray analysis revealed that each isomiR has a distinct impact on the cellular transcriptome. Parallel integrative analysis of mRNA expression from BRCA data sets of the TCGA repository demonstrated that isomiRs can distinguish between the luminal A and luminal B subtypes and explain in more depth the molecular differences between them than the archetype molecules. In conclusion, our findings provide evidence that post-transcriptional studies of BRCA will benefit from transcending the one-locus-one-miRNA paradigm and taking into account all isoforms from each miRNA locus as well as the patient's race.

Phobos: A novel software for recording rodents' behavior during the thigmotaxis and the elevated plus-maze test

Evaluation of fear and anxiety levels offers valuable insight on the impact of experimental conditions. The elevated plus-maze and the open field (thigmotactic responce) tests are two well-established behavioral procedures for the quantification of anxiety in rodents. In this study, Phobos, a novel, effective and simple application developed for recording rodents' behavior during the elevated plus-maze and the open-field test, is being presented. Phobos is able to generate all basic locomotor-related behavioral results at once, immediately after a simple manual record of the rodent's position, along with simultaneous analysis of the experiment in 5-min periods. The efficiency of Phobos is demonstrated by presenting results from the two behavioral tests showing that animal's behavior unfolds differently in each one. Phobos manages to ease the experimenter from laborious work by providing self-explanatory characteristics and a convenient way to record the behavior of the animal, while it quickly calculates all basic locomotor-related parameters, easing behavioral studies. Phobos is freely accessible at https://sourceforge.net/projects/phobosapplication/.

Nuclear and mitochondrial tRNA-lookalikes in the human genome

We are interested in identifying and characterizing loci of the human genome that harbor sequences resembling known mitochondrial and nuclear tRNAs. To this end, we used the known nuclear and mitochondrial tRNA genes (the “tRNA-Reference” set) to search for “tRNA-lookalikes” and found many such loci at different levels of sequence conservation. We find that the large majority of these tRNA-lookalikes resemble mitochondrial tRNAs and exhibit a skewed over-representation in favor of some mitochondrial anticodons. Our analysis shows that the tRNA-lookalikes have infiltrated specific chromosomes and are preferentially located in close proximity to known nuclear tRNAs (z-score ≤ −2.54, P-value ≤ 0.00394). Examination of the transcriptional potential of these tRNA-lookalike loci using public transcript annotations revealed that more than 20% of the lookalikes are transcribed as part of either known protein-coding pre-mRNAs, known lncRNAs, or known non-protein-coding RNAs, while public RNA-seq data perfectly agreed with the endpoints of tRNA-lookalikes. Interestingly, we found that tRNA-lookalikes are significantly depleted in known genetic variations associated with human health and disease whereas the known tRNAs are enriched in such variations. Lastly, a manual comparative analysis of the cloverleaf structure of several of the transcribed tRNA-lookalikes revealed no disruptive mutations suggesting the possibility that these loci give rise to functioning tRNA molecules.

Plasma metabolomic profiling suggests early indications for predisposition to latent insulin resistance in children conceived by ICSI

BACKGROUND

There have been increasing indications about an epigenetically-based elevated predisposition of assisted reproductive technology (ART) offspring to insulin resistance, which can lead to an unfavorable cardio-metabolic profile in adult life. However, the relevant long-term systematic molecular studies are limited, especially for the IntraCytoplasmic Sperm Injection (ICSI) method, introduced in 1992. In this study, we carefully defined a group of 42 prepubertal ICSI and 42 naturally conceived (NC) children. We assessed differences in their metabolic profile based on biochemical measurements, while, for a subgroup, plasma metabolomic analysis was also performed, investigating any relevant insulin resistance indices.

METHODS & RESULTS

Auxological and biochemical parameters of 42 6.8±2.1 yrs old ICSI-conceived and 42 age-matched controls were measured. Significant differences between the groups were determined using univariate and multivariate statistics, indicating low urea and low-grade inflammation markers (YKL-40, hsCRP) and high triiodothyronine (T3) in ICSI-children compared to controls. Moreover, plasma metabolomic analysis carried out for a subgroup of 10 ICSI- and 10 NC girls using Gas Chromatography-Mass Spectrometry (GC-MS) indicated clear differences between the two groups, characterized by 36 metabolites linked to obesity, insulin resistance and metabolic syndrome. Notably, the distinction between the two girl subgroups was accentuated when both their biochemical and metabolomic measurements were employed.

CONCLUSIONS

The present study contributes a large auxological and biochemical dataset of a well-defined group of pre-pubertal ICSI-conceived subjects to the research of the ART effect to the offspring's health. Moreover, it is the first time that the relevant usefulness of metabolomics was investigated. The acquired results are consistent with early insulin resistance in ICSI-offspring, paving the way for further systematic investigations. These data support that metabolomics may unravel metabolic differences before they become clinically or biochemically evident, underlining its utility in the ART research.