Article
Genetics & Heredity
Xiaoqin Huang, Akhilesh K. K. Bajpai, Jian Sun, Fuyi Xu, Lu Lu, Siamak Yousefi
Summary: The discovery of glaucoma biomarkers based on gene expression data could provide new insights for early diagnosis and treatment options. Our study applied Non-negative Matrix Factorization (NMF) to extract latent representations of RNA-seq data and identified marker genes for glaucoma using a novel gene scoring method. The NMF method significantly improved the enrichment detection of glaucoma genes and showed promise in glaucoma biomarker identification.
FRONTIERS IN GENETICS
(2023)
Article
Computer Science, Artificial Intelligence
Khanh Luong, Richi Nayak, Thirunavukarasu Balasubramaniam, Md Abul Bashar
Summary: This paper proposes a deep non-negative matrix factorization-based framework for effective multi-view data clustering by uncovering the non-linear relationships and intrinsic components of the data. The framework effectively incorporates the optimal manifold of multi-view data and outperforms existing multi-view matrix factorization-based methods.
PATTERN RECOGNITION
(2022)
Article
Computer Science, Artificial Intelligence
Gal Gilad, Itay Sason, Roded Sharan
Summary: Non-negative matrix factorization (NMF) is a popular method used to find low rank approximations of matrices, especially in genomics for interpreting mutation data. A key challenge in using NMF is determining the number of components. A new method, CV2K, is proposed in this study to automatically select this number based on cross validation and parsimony considerations. Results show that CV2K leads to improved predictions compared to previous approaches, even those involving human assessment.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY
(2021)
Article
Multidisciplinary Sciences
Mikio Shiga, Shigeto Seno, Makoto Onizuka, Hideo Matsuda
Summary: Single-cell RNA sequencing technology allows us to understand biological processes at unprecedented resolution, but it requires a complex data processing pipeline. Unsupervised cell clustering plays a crucial role in identifying cell types, discovering cell diversity, and subpopulations. The use of different quantification methods to process gene expression profiles can significantly impact clustering results.
Article
Cell Biology
Kaiyuan Xing, Bo Zhang, Zixuan Wang, Yanru Zhang, Tengyue Chai, Jingkai Geng, Xuexue Qin, Xi Steven Chen, Xinxin Zhang, Chaohan Xu
Summary: By using single-cell RNA-seq and bioinformatics approach, we identified TNBC subtype-specific prognosis signatures and confirmed their association with cancer development. Further validation demonstrated the potential of these signatures as prognostic markers for individualized treatment of TNBC patients.
Article
Engineering, Multidisciplinary
Hao Jiang, Ming Yi, Shihua Zhang
Summary: This study introduces a novel approach based on kernel non-negative matrix factorization to detect nonlinear gene-gene relationships and build a low-dimensional representation on the original data. Furthermore, an efficient method for determining the optimal cluster number is proposed to improve clustering accuracy.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Environmental Sciences
Min Zhang, Jun Shi, Huiping Deng
Summary: This study found that microplastics caused inflammatory damage and histological changes in the heart tissue of mice. It also discovered the role of m6A modification in gene expression in microplastic-induced cardiotoxicity, providing new insights into the chronic toxicity of microplastic exposure on the heart.
Article
Computer Science, Information Systems
Anmin Fu, Zhenzhu Chen, Yi Mu, Willy Susilo, Yinxia Sun, Jie Wu
Summary: This paper presents a novel outsourced scheme for Non-negative Matrix Factorization (O-NMF) to alleviate clients' computing burden and address data privacy and verification issues when outsourcing NMF.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Biochemistry & Molecular Biology
Teng Huang, Jiaheng Li, San Ming Wang
Summary: Abnormal gene expression plays a key role in cancer development. We hypothesized that in cancer, core promoter sequences could be mutated to interfere with transcriptional factors' interaction, resulting in altered transcriptional initiation, abnormal gene expression, and cancer development. Using triple-negative breast cancer (TNBC) as a model, we identified somatic and germline variants in core promoters of genes that affect gene expression and validated the findings. Comparison with core promoter variation data from unclassified breast cancer revealed TNBC-specific core promoter variants. This study demonstrates the mutability of core promoters in cancer and their impact on transcriptional initiation in TNBC and other cancer types.
