Search Results - EGA European Genome-Phenome Archive

COPD and neutrophils sc

Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

Study EGAS00001006322

COPD and neutrophils sc rhapsody

Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

Study EGAS00001006323

Rare coding variants in lupus risk genes

Systemic lupus erythematosus (SLE) is the prototypic systemic autoimmune disease. It is thought that many common variant gene loci of weak effect act additively to predispose to common autoimmune diseases, while the contribution of rare variants remains unclear. Here we describe that rare coding variants in lupus-risk genes are present in most SLE patients and healthy controls. We demonstrate the functional consequences of rare and low frequency missense variants in the interacting proteins BLK and BANK1, which are present alone, or in combination, in a substantial proportion of lupus patients. The rare variants found in patients, but not those found exclusively in controls, impair suppression of IRF5 and type-I IFN in human B cell lines and increase pathogenic lymphocytes in lupus-prone mice. Thus, rare gene variants are common in SLE and likely contribute to genetic risk.

Study EGAS00001003548

Short and long-read sequencing of Brugada syndrome samples

Genome-wide association studies (GWAS) are instrumental in identifying loci with an impact on human traits and disease. Typically, however, most GWAS information is considered redundant as it is based on neighboring single-nucleotide variants (SNVs) in strong linkage disequilibrium (LD). In this context, besides the most significant hit (lead SNV) in every trait- or disease-associated locus, the rest of GWAS hits are often marginally reported, examined, or exploited. To interrogate the value of integrating the information provided by the full set of GWAS hits and fine-mapping haplotypes containing these SNVs, here we focused on a locus repeatedly associated with traits of the cardiac electrical conduction system and arrhythmia (SCN5A-SCN10A). We found that the same SNV can exhibit differing associations depending on haplotype. Thus, these analyses provide corroborative evidence that assuming redundancy among neighboring GWAS hits has the risk of missing critical disease-risk associations.

Study EGAS00001004927

RNA stability controlled by m6A methylation contributes to X-to-autosome dosage compensation in mammals

In mammals, X-chromosomal genes are expressed from a single copy since males (XY) possess a single X chromosome, while females (XX) undergo X inactivation. To compensate for this reduction in dosage compared to two active copies of autosomes, it has been proposed that genes from the active X chromosome exhibit dosage compensation. However, the existence and mechanism of X-to-autosome dosage compensation are still under debate. Here, we show that X-chromosomal transcripts are reduced in m6A modifications and more stable compared to their autosomal counterparts. Acute depletion of m6A selectively stabilises autosomal transcripts, resulting in perturbed dosage compensation in mouse embryonic stem cells. We propose that higher stability of X-chromosomal transcripts is directed by lower levels of m6A, indicating that mammalian dosage compensation is partly regulated by epitranscriptomic RNA modifications.

Study EGAS00001007112

Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and lethal tumor in adolescent and young adult patients. Currently, there is no standard-of-care treatment for these patients. Reliable models that represent this disease and can be used for translational research are scarce. To model SCCOHTs, we have established eight patient-derived tumoroid lines from tumor lesions of three patients with SCCOHT. The tumoroids recapitulate genomic and transcriptomic characteristics of the corresponding patient tumors and capture intrapatient tumor heterogeneity. Organoid drug profiling using a library of 153 clinical compounds identified methotrexate as an effective and selective drug against SCCOHTs with a clinically relevant IC50 of 35 nmol/L. RNA sequencing demonstrated that methotrexate induced TP53 pathway activation and apoptosis. These data underscore that organoid technology can support the design of therapeutic strategies for rare cancers.

Study EGAS00001007911

Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

Study EGAS00001007877

DAC for Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

Dac EGAC00001001250

UM

metabolite levels provided by UM platform (Creative Dynamics Inc, NY, USA) (the data is raw abundance. Mapping was applied on log10 transformed data)

Dataset EGAD00010002146

Center of Medical Genetics Ghent - lab BMN

This is a DAC created to contain datasets generated in lab BMN, part of the Center of Medical Genetics Ghent, Belgium.

Dac EGAC50000000351

DAC for DRS peripheral blood, University Medical Center Johannes Gutenberg University Mainz

This DAC is in relation to the DRS samples of peripheral blood of healthy control

Dac EGAC50000000667

EGAD00000000019

840 families where both parents have been genotyped together with the child with severe malaria

Dataset EGAD00000000019

Tumor sample of a serious ovarian carcinoma

Dataset EGAD00001000139

Blood sample of serious ovarian carcinoma patient

Dataset EGAD00001000140

REL-2017-07-2016

HipSci - Battens Disease - Genotyping Array - July 2017

Dataset EGAD00010001366

REL-2017-07-2007

HipSci - Kabuki Syndrome - Genotyping Array - July 2017

Dataset EGAD00010001348

REL-2017-07-2008

HipSci - Usher Syndrome - Genotyping Array - July 2017

Dataset EGAD00010001350

REL-2017-07-2009

HipSci - Alport Syndrome - Genotyping Array - July 2017

Dataset EGAD00010001352

REL-2017-07-2010

HipSci - Congenital Hyperinsulinia - Genotyping Array - July 2017

Dataset EGAD00010001354

REL-2017-07-07

HipSci - Hypertrophic Cardiomyopathy - Genotyping Array - July 2017

Dataset EGAD00010001356

REL-2017-07-2014

HipSci - Macular Dystrophy - Genotyping Array - July 2017

Dataset EGAD00010001362

REL-2017-07-2015

HipSci - Retinitis Pigmentosa - Genotyping Array - July 2017

Dataset EGAD00010001364

colon

Normal Colon Crypt - EPIC Methylation Array

Dataset EGAD00010002200

Dataset for the spanish node

Dataset EGAD50000000884

KUI7051

Nanopore pericentromere normal methylation

Dataset EGAD00001009885

Transcriptome

Transcriptome from EGAS00001001846

Dataset EGAD00001002163

Novel driver variants in the histone 3.3 genes, H3F3A and H3F3B, define bone and cartilage cancer sub-types

A selection of human cancers harbours somatic driver mutations in genes encoding histones, most notably childhood brain tumours with K27M substitutions of the histone 3.3 gene, H3F3A. We performed whole genome sequencing of the benign cartilage tumour, chondroblastoma, and targeted sequencing of histone 3.3 genes, H3F3A and H3F3B, in seven further skeletal tumour types. We identified an exceptionally high prevalence of novel histone 3.3 driver mutations at glycine 34 and at lysine 36. Histone 3.3 gene mutations were found in 91% in giant cell tumours of bone (48/53), mainly H3F3A G34W variants, and in 92% of chondroblastoma (73/79), predominantly K36M mutations in H3F3B. H3F3B is paralogous to the cancer gene H3F3A. However, H3F3B driver variants have not previously been reported in human cancer. Our observation demonstrate remarkable tumour-specificity of mutations, with respect to which histone 3.3 gene and residue is mutated, indicating that the advantage these mutations confer is tumour dependent. Moreover, tumour-specific mutation of H3F3A and H3F3B suggests, that although both genes encode identical proteins, they are likely non-redundant and employed differentially during skeletal development.

Dataset EGAD00001000646

Hypermutation of the inactive X chromosome is a frequent event in cancer

Mutation is a fundamental process in tumorigenesis. However the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. As part of the ICGC PedBrain and Malignant Lymphoma (MMML-Seq) consortium we performed a cross-cancer comparison of whole genomes comprising a diverse set of childhood and adult tumors including both solid and hematopoietic malignancies. In addition we performed whole genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals to compare somatic mutation rates.

Study EGAS00001000565

Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing

scGBS is a single-cell sequencing-based methodology to haplotype and copy-number profile single cells. Genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing of the restriction fragments. scGBS data serves as the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping (Zamani Esteki et al., 2015). We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells with the use of a HapMap cell line pedigree (7 single cells). A clinical validation of the methodology with a total of 14 single blastomeres and 3 trophectoderm samples biopsies from human preimplantation embryos for 6 PGT-M families were processed with scGBS and were previously haploptyped via SNP array.

Dataset EGAD00001007794

Somatic mutations in facial skin from countries of contrasting skin cancer risk

The incidence of non-melanoma skin cancer is 17-fold lower in Singapore compared to the UK1, despite Singapore receiving 2-3 times more year-round ultraviolet radiation (UV)2,3. The ageing epidermis of the skin comprises competing somatic mutant clones4,5, from which such cancers develop. We question if differences in keratinocyte skin cancer incidence are reflected in the mutational landscape by comparing ageing facial epidermis from donors of Singapore and the UK. We find UK skin to be a highly competitive, densely mutated landscape with 4-fold greater mutation burden compared to Singaporean skin and differences in clonal selection by country. We disproportionately observe multiple features common to keratinocyte skin cancers6,7,8 in UK skin, such as UV mutagenesis, copy number aberration and hotspot mutations (in particular TP53 R248W). We conclude that keratinocyte skin cancer incidence is reflected in the somatic clones of non-cancerous epidermis. Finally, we re-analyse squamous cell carcinoma exomes from Korea9 to show, even in low incidence populations, carcinogenesis is driven by UV damage.

Dataset EGAD00001009666

A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

Abstract: Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cancer cell trajectory regionalizes tumours into distinct tissue niches and manifests in a conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to jointly map cancer cell states and clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

Dataset EGAD00001015516

Assessment of epigenetic variation in human iPS cells-Medip

n order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The methylation status of these iPS cells will be compared. Protocol: Primary cell cultures were generated and reprogrammed to iPS cells. DNA was extracted and immunoprecipitated using anti-methyl cytosine and anti-hydroxymethyl cytosine antibodies. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001000827

Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene independent manner. In contrast, amplifications caused by whole chromosomal duplications have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

Dataset EGAD00001004124

Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

Dataset EGAD00001000394

The mutational landscape of normal human endometrial epithelium - Additional Samples

All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

Dataset EGAD00001005214

Transcriptional mechanisms of resistance to anti-PD-1 therapy

Purpose: To explore factors associated with response and resistance to anti-PD-1 therapy, we analyzed multiple disease sites at autopsy in a patient with widely metastatic melanoma who had a heterogeneous response.Materials and Methods: Twenty-six melanoma specimens (four pre-mortem, 22 post-mortem) were subjected to whole-exome sequencing. Candidate immunologic markers and gene expression were assessed in ten cutaneous metastases showing response or progression during therapy.Results: The melanoma was driven by biallelic inactivation of NF1. All lesions had highly concordant mutational profiles and copy number alterations, indicating linear clonal evolution. Expression of candidate immunologic markers was similar in responding and progressing lesions. However, progressing cutaneous metastases were associated with over-expression of genes associated with extracellular matrix and neutrophil function.Conclusions: Although mutational and immunologic differences have been proposed as the primary determinants of heterogeneous response/resistance to targeted therapies and immunotherapies, respectively, differential lesional gene expression profiles may also dictate anti-PD-1 outcomes.

Study EGAS00001002195

Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab

We report herein an extensive exploratory biomarker analysis of refractory tumors taken from pediatric patients prior to receiving atezolizumab monotherapy in the phase 1-2 iMATRIX-atezolizumab trial (NCT02541604). A high percentage of CD8+ T cells and elevated protein levels of programmed cell death ligand 1 (PD-L1) were associated with progression-free survival (PFS). T-cell receptor (TCR) sequencing revealed that diverse infiltrating TCR repertoire at baseline was prognostic. We found no associations between panel-based tumor mutation burden (TMB) or specific genetic aberrations with PFS in this study. Through a pan-cancer gene co-expression network analysis, we developed a novel tumor-agnostic Pediatric Cytotoxicity and Antigen Presentation (PedCAP) signature that was associated with improved PFS in the iMATRIX-atezo study. Our study highlights features of immune response in pediatric cancers when treated with immune checkpoint inhibitors and provides a multi-biomarker pediatric immunogram framework to guide prospective clinical trials in pediatric cancers.

