A Deep Learning Approach to Causal Inference in Human Genomics using Counterfactual Reasoning DOI Creative Commons
Tshepo Kitso Gobonamang

Published: July 17, 2023

In this paper, we delve into the intricate realm of human genomics, presenting a novel design that leverages deep learning and counterfactual reasoning for causal inference. We postulate mutations occurring within DNA sequences have potential to instigate diseases by interrupting essential biological processes, hypothesis fundamentally drives research. To test this, undertaken meticulous extraction key attributes from range databases hosted National Center Biotechnology Information (NCBI). These are subsequently processed using one-hot encoding, technique effectively transforms categorical variables form could be provided machine algorithms. A sophisticated model is then utilized ascertain accuracy hypothesis. The output, depicted as graph, elucidates relationships interactions between in question, providing graphical representation proposed Our research suggests strategic modifications sequence or alterations set induce significant changes processes. This, turn, can lead structure function proteins, cornerstone cellular operations. also underline importance statements formulating hypotheses driving intelligent behavior. Despite their untestable nature inherent subjectivity, these counterfactuals serve powerful tools comprehending predicting outcomes. implications extend beyond academic interest. It provides pathway deeper understanding genomics holds promise development targeted therapies genetic diseases. fosters possibility personalized medicine therapeutic strategies alter course disease at level, potentially revolutionizing healthcare.

Language: Английский

The role of coagulome in the tumor immune microenvironment DOI Creative Commons
Riajul Wahab, Md. Mahedi Hasan,

Zulfikar Azam

et al.

Advanced Drug Delivery Reviews, Journal Year: 2023, Volume and Issue: 200, P. 115027 - 115027

Published: July 28, 2023

Language: Английский

Citations

12
Fueling the fight against cancer: Exploring the impact of branched-chain amino acid catalyzation on cancer and cancer immune microenvironment DOI
Qianquan Ma, Haoyu Li,

Zhihao Song

et al.

Metabolism, Journal Year: 2024, Volume and Issue: 161, P. 156016 - 156016

Published: Aug. 31, 2024

Language: Английский

Citations

5
Review on analytical technologies and applications in metabolomics DOI Open Access
Xin Meng, Yan Liu,

SHUJUN XU

et al.

Biocell, Journal Year: 2024, Volume and Issue: 48(1), P. 65 - 78

Published: Jan. 1, 2024

Over the past decade, swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry, nuclear magnetic resonance, and multivariate statistics. Currently, garners widespread application across diverse fields including drug research development, early disease detection, toxicology, food nutrition science, biology, prescription, chinmedomics, among others. Metabolomics serves an effective characterization technique, offering insights into physiological process alterations in vivo. These changes may result from various exogenous factors like environmental conditions, stress, medications, well endogenous elements genetic protein-based influences. The potential scientific outcomes gleaned these have catalyzed formulation innovative methods, poised further broaden scope this domain. Today, has evolved a valuable widely accepted instrument life sciences. However, comprehensive reviews focusing on sample preparation analytical methodologies employed within sciences are surprisingly scant. This review aims fill that gap, providing overview current trends recent advancements metabolomics. Particular emphasis is placed preparation, sophisticated techniques, their applications science research.

Language: Английский

Citations

4
COL1A1, mediated by m6A methylation of METTL3, facilitates oral squamous cell carcinoma cell growth and metastasis DOI

Ruya Lv,

Yao Yao,

Jingjing Dong

et al.

Odontology, Journal Year: 2024, Volume and Issue: unknown

Published: June 20, 2024

Language: Английский

Citations

4
BCAA metabolism in cancer progression and therapy resistance: The balance between fuel and cell signaling DOI Creative Commons
Zhou Yi, Jiahui Kou, Wenjin Li

et al.

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: May 14, 2025

Branched-chain amino acids (BCAAs), including leucine, isoleucine, and valine, play a crucial role in cellular metabolism signaling. Recent studies have demonstrated that BCAA metabolic reprogramming is key driver of tumor progression treatment resistance various cancers. supports cancer cell growth, survival, proliferation by modulating pathways such as mTOR signaling oxidative stress responses. By promoting immunosuppressive conditions increasing the survival rate stem cells (CSCs), BCAAs contribute to immune evasion therapies chemotherapy checkpoint inhibitors. This article explores different patterns tumors introduces BCAA-related targets for overcoming resistance, offering new directions precision treatment, reducing improving patient outcomes.

Language: Английский

Citations

0
Tumor‑associated macrophages activated in the tumor environment of hepatocellular carcinoma: Characterization and treatment (Review) DOI
Mingkai Yu, Haixia Yu, Hongmei Wang

et al.

International Journal of Oncology, Journal Year: 2024, Volume and Issue: 65(4)

Published: Sept. 5, 2024

Hepatocellular carcinoma (HCC) tissue is rich in dendritic cells, T B macrophages, natural killer cells and cellular stroma. Together they form the tumor microenvironment (TME), which also numerous cytokines. Tumor‑associated macrophages (TAMs) are involved regulation of development. TAMs HCC receive stimuli different directions, polarize directions release cytokines to regulate development HCC. mostly divided into two cell phenotypes: M1 M2. secrete pro‑inflammatory mediators, M2 a variety anti‑inflammatory pro‑tumorigenic substances. The TAM polarization tumors Both direct indirect methods for discussed. indirectly support by promoting peripheral angiogenesis regulating immune TME. In terms between present review mainly focuses on molecular mechanism. both proliferation apoptosis quantitative changes HCC, stimulate related invasive migratory ability stemness cells. aims identify immunotherapeutic options based mechanisms TME

