ReviewSensors (Basel, Switzerland)2020
Raman Microscopy: Progress in Research on Cancer Cell Sensing.
Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 48 citations in OpenAlex.
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Probe Cytotoxic and Oxidative Stress Effects of Nanoplastics on Caco-2 Cells: Insights from Raman Spectroscopy and Machine Learning.Sensors (Basel, Switzerland) · 2026Article
- Training and validation of a 1D CNN model for accurate three-class classification of oral cancer using serum Raman spectroscopy.Discover oncology · 2026Article
- KYNU is a potential metabolic-related biomarker for nasopharyngeal carcinoma by Raman spectroscopy, metabolomics, and transcriptomics analysis.Discover oncology · 2025Article
- Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis.Communications biology · 2025Article
- Raman Spectroscopy in Cellular and Tissue Aging Research.Aging cell · 2025Review
- GenAI synthesis of histopathological images from Raman imaging for intraoperative tongue squamous cell carcinoma assessment.International journal of oral science · 2025Article
- Correlative Raman Imaging: Development and Cancer Applications.Biosensors · 2024Review
- Hybrid Biosilica Nanoparticles for in-vivo Targeted Inhibition of Colorectal Cancer Growth and Label-Free Imaging.International journal of nanomedicine · 2024Article
- Assessment of Primary Human Liver Cancer Cells by Artificial Intelligence-Assisted Raman Spectroscopy.Cells · 2023Article
- Raman Spectroscopy Combined with Malaria Protein for Early Capture and Recognition of Broad-Spectrum Circulating Tumor Cells.International journal of molecular sciences · 2023Article
- The emerging applications and advancements of Raman spectroscopy in pediatric cancers.Frontiers in oncology · 2023Review
- Impact of preprocessing methods on the Raman spectra of brain tissue.Biomedical optics express · 2022Article
- Who's Who? Discrimination of Human Breast Cancer Cell Lines by Raman and FTIR Microspectroscopy.Cancers · 2022Article
- Specific intracellular signature of SARS-CoV-2 infection using confocal Raman microscopy.Communications chemistry · 2022Article
- Raman and XANES Spectroscopic Study of the Influence of Coordination Atomic and Molecular Environments in Biomimetic Composite Materials Integrated with Dental Tissue.Nanomaterials (Basel, Switzerland) · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.