Study EGAS00001006004

Single-cell RNA sequencing of sorted regulatory T cells

Single-cell RNA sequencing of flow cytometry enriched CD4+ CD127- CD25+ regulatory T cells from 8 systemic lupus erythematosus patients (SLE_001 to SLE_007, and SLE_009) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform (incl. generation of TCR libraries). Samples from patients SLE_001, SLE_002, SLE_004, SLE_006 were collected and processed on the first day of experiment (Day 1), and samples from patients SLE_003, SLE_005, SLE_007, SLE_009 on the second day of experiment (Day 2). On each day, samples were pooled and distributed to four lanes on the chromium controller. Run ID 245269 and ID 245270 identify samples sequenced on separate flow cells. Provided are raw sequencing files.

Dataset EGAD50000000663

Targeted plasma cell-free DNA sequencing for tissue-of-origin determination and donor-derived cell-free DNA quantification in organ transplant recipients and healthy controls

The dataset comprises targeted deep methylation sequencing data used for both tissue-of-origin determination and donor-derived cfDNA quantification. It includes plasma cfDNA data from stable kidney transplant recipients (n = 31), stable liver transplant recipients (n = 20) and healthy controls (n = 23). In addition, plasma cfDNA samples collected early after transplantation were analyzed from kidney transplant recipients (n = 44) and liver transplant recipients (n = 40). The dataset also features genomic DNA data generated from whole blood (n = 10) and buffy coat (n = 3) from healthy controls, as well as from T cells (n = 1), B cells (n = 2), hepatocytes (n = 1) and kidney epithelium (n = 1). Lastly, genomic DNA data was generated from buffy coat of transplant recipients (n = 17). Here, “n” indicates the sample number.

Dataset EGAD50000001446

How upcycled prostate cancer sequences enabled key findings on telomeres length

The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

Tumor-specific expression of let-7i and miR-192 is associated with resistance to cisplatin-based chemoradiotherapy in patients with larynx and hypopharynx cancer

Background: The majority of patients with locally advanced larynx or hypopharynx squamous cell carcinoma are treated with organ preserving chemoradiotherapy (CRT). Clinical outcome following CRT varies greatly. We hypothesized tumor microRNA (miRNA) expression is predictive for outcome following CRT. Methods: Next-generation sequencing (NGS) miRNA profiling was performed on 37 formalin fixed paraffin embedded (FFPE) tumor samples. Patients with a recurrence free survival (RFS) of less than 2 years (“poor outcome”) and patients without recurrence within 2 years (“good outcome”) were compared by differential expression analysis. Tumor-specific miRNAs were selected based on normal mucosa miRNA expression data from The Cancer Genome Atlas database. A model was constructed to predict outcome using group-regularized penalized logistic ridge regression. Candidate miRNAs were validated in the initial sample set by RT-qPCR as well as in 46 additional tumor samples.Results: 1,938 known mature miRNAs were detected. Thirteen miRNAs were differentially expressed (p<0.05, FDR<0.1) according to outcome group. Initial class prediction in the NGS cohort (n=37) resulted in a model combining five miRNAs and disease stage, able to predict CRT outcome with an area under the curve (AUC) of 0.82. In the RT-qPCR cohort (n=83), 25 patients (30%) experienced early recurrence (median RFS 8 months; median follow-up 42 months). Class prediction resulted in a model combining let-7i-5p and miR-192-5p and disease stage, able to discriminate with an AUC of 0.80 patients with good versus poor clinical outcome.Conclusion: The combined miRNA expression and disease stage prediction model is superior to using either factor alone. ¬¬¬This study indicates NGS miRNA profiling using FFPE specimens is feasible, resulting in clinically relevant biomarkers.

Study EGAS00001004001

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