Language: Английский

Citations

3
Causal associations of MICB, CTSA, and MMP9 proteins with oral cancer: Mendelian randomization study DOI Creative Commons
Bowen Dong, Jian Hua, Shanni Ma

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Oct. 27, 2024

Oral cancer (ORCA) is the most prevalent histological subtype of oral malignancies in which immune modulation relevant. The goal this work was to employ Mendelian randomization (MR) investigate causal connection between immune-related proteins MICB, CTSA, MMP9, and ORCA. Open GWAS database Integrative Epidemiology Unit (IEU) accessed collect data for ORCA (ieu-b-4961), MICB (prot-a-1898), CTSA (prot-a-717) MMP9 (prot-a-1921). From 372,373 samples, dataset comprises 7,723,107 single nucleotide polymorphisms (SNPs). all have 10,534,735 SNPs 3,301 sample sizes. Then, primary SVMR implementation approaches were weighted mode, simple inverse variance (IVW), median, MR-Egger. IVW effective technique. A sensitivity study also carried out assess correctness data, with special focus devoted heterogeneity, horizontal pleiotropy, Leave-One-Out (LOO). MVMR eventually implemented as well. analysis three exposure factors (ieu-b-94, ebi-a-GCST012237) performed validate results. According results, there a noteworthy interaction (P = 0.0014), 0.0343), 0.0003). Furthermore, odds ratios (ORs) values revealed that (OR 1.0005) an risk factor, whereas 0.9994) 0.9993) security factors. robustness findings confirmed by p-values heterogeneity both greater than 0.05. result did not affect any safety or hazard features these However, P value 0.05, implying may influence on MMP9. validation outcomes datasets harmonized from previous research, thereby solidifying reliability Our investigation provided crucial resource further research subject demonstrating relationship

Language: Английский

Citations

3
Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer DOI Creative Commons

Sisi Gong,

Zhijun Liao, Meie Wang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: June 7, 2024

Abstract Triple-negative breast cancer (TNBC) is recognized for its aggressive nature, lack of effective diagnosis and treatment, generally poor prognosis. The objective this study was to investigate the metabolic changes in TNBC using metabolomics approaches explore underlying mechanisms through integrated analysis with transcriptomics. In study, serum untargeted profiles were firstly explored between 18 21 healthy controls (HC) by liquid chromatography-mass spectrometry (LC-MS), identifying a total 22 significantly altered metabolites (DMs). Subsequently, receiver operating characteristic revealed that 7-methylguanine could serve as potential biomarker both discovery validation sets. Additionally, transcriptomic datasets retrieved from GEO database identify differentially expressed genes (DEGs) normal tissues. An integrative DMs DEGs subsequently conducted, uncovering molecular TNBC. Notably, three pathways—tyrosine metabolism, phenylalanine glycolysis/gluconeogenesis—were enriched, explaining energy metabolism disorders Within these pathways, two (4-hydroxyphenylacetaldehyde oxaloacetic acid) six (MAOA, ADH1B, ADH1C, AOC3, TAT, PCK1) identified critical components. summary, highlights biomarkers potentially be utilized screening comprehensive transcriptomics data provides validated in-depth understanding metabolism.

Language: Английский

Citations

1
Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer DOI Creative Commons

Sisi Gong,

Rongfu Huang,

Meie Wang

et al.

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Nov. 11, 2024

Triple-negative breast cancer (TNBC) is known for its aggressive nature, lack of effective diagnostic tools and treatments, generally poor prognosis. The objective this study was to investigate metabolic changes in TNBC using metabolomics approaches explore the underlying mechanisms through integrated analysis with transcriptomics. In study, serum untargeted profiles were first examined between 18 patients 21 healthy control (HC) subjects liquid chromatography-mass spectrometry (LC-MS), identifying a total 22 significantly differential metabolites (DMs). Subsequently, receiver operating characteristic revealed that 7-methylguanine could serve as potential biomarker both discovery validation sets. Additionally, transcriptomic datasets retrieved from GEO database identify differentially expressed genes (DEGs) normal tissues. An integrative DMs DEGs conducted, uncovering molecular TNBC. Notably, three pathways—tyrosine metabolism, phenylalanine glycolysis/gluconeogenesis—were enriched, providing insight into energy metabolism disorders Within these pathways, two (4-hydroxyphenylacetaldehyde oxaloacetic acid) six (MAOA, ADH1B, ADH1C, AOC3, TAT, PCK1) identified key components. summary, highlights biomarkers potentially be used diagnosis screening comprehensive transcriptomics data offers validated in-depth understanding metabolism.

Language: Английский

Citations

1
Using CADD tools to inhibit the overexpressed genes FAP, FN1, and MMP1 by repurposing ginsenoside C and Rg1 as a treatment for oral cancer DOI Creative Commons

Manal Abouelwafa,

Tamer M. Ibrahim, Mohamed El-Hadidi

et al.

Frontiers in Molecular Biosciences, Journal Year: 2023, Volume and Issue: 10

Published: Oct. 23, 2023

Oral cancer is one of the most common types. Many factors can express certain genes that cause proliferation oral tissues. Overexpressed were detected in patients; three highly impacted. FAP, FN1, and MMP1 targeted showed inhibition results silico by ginsenoside C Rg1. Approved drugs retrieved from DrugBank database. The docking scores show an excellent interaction between ligands macromolecules. Further molecular dynamics simulations binding stability proposed natural products. This work recommends repurposing Rg1 as potential binders for selected targets endorses future experimental validation treatment cancer.

Language: Английский

Citations

2