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Article: Data-Driven Medicine in the Diagnosis and Treatment of Infertility.

de Santiago, Ines / Polanski, Lukasz

2022 Volume 11, Issue 21

Abstract: Infertility, although not a life-threatening condition, affects around 15% of couples trying for a pregnancy. The increasing availability of large datasets from various sources, together with advances in machine learning (ML) and artificial intelligence ( ...

Abstract	Infertility, although not a life-threatening condition, affects around 15% of couples trying for a pregnancy. The increasing availability of large datasets from various sources, together with advances in machine learning (ML) and artificial intelligence (AI), are enabling a transformational change in infertility care. However, real-world applications of data-driven medicine in infertility care are still relatively limited. At present, very little can prevent infertility from arising; more work is required to learn about ways to improve natural conception and the detection and diagnosis of infertility, improve assisted reproduction treatments (ART) and ultimately develop useful clinical-decision support systems to assure the successful outcome of either fertility preservation or infertility treatment. In this opinion article, we discuss recent influential work on the application of big data and AI in the prevention, diagnosis and treatment of infertility. We evaluate the challenges of the sector and present an interpretation of the different innovation forces that are driving the emergence of a systems approach to infertility care. Efforts including the integration of multi-omics information, collection of well-curated biological samples in specialised biobanks, and stimulation of the active participation of patients are considered. In the era of Big Data and AI, there is now an exciting opportunity to leverage the progress in genomics and digital technologies and develop more sophisticated approaches to diagnose and treat infertility disorders.
Language	English
Publishing date	2022-10-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm11216426
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Article ; Online: Analysis of ChIP-seq Data in R/Bioconductor.

de Santiago, Ines / Carroll, Thomas

Methods in molecular biology (Clifton, N.J.)

2017 Volume 1689, Page(s) 195–226

Abstract: The development of novel high-throughput sequencing methods for ChIP (chromatin immunoprecipitation) has provided a very powerful tool to study gene regulation in multiple conditions at unprecedented resolution and scale. Proactive quality-control and ... ...

Abstract	The development of novel high-throughput sequencing methods for ChIP (chromatin immunoprecipitation) has provided a very powerful tool to study gene regulation in multiple conditions at unprecedented resolution and scale. Proactive quality-control and appropriate data analysis techniques are of critical importance to extract the most meaningful results from the data. Over the last years, an array of R/Bioconductor tools has been developed allowing researchers to process and analyze ChIP-seq data. This chapter provides an overview of the methods available to analyze ChIP-seq data based primarily on software packages from the open-source Bioconductor project. Protocols described in this chapter cover basic steps including data alignment, peak calling, quality control and data visualization, as well as more complex methods such as the identification of differentially bound regions and functional analyses to annotate regulatory regions. The steps in the data analysis process were demonstrated on publicly available data sets and will serve as a demonstration of the computational procedures routinely used for the analysis of ChIP-seq data in R/Bioconductor, from which readers can construct their own analysis pipelines.
MeSH term(s)	Animals ; Chromatin Immunoprecipitation/methods ; Computational Biology/methods ; Data Interpretation, Statistical ; Databases, Nucleic Acid ; High-Throughput Nucleotide Sequencing/methods ; Mice ; Sequence Analysis, DNA ; Software ; Workflow
Language	English
Publishing date	2017-10-09
Publishing country	United States
Document type	Journal Article
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-4939-7380-4_17
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Article ; Online: Smoking-associated gene expression alterations in nasal epithelium reveal immune impairment linked to lung cancer risk.

de Biase, Maria Stella / Massip, Florian / Wei, Tzu-Ting / Giorgi, Federico M / Stark, Rory / Stone, Amanda / Gladwell, Amy / O'Reilly, Martin / Schütte, Daniel / de Santiago, Ines / Meyer, Kerstin B / Markowetz, Florian / Ponder, Bruce A J / Rintoul, Robert C / Schwarz, Roland F

Genome medicine

2024 Volume 16, Issue 1, Page(s) 54

Abstract: Background: Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to modifiable lifestyle risk in the form of tobacco smoke has long been established. More than 50% of all smoking- ... ...

Abstract	Background: Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to modifiable lifestyle risk in the form of tobacco smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, 40% of which occur more than 15 years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk remain unclear. We thus set out to examine whether risk stratification in the clinic and in the general population can be improved upon by the addition of genetic data and to explore the mechanisms of the persisting risk in former smokers. Methods: We analysed transcriptomic data from accessible airway tissues of 487 subjects, including healthy volunteers and clinic patients of different smoking statuses. We developed a computational model to assess smoking-associated gene expression changes and their reversibility after smoking is stopped, comparing healthy subjects to clinic patients with and without lung cancer. Results: We find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune- and interferon-related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Conclusions: Our results provide initial evidence for germline-mediated personalized smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.
MeSH term(s)	Humans ; Lung Neoplasms/genetics ; Lung Neoplasms/metabolism ; Smoking/adverse effects ; Smoking/genetics ; Lung/metabolism ; Nicotiana ; Nasal Mucosa/metabolism ; Transcriptome
Language	English
Publishing date	2024-04-08
Publishing country	England
Document type	Journal Article
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-024-01317-4
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Article ; Online: Master Regulators of Oncogenic KRAS Response in Pancreatic Cancer: An Integrative Network Biology Analysis.

Sivakumar, Shivan / de Santiago, Ines / Chlon, Leon / Markowetz, Florian

PLoS medicine

2017 Volume 14, Issue 1, Page(s) e1002223

Abstract: Background: KRAS is the most frequently mutated gene in pancreatic ductal adenocarcinoma (PDAC), but the mechanisms underlying the transcriptional response to oncogenic KRAS are still not fully understood. We aimed to uncover transcription factors that ... ...

Abstract	Background: KRAS is the most frequently mutated gene in pancreatic ductal adenocarcinoma (PDAC), but the mechanisms underlying the transcriptional response to oncogenic KRAS are still not fully understood. We aimed to uncover transcription factors that regulate the transcriptional response of oncogenic KRAS in pancreatic cancer and to understand their clinical relevance. Methods and findings: We applied a well-established network biology approach (master regulator analysis) to combine a transcriptional signature for oncogenic KRAS derived from a murine isogenic cell line with a coexpression network derived by integrating 560 human pancreatic cancer cases across seven studies. The datasets included the ICGC cohort (n = 242), the TCGA cohort (n = 178), and five smaller studies (n = 17, 25, 26, 36, and 36). 55 transcription factors were coexpressed with a significant number of genes in the transcriptional signature (gene set enrichment analysis [GSEA] p < 0.01). Community detection in the coexpression network identified 27 of the 55 transcription factors contributing to three major biological processes: Notch pathway, down-regulated Hedgehog/Wnt pathway, and cell cycle. The activities of these processes define three distinct subtypes of PDAC, which demonstrate differences in survival and mutational load as well as stromal and immune cell composition. The Hedgehog subgroup showed worst survival (hazard ratio 1.73, 95% CI 1.1 to 2.72, coxPH test p = 0.018) and the Notch subgroup the best (hazard ratio 0.62, 95% CI 0.42 to 0.93, coxPH test p = 0.019). The cell cycle subtype showed highest mutational burden (ANOVA p < 0.01) and the smallest amount of stromal admixture (ANOVA p < 2.2e-16). This study is limited by the information provided in published datasets, not all of which provide mutational profiles, survival data, or the specifics of treatment history. Conclusions: Our results characterize the regulatory mechanisms underlying the transcriptional response to oncogenic KRAS and provide a framework to develop strategies for specific subtypes of this disease using current therapeutics and by identifying targets for new groups.
MeSH term(s)	Animals ; Cell Line ; Gene Expression Regulation, Neoplastic ; Humans ; Mice ; Pancreatic Neoplasms/genetics ; Proto-Oncogene Proteins p21(ras)/genetics ; Proto-Oncogene Proteins p21(ras)/metabolism ; Transcription Factors
Chemical Substances	KRAS protein, human ; Transcription Factors ; Hras protein, mouse (EC 3.6.5.2) ; Proto-Oncogene Proteins p21(ras) (EC 3.6.5.2)
Language	English
Publishing date	2017-01-31
Publishing country	United States
Document type	Journal Article
ZDB-ID	2185925-5
ISSN	1549-1676 ; 1549-1277
ISSN (online)	1549-1676
ISSN	1549-1277
DOI	10.1371/journal.pmed.1002223
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Article ; Online: Immunophenotypes of pancreatic ductal adenocarcinoma: Meta-analysis of transcriptional subtypes.