Article
Physics, Applied
Hua Yu, Ziteng Wang, Mana Nemoto, Kazuyuki Suzuta, Len Ito, Shin-ichi Morita
Summary: Research has shown that NMF used in biological data analysis has limitations in providing unique decomposition, but by visualizing the possible ranges of NMF in a binary system, the mechanism has been clarified and new research perspectives have been opened up.
APPLIED PHYSICS EXPRESS
(2021)
Article
Instruments & Instrumentation
Kirsty Milligan, Kendra Scarrott, Jeffrey L. Andrews, Alexandre G. Brolo, Julian J. Lum, Andrew Jirasek
Summary: Raman spectroscopy is a useful tool for obtaining biochemical information, but interpreting the data can be challenging. Our group has demonstrated a non-negative matrix factorization framework as an alternative to dimensionality reduction techniques for Raman spectroscopy data related to radiation response monitoring. We evaluated the accuracy of the model in reconstructing mixture solutions of known concentrations and considered factors such as spectral bases, noise thresholds, and different biochemical groups. Overall, the model performed well and solid bases spectra were comparable to solution bases spectra. The inclusion of an unconstrained component did not significantly affect the deconstruction, as long as all biochemicals were included in the model.
APPLIED SPECTROSCOPY
(2023)
Article
Biochemical Research Methods
Sini Junttila, Johannes Smolander, Laura L. Elo
Summary: This study compared 18 methods for identifying differential states (DS) changes between conditions in multisubject scRNA-seq data, and found that pseudobulk methods and mixed models performed best, showing superior statistical performance compared to naive single-cell methods.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Qingwang Chen, Yaqing Liu, Yuechen Gao, Ruolan Zhang, Wanwan Hou, Zehui Cao, Yi-Zhou Jiang, Yuanting Zheng, Leming Shi, Ding Ma, Jingcheng Yang, Zhi-Ming Shao, Ying Yu
Summary: The study presents a molecular subtyping method for triple-negative breast cancer and provides a multiomics dataset consisting of clinical, genomic, and transcriptomic information. This work contributes to a better understanding of the mechanisms of this breast cancer type, identification of actionable targets, and offers a user-friendly database for data access and exploration.
Article
Biotechnology & Applied Microbiology
Liang Zong, Yabing Zhu, Yuan Jiang, Ying Xia, Qun Liu, Sanjie Jiang
Summary: RNA-Seq analysis of FFPE samples is a highly effective approach but degradation of RNAs limits its application. A new RNA-Seq method has been developed to overcome this limitation. This study compares and evaluates three commercially available exome capture kits, providing valuable guidance for obtaining high-quality data from FFPE samples.
Review
Biochemical Research Methods
Amarinder Singh Thind, Isha Monga, Prasoon Kumar Thakur, Pallawi Kumari, Kiran Dindhoria, Monika Krzak, Marie Ranson, Bruce Ashford
Summary: Innovations in next-generation sequencing techniques and bioinformatics tools have revolutionized our understanding of RNA. Bulk RNA-Seq data is commonly used to study gene expression, isoform expression, alternative splicing, and more, with hidden biological information such as copy number alterations and presence of neoantigens also being extracted. Advanced bioinformatic algorithms have expanded the capacity to retrieve this hidden biological information, positioning bulk RNA-Seq as a powerful tool for providing biological insights.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Oncology
Barrie Peck, Philip Bland, Ioanna Mavrommati, Gareth Muirhead, Hannah Cottom, Patty T. Wai, Sarah L. Maguire, Holly E. Barker, Eamonn Morrison, Divya Kriplani, Lu Yu, Amy Gibson, Giulia Falgari, Keith Brennan, Gillian Farnie, Richard Buus, Rebecca Marlow, Daniela Novo, Eleanor Knight, Naomi Guppy, Daniela Kolarevic, Snezana Susnjar, Natasa Medic Milijic, Kalnisha Naidoo, Patrycja Gazinska, Ioannis Roxanis, Sunil Pancholi, Lesley-Ann Martin, Erle M. Holgersen, Maggie C. U. Cheang, Farzana Noor, Sophie Postel-Vinay, Gerard Quinn, Simon McDade, Lukas Krasny, Paul Huang, Frances Daley, Fredrik Wallberg, Jyoti S. Choudhary, Syed Haider, Andrew N. Tutt, Rachael Natrajan
Summary: This study highlights the identification of CREBBP as a novel driver in aggressive TNBC, with associated genetic vulnerability in tumor cells with alterations in CREBBP, and provides a preclinical rationale for assessing CREBBP alterations as a biomarker of CDK4/6 inhibitor response in a new patient population. Targeting CREBBP alterations with clinical CDK4/6 inhibitors selectively impairs growth in spheroids, cell line xenografts, and patient-derived models from multiple tumor types.
