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Emerging Technologies and Data Science

Studies, methods, and large datasets that employ computational biology, high-throughput techniques, imaging, physical sciences, or engineering to investigate cancer biology

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Latest in Emerging Technologies and Data Science

December 11 2024

Kinetics of Nirogacestat-Mediated Increases in B-cell Maturation Antigen on Plasma Cells Inform Therapeutic Combinations in Multiple Myeloma

Todd Shearer, Melissa Comstock et al.

B-cell maturation antigen (BCMA) is the target of several investigational and approved drugs for multiple myeloma. BCMA expressed on plasma cells (PC) and multiple myeloma cells is cleaved by the enzyme γ-secretase, reducing membrane-bound BCMA (mbBCMA) receptor density. γ-Secretase inhibitors (GSI) have been shown to ...

December 06 2024

Pan-Cancer Analysis of Homologous Recombination Deficiency in Cell Lines

Anne E. Dodson, Sol Shenker et al.

Homologous recombination deficiency (HRD) drives genomic instability in multiple cancer types and renders tumors vulnerable to certain DNA-damaging agents such as PARP inhibitors. Thus, HRD is emerging as an attractive biomarker in oncology. A variety of in silico methods are available for predicting HRD; however, few of ...

December 05 2024

Clonal hematopoiesis of indeterminate potential (CHIP) and its association with treatment outcomes and adverse events in patients with solid tumours

Tharani Krishnan, Joao Paulo Solar Vasconcelos et al.

Clonal hematopoiesis of indeterminate potential (CHIP) is the clonal expansion of hematopoietic stem cells from somatic mutations. It is a common incidental finding in cell-free DNA (cfDNA). We investigated the incidence of CHIP in cfDNA from patients with solid tumours and explored its association with treatment outcomes ...

December 04 2024

Single-Cell Analysis of Bone Marrow CD8⁺ T Cells in Myeloid Neoplasms Reveals Pathways Associated with Disease Progression and Response to Treatment with Azacitidine

Athanasios Tasis, Nikos E. Papaioannou et al.

CD8+ T cells are crucial for antitumor immunity. However, their functionality is often altered in higher-risk myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML). To understand their role in disease progression, we conducted a comprehensive immunophenotypic analysis of 104 pretreatment bone marrow (BM) ...

December 02 2024

Dynamic Evolution of Fibroblasts Revealed by Single-Cell RNA Sequencing of Human Pancreatic Cancer

Slavica Dimitrieva, Jon M. Harrison et al.

Cancer progression and response to therapy are inextricably reliant on the coevolution of a supportive tissue microenvironment. This is particularly evident in pancreatic ductal adenocarcinoma, a tumor type characterized by expansive and heterogeneous stroma. Herein, we employed single-cell RNA sequencing and spatial ...

November 27 2024

Tumor expression of CD83 reduces glioma progression and is associated with reduced immunosuppression

Malcolm F. McDonald, Rachel Naomi Curry et al.

Malignant glioma, the most lethal form of brain cancer, presents with an immunosuppressive microenvironment that obstructs tumor cell clearance and hampers immunotherapeutic interventions. Despite advancements in characterizing cellular and extracellular profiles in cancer, the immunosuppressive mechanisms specific to ...

November 14 2024

Identification of Non-Coding RNA Biomarkers in Non-Small Cell Lung Cancer to Address Racial Disparities

Lu Gao, Pushpa Dhilipkannah et al.

Lung cancer significantly impacts mortality, with African Americans (AAs) showing higher rates than White Americans (WAs). Noncoding RNAs (ncRNAs) play a crucial role in lung tumorigenesis. To identify ncRNA biomarkers associated with racial disparities in lung cancer, we used droplet digital PCR to examine 93 lung ...

November 14 2024

Mathematical Modeling Unveils Optimization Strategies for Targeted Radionuclide Therapy of Blood Cancers

Maxim Kuznetsov, Vikram Adhikarla et al.

Targeted radionuclide therapy (TRT) is based on injections of cancer-specific molecules conjugated with radioactive nuclides. Despite the specificity of this treatment, it is not devoid of side effects limiting its use and is especially harmful for rapidly proliferating organs well perfused by blood, like bone marrow. ...

November 11 2024

DeePathNet: a transformer-based deep learning model integrating multi-omic data with cancer pathways

Zhaoxiang Cai, Rebecca C. Poulos et al.

Multi-omic data analysis incorporating machine learning has the potential to significantly improve cancer diagnosis and prognosis. Traditional machine learning methods are usually limited to omic measurements, omitting existing domain knowledge, such as the biological networks that link molecular entities in various omic ...

October 29 2024

SpliceMutr enables pan-cancer analysis of splicing-derived neoantigen burden in tumors

Theron Palmer, Michael D Kessler et al.

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Topics in Emerging Technologies and Data Science

Expand/Collapse Section CHEMISTRY & CHEMICAL BIOLOGY
Expand/Collapse Section PROTEOMICS
Expand/Collapse Section SYSTEMS BIOLOGY
Expand/Collapse Section BIOPHYSICAL TECHNOLOGIES
- Nuclear magnetic resonance
- X-ray crystallography
Expand/Collapse Section BIOSTATISTICS
Expand/Collapse Section COMPUTATIONAL METHODS
- Artificial intelligence & machine learning
- Gene expression profiling
- Algorithms
- Database resources
- Mathematical modeling
- Molecular modeling
- Sequence analysis
- Software
Expand/Collapse Section DRUG DISCOVERY TECHNOLOGIES
- Novel assay technology
- Screening strategies (assays and chemical libraries)
- Natural products
- Synthesis
- Structural studies
- Computational methods
Expand/Collapse Section ENGINEERING
Expand/Collapse Section GENE TECHNOLOGIES
- Cytogenetics
- Comparative genomics
- Mutation detection methods
- Microarrays
- High-throughput sequencing
Expand/Collapse Section IMAGING
- Magnetic resonance imaging (MRI)
- X-ray computed tomography (CT)
- Positron emission tomography (PET)
- Ultrasound/Photoacoustics
- Small animal imaging
- Imaging probes
Expand/Collapse Section LIQUID BIOPSY
Expand/Collapse Section MATERIAL SCIENCE
Expand/Collapse Section PRECLINICAL MODELS
- Animal models of cancer
- In vitro models of cancer
- Organoids
- Xenograft models
Expand/Collapse Section PROTEIN TECHNOLOGIES
Expand/Collapse Section SINGLE CELL TECHNOLOGIES

Emerging Technologies and Data Science

Topics in Emerging Technologies and Data Science

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