de Santiago, Ines / Yau, Christopher / Heij, Lara / Middleton, Mark R / Markowetz, Florian / Grabsch, Heike I / Dustin, Michael L / Sivakumar, Shivan

International journal of cancer

2019 Volume 145, Issue 4, Page(s) 1125–1137

Abstract: Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5-year survival rate of <5%. Recent studies of PDAC have provided several transcriptomic ... ...

Abstract	Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5-year survival rate of <5%. Recent studies of PDAC have provided several transcriptomic classifications based on separate analyses of individual patient cohorts. There is a need to provide a unified transcriptomic PDAC classification driven by therapeutically relevant biologic rationale to inform future treatment strategies. Here, we used an integrative meta-analysis of 353 patients from four different studies to derive a PDAC classification based on immunologic parameters. This consensus clustering approach indicated transcriptomic signatures based on immune infiltrate classified as adaptive, innate and immune-exclusion subtypes. This reveals the existence of microenvironmental interpatient heterogeneity within PDAC and could serve to drive novel therapeutic strategies in PDAC including immune modulation approaches to treating this disease.
MeSH term(s)	Adenocarcinoma/genetics ; Adenocarcinoma/pathology ; Carcinoma, Pancreatic Ductal/genetics ; Carcinoma, Pancreatic Ductal/pathology ; Cluster Analysis ; Gene Expression Regulation, Neoplastic/genetics ; Humans ; Immunophenotyping/methods ; Pancreatic Neoplasms/genetics ; Pancreatic Neoplasms/pathology ; Prognosis ; Transcription, Genetic/genetics ; Transcriptome/genetics
Language	English
Publishing date	2019-03-18
Publishing country	United States
Document type	Journal Article ; Meta-Analysis ; Research Support, Non-U.S. Gov't
ZDB-ID	218257-9
ISSN	1097-0215 ; 0020-7136
ISSN (online)	1097-0215
ISSN	0020-7136
DOI	10.1002/ijc.32186
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Article: Impact of artifact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data.

Carroll, Thomas S / Liang, Ziwei / Salama, Rafik / Stark, Rory / de Santiago, Ines

Frontiers in genetics

2014 Volume 5, Page(s) 75

Abstract: With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-seq throughput, the development of working standards for the quality assessment of ChIP-seq studies has received significant attention. The ENCODE consortium's ... ...

Abstract	With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-seq throughput, the development of working standards for the quality assessment of ChIP-seq studies has received significant attention. The ENCODE consortium's large scale analysis of transcription factor binding and epigenetic marks as well as concordant work on ChIP-seq by other laboratories has established a new generation of ChIP-seq quality control measures. The use of these metrics alongside common processing steps has however not been evaluated. In this study, we investigate the effects of blacklisting and removal of duplicated reads on established metrics of ChIP-seq quality and show that the interpretation of these metrics is highly dependent on the ChIP-seq preprocessing steps applied. Further to this we perform the first investigation of the use of these metrics for ChIP-exo data and make recommendations for the adaptation of the NSC statistic to allow for the assessment of ChIP-exo efficiency.
Language	English
Publishing date	2014-04-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2014.00075
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Article: BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes

de Santiago, Ines / Chilamakuri, Chandra Sekhar Reddy / Liu, Wei / Markowetz, Florian / Meyer, Kerstin B / O’Reilly, Martin / Ponder, Bruce A. J / Yuan, Ke

Genome biology. 2017 Dec., v. 18, no. 1

2017

Abstract: Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods of detecting an allelic imbalance ... ...

Abstract	Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods of detecting an allelic imbalance assume diploid genomes. This assumption severely limits their applicability to cancer samples with frequent DNA copy-number changes. Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of background allele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and six targeted FAIRE-seq samples, we show that BaalChIP effectively corrects allele-specific analysis for copy-number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.
Keywords	Bayesian theory ; diploidy ; DNA ; gene frequency ; genome ; neoplasms ; phenotypic variation ; statistical analysis ; transcription factors
Language	English
Dates of publication	2017-12
Size	p. 39.
Publishing place	BioMed Central
Document type	Article
ZDB-ID	2040529-7
ISSN	1474-760X ; 1465-6914 ; 1465-6906
ISSN (online)	1474-760X ; 1465-6914
ISSN	1465-6906
DOI	10.1186/s13059-017-1165-7
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Article ; Online: Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

Martins, Filipe Correia / Couturier, Dominique-Laurent / de Santiago, Ines / Sauer, Carolin Margarethe / Vias, Maria / Angelova, Mihaela / Sanders, Deborah / Piskorz, Anna / Hall, James / Hosking, Karen / Amirthanayagam, Anumithra / Cosulich, Sabina / Carnevalli, Larissa / Davies, Barry / Watkins, Thomas B K / Funingana, Ionut G / Bolton, Helen / Haldar, Krishnayan / Latimer, John /

Baldwin, Peter / Crawford, Robin / Eldridge, Matthew / Basu, Bristi / Jimenez-Linan, Mercedes / Mcpherson, Andrew W / McGranahan, Nicholas / Litchfield, Kevin / Shah, Sohrab P / McNeish, Iain / Caldas, Carlos / Evan, Gerard / Swanton, Charles / Brenton, James D

Nature communications

2022 Volume 13, Issue 1, Page(s) 6360

Abstract: Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes ... ...

Abstract	Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identify five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reason that their strong selection should prioritise them as key biomarkers for targeted therapies. We use primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number is associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC is statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway is independently observed in squamous lung cancer and triple negative breast cancer. In this work, we show that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.
MeSH term(s)	Humans ; Female ; Ovarian Neoplasms/drug therapy ; Ovarian Neoplasms/genetics ; Ovarian Neoplasms/pathology ; DNA Copy Number Variations ; Phosphatidylinositol 3-Kinases/genetics ; Phosphatidylinositol 3-Kinases/metabolism ; Proto-Oncogene Proteins p21(ras)/genetics ; Cystadenocarcinoma, Serous/drug therapy ; Cystadenocarcinoma, Serous/genetics ; Cystadenocarcinoma, Serous/metabolism ; Class I Phosphatidylinositol 3-Kinases/genetics ; Class I Phosphatidylinositol 3-Kinases/metabolism ; Paclitaxel/therapeutic use ; TOR Serine-Threonine Kinases/genetics ; TOR Serine-Threonine Kinases/metabolism ; Mechanistic Target of Rapamycin Complex 1/metabolism
Chemical Substances	Phosphatidylinositol 3-Kinases (EC 2.7.1.-) ; Proto-Oncogene Proteins p21(ras) (EC 3.6.5.2) ; Class I Phosphatidylinositol 3-Kinases (EC 2.7.1.137) ; Paclitaxel (P88XT4IS4D) ; TOR Serine-Threonine Kinases (EC 2.7.11.1) ; Mechanistic Target of Rapamycin Complex 1 (EC 2.7.11.1)
Language	English
Publishing date	2022-10-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-33870-0
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Article ; Online: Eukaryotic gene regulation in three dimensions and its impact on genome evolution.