Article
Oncology
Caroline Conway, Denis M. Collins, Amanda McCann, Kellie Dean
Summary: The report provides an overview of research presented at the 56th annual conference of the Irish Association for Cancer Research, focusing on low-survival cancers. It emphasizes the need for new and improved treatment strategies for these challenging cancers, highlighting ongoing research efforts aimed at improving patient outcomes.
Article
Biochemistry & Molecular Biology
Mark Wappett, Adam Harris, Alexander L. R. Lubbock, Ian Lobb, Simon McDade, Ian M. Overton
Summary: Achilles' heel relationships in cancer cells can be identified using the SynLeGG tool, which analyzes omics data to discover genetic dependency relationships. The tool relies on the MultiSEp algorithm for unsupervised cell line clustering and shows favorable performance in comparison to other approaches. It also offers tissue-specific analysis and provides additional information for interpretation and drug target prioritization.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Oncology
Julia Samson, Magdalina Derlipanska, Oza Zaheed, Kellie Dean
Summary: This study conducted a molecular and cellular characterization of two patient-derived DCIS cell lines, ETCC-006 and ETCC-010, revealing differences in migration and anchorage-independent growth capabilities compared to other DCIS cell lines. Despite being isogenic, less than 30% of differentially expressed transcripts overlapped between the two lines, with enrichment in pathways involving receptor tyrosine kinases and DNA replication/cell cycle programs.
Article
Cell Biology
Oza Zaheed, Stephen J. Kiniry, Pavel V. Baranov, Kellie Dean
Summary: The detection of translation in non-coding RNAs provides an opportunity for identifying novel bioactive peptides and microproteins, with ribosome profiling and mass spectrometry being the main methods used. Public data mining is an attractive strategy for this purpose, but it requires intensive data processing. Researchers in this study used tools like OpenProt, GWIPS-viz, and Trips-Viz to explore the translation in non-coding RNAs, and found evidence suggesting that the MTLN mRNA, previously misannotated, likely encodes only a short proteoform.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Cell Biology
Baharak Ahmaderaghi, Raheleh Amirkhah, James Jackson, Tamsin R. M. Lannagan, Kathryn Gilroy, Sudhir B. Malla, Keara L. Redmond, Gerard Quinn, Simon S. McDade, Tim Maughan, Simon Leedham, Andrew S. D. Campbell, Owen J. Sansom, Mark Lawler, Philip D. Dunne
Summary: We have developed an open source data analysis platform called MouSR, which allows 'wet-lab' users to easily analyze transcriptional data without requiring programming skills. This platform provides a user-friendly interface and a suite of molecular characterization options for rapid transcriptomic analysis, addressing a major bottleneck in biological discovery.
DISEASE MODELS & MECHANISMS
(2022)
Article
Oncology
Vera Grinkevitch, Mark Wappett, Nyree Crawford, Stacey Price, Andrea Lees, Christopher McCann, Katherine McAllister, Jochen Prehn, Jamie Young, Jess Bateson, Lewis Gallagher, Magali Michaut, Vivek Iyer, Aikaterini Chatzipli, Syd Barthorpe, Daniel Ciznadija, Ido Sloma, Amy Wesa, David A. Tice, Lodewyk Wessels, Mathew Garnett, Daniel B. Longley, Ultan McDermott, Simon S. McDade
Summary: Second-generation TRAIL-R2 agonists face two major clinical challenges: lack of predictive biomarkers and development of resistance. This study identifies caspase-8:FLIP(L) and caspase-8:MCL-1 ratios as potential predictive biomarkers for second-generation TRAIL-R2 agonists, and loss of key effectors like FADD and caspase-8 as likely drivers of clinical resistance in solid tumors.
MOLECULAR CANCER THERAPEUTICS
(2022)
Article
Oncology
Emma H. Allott, Kellie Dean, Tracy Robson, Claire Meaney
Summary: The 57th Annual Conference of the Irish Association for Cancer Research focused on the tumor microenvironment and its impact on tumor growth and progression. The complexity of the microenvironment was highlighted, along with its potential as a target for new cancer treatments. Discussions also emphasized the importance of modeling the surrounding environment for a more comprehensive understanding of tumorigenesis.
Article
Biochemical Research Methods
Gerard P. Quinn, Tamas Sessler, Baharak Ahmaderaghi, Shauna Lambe, Harper VanSteenhouse, Mark Lawler, Mark Wappett, Bruce Seligmann, Daniel B. Longley, Simon S. McDade
Summary: classifieR is an easy-to-use web application based on R-Shiny, designed to facilitate flexible and rapid single sample annotation of transcriptional profiles from cancer patient samples in laboratories. It provides information on the molecular makeup of samples, as well as analysis of prognosis, druggability, and discovery of new information.
BMC BIOINFORMATICS
(2022)
Article
Gastroenterology & Hepatology
Shania M. Corry, Amy M. B. McCorry, Tamsin R. M. Lannagan, Niamh A. Leonard, Natalie C. Fisher, Ryan M. Byrne, Petros Tsantoulis, Xabier Cortes-Lavaud, Raheleh Amirkhah, Keara L. Redmond, Aoife J. McCooey, Sudhir B. Malla, Emily Rogan, Svetlana Sakhnevych, Michael A. Gillespie, Mark White, Susan D. Richman, Rene-Filip Jackstadt, Andrew D. Campbell, Sarah Maguire, Simon S. McDade, Daniel B. Longley, Maurice B. Loughrey, Helen G. Coleman, Emma M. Kerr, Sabine Tejpar, Timothy Maughan, Simon J. Leedham, Donna M. Small, Aideen E. Ryan, Owen J. Sansom, Mark Lawler, Philip D. Dunne
Summary: This study identifies and validates a HiFi-specific prognostic signature (HPS) based on STAT1-related signaling in the stroma-rich subtype of colon cancer. The HPS is associated with immune cell and antigen processing in stroma-rich colon cancer and treatment with the TLR3 agonist poly(I:C) can enhance the HPS signaling and reduce liver metastases.
Article
Oncology
Hajrah Khawaja, Rebecca Briggs, Cheryl H. Latimer, Mustasin Rassel, Dary Griffin, Lyndsey Hanson, Alberto Bardelli, Frederica Di Nicolantonio, Simon S. McDade, Christopher J. Scott, Shauna Lambe, Manisha Maurya, Andreas U. Lindner, Jochen H. M. Prehn, Jose Sousa, Chris Winnington, Melissa J. LaBonte, Sarah Ross, Sandra Van Schaeybroeck
Summary: Novel covalent inhibitors of KRASG12C have shown limited response rates in patients with KRASG12C-mutant colorectal cancer. In this study, researchers found that the combination of AZ'1569 and a Bcl-xL inhibitor led to a dramatic and universal apoptosis, suggesting a potential therapeutic strategy for patients with KRAS G12C-mutant colorectal cancer.
MOLECULAR CANCER THERAPEUTICS
(2023)
Article
Cell Biology
Ivana Steiner, Teresita del N. J. Flores-Tellez, Renaud Mevel, Amin Ali, Pengbo Wang, Pieta Schofield, Caron Behan, Nicholas Forsythe, Garry Ashton, Catherine Taylor, Ian G. Mills, Pedro Oliveira, Simon S. McDade, Dietmar M. Zaiss, Ananya Choudhury, Georges Lacaud, Esther Baena
Summary: Conditional deletion of PTEN gene in prostate cells leads to an increase in LY6D+ progenitor cells, resulting in the formation of castration-resistant prostate cancer with unmet clinical need. LY6D+ tumor cells are enriched in high-grade and androgen-resistant prostate cancer, providing clinical evidence for their contribution to advanced disease. Interfering with the MAPK signaling pathway can prevent the progression of castration-resistant prostate cancer.