Evidence map›Paper›PMID 40621756›Full record

ReviewCurrent drug targets2025

Matrix Metalloproteinase-9: A Key Diagnostic Biomarker in Cancer Progression.

Arpita Srivastava, Jatin Gupta, Shivani Singhal, Hardeep Tulli, Neetu Mishra, Neha Atale, Buddhi Prakash Jain, Christophe Grosset, Bhawna Saxena, Vibha Rani

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current drug targets, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

10 authors.

Arpita SrivastavaTