Quick Navigation

Topics

Quantum Machine Learning Quantum Chemistry Spin Qubits Silicon Quantum Computing

Next-generation nano-biosensors for hepatocellular carcinoma.

PubMed
Authors: Abuhassan Q, Saleh K, Roopashree R, Kanwar JB, Sudhakar T, Sharma V, Chauhan AS, Khaitova S

Year

2026

Paper ID

9945

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

142

Citations

3

Abstract

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and the limited sensitivity of conventional biomarkers. The emergence of nanomaterial-based biosensors offers transformative potential for precision diagnostics by integrating advanced physicochemical properties with molecular recognition strategies. This narrative review current progress in next-generation nanomaterial biosensors, including carbon nanostructures, metal-organic frameworks, quantum dots, and plasmonic nanoparticles, highlighting their roles in enhancing the sensitivity, specificity, and multiplexed detection of HCC-associated biomarkers such as alpha-fetoprotein, glypican-3, and circulating nucleic acids. We discuss innovative design principles, translational challenges, and clinical validation pathways, emphasizing how nanomaterial-enabled platforms can bridge the gap between laboratory innovation and bedside application. By critically evaluating technological advances and unmet clinical needs, this review underscores the promise of nanomaterial biosensors in enabling earlier detection, personalized monitoring, and improved prognostic assessment of HCC, ultimately advancing precision oncology.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis and the limited sensitivity of conventional...

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #9945 #78837 TLS loss in superconducting res... #78828 Verifiable Sampling for Delegat... #78813 Large-Scale Benchmarking of Qua... #78797 Local polarization control of o...

External citation index: OpenAlex citation signal • updated 2026-10-25 17:34:00

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.