Babu, M Madan / Janga, Sarath Chandra / de Santiago, Ines / Pombo, Ana

Current opinion in genetics & development

2008 Volume 18, Issue 6, Page(s) 571–582

Abstract: Recent advances in molecular techniques and high-resolution imaging are beginning to provide exciting insights into the higher order chromatin organization within the cell nucleus and its influence on eukaryotic gene regulation. This improved ... ...

Abstract	Recent advances in molecular techniques and high-resolution imaging are beginning to provide exciting insights into the higher order chromatin organization within the cell nucleus and its influence on eukaryotic gene regulation. This improved understanding of gene regulation also raises fundamental questions about how spatial features might have constrained the organization of genes on eukaryotic chromosomes and how mutations that affect these processes might contribute to disease conditions. In this review, we discuss recent studies that highlight the role of spatial components in gene regulation and their impact on genome evolution. We then address implications for human diseases and outline new directions for future research.
MeSH term(s)	Aging/genetics ; Animals ; Computational Biology/methods ; Eukaryotic Cells ; Evolution, Molecular ; Gene Expression Regulation/genetics ; Gene Regulatory Networks/genetics ; Genetic Diseases, Inborn/genetics ; Genome/genetics ; Humans ; Models, Genetic
Language	English
Publishing date	2008-11-27
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1077312-5
ISSN	1879-0380 ; 0959-437X
ISSN (online)	1879-0380
ISSN	0959-437X
DOI	10.1016/j.gde.2008.10.002
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Article ; Online: Active and poised promoter states drive folding of the extended HoxB locus in mouse embryonic stem cells.

Barbieri, Mariano / Xie, Sheila Q / Torlai Triglia, Elena / Chiariello, Andrea M / Bianco, Simona / de Santiago, Inês / Branco, Miguel R / Rueda, David / Nicodemi, Mario / Pombo, Ana

Nature structural & molecular biology

2017 Volume 24, Issue 6, Page(s) 515–524

Abstract: Gene expression states influence the 3D conformation of the genome through poorly understood mechanisms. Here, we investigate the conformation of the murine HoxB locus, a gene-dense genomic region containing closely spaced genes with distinct activation ... ...

Abstract	Gene expression states influence the 3D conformation of the genome through poorly understood mechanisms. Here, we investigate the conformation of the murine HoxB locus, a gene-dense genomic region containing closely spaced genes with distinct activation states in mouse embryonic stem (ES) cells. To predict possible folding scenarios, we performed computer simulations of polymer models informed with different chromatin occupancy features that define promoter activation states or binding sites for the transcription factor CTCF. Single-cell imaging of the locus folding was performed to test model predictions. While CTCF occupancy alone fails to predict the in vivo folding at genomic length scale of 10 kb, we found that homotypic interactions between active and Polycomb-repressed promoters co-occurring in the same DNA fiber fully explain the HoxB folding patterns imaged in single cells. We identify state-dependent promoter interactions as major drivers of chromatin folding in gene-dense regions.
MeSH term(s)	Animals ; Chromatin/metabolism ; Computer Simulation ; DNA/chemistry ; DNA/metabolism ; Embryonic Stem Cells/physiology ; Fluorescent Antibody Technique ; Genetic Loci ; In Situ Hybridization, Fluorescence ; Mice ; Microscopy, Confocal ; Nucleic Acid Conformation ; Promoter Regions, Genetic ; Protein Binding ; Single-Cell Analysis ; Transcription Factors/metabolism
Chemical Substances	Chromatin ; Transcription Factors ; DNA (9007-49-2)
Language	English
Publishing date	2017-04-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	2126708-X
ISSN	1545-9985 ; 1545-9993
ISSN (online)	1545-9985
ISSN	1545-9993
DOI	10.1038/nsmb.3402
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