Evidence map›Paper›PMID 38607302›Full record

ReviewChemical Society reviews2024

SERS in 3D cell models: a powerful tool in cancer research.

Lara Troncoso-Afonso, Gail A Vinnacombe-Willson, Clara García-Astrain, Luis M Liz-Márzan

Open access · hybridAbstract readReview
In one paragraph

Review in Chemical Society reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
9.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 49 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. High-YieldACS nano · 2025
    Article
  5. Plasmonic-Hydrogel Hybrid Biomaterials Via In Situ Seeded Growth.Angewandte Chemie (International ed. in English) · 2025
    Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Lara Troncoso-AfonsoBioNanoPlasmonics Laboratory, CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), 20014 Donostia-San Sebastián, Spain. llizmarzan@cicbiomagune.es.ORCID http://orcid.org/0009-0004-0695-3248
Gail A Vinnacombe-WillsonBioNanoPlasmonics Laboratory, CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), 20014 Donostia-San Sebastián, Spain. llizmarzan@cicbiomagune.es.ORCID http://orcid.org/0000-0002-6897-6574
Clara García-AstrainBioNanoPlasmonics Laboratory, CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), 20014 Donostia-San Sebastián, Spain. llizmarzan@cicbiomagune.es.ORCID http://orcid.org/0000-0002-4231-7335
Luis M Liz-MárzanBioNanoPlasmonics Laboratory, CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), 20014 Donostia-San Sebastián, Spain. llizmarzan@cicbiomagune.es.ORCID http://orcid.org/0000-0002-6647-1353
CIC biomaGUNE · ESIkerbasque · ESUniversity of the Basque Country · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unraveling the cellular and molecular mechanisms underlying tumoral processes is fundamental for the diagnosis and treatment of cancer. In this regard, three-dimensional (3D) cancer cell models more realistically mimic tumors compared to conventional 2D cell cultures and are more attractive for performing such studies. Nonetheless, the analysis of such architectures is challenging because most available techniques are destructive, resulting in the loss of biochemical information. On the contrary, surface-enhanced Raman spectroscopy (SERS) is a non-invasive analytical tool that can record the structural fingerprint of molecules present in complex biological environments. The implementation of SERS in 3D cancer models can be leveraged to track therapeutics, the production of cancer-related metabolites, different signaling and communication pathways, and to image the different cellular components and structural features. In this review, we highlight recent progress in the use of SERS for the evaluation of cancer diagnosis and therapy in 3D tumoral models. We outline strategies for the delivery and design of SERS tags and shed light on the possibilities this technique offers for studying different cellular processes, through either biosensing or bioimaging modalities. Finally, we address current challenges and future directions, such as overcoming the limitations of SERS and the need for the development of user-friendly and robust data analysis methods. Continued development of SERS 3D bioimaging and biosensing systems, techniques, and analytical strategies, can provide significant contributions for early disease detection, novel cancer therapies, and the realization of patient-tailored medicine.

Indexed as

NeoplasmsSpectrum Analysis, RamanAnimalsHumans

Identifiers

PMID38607302
PMCPMC11104264
OpenAlexW4394762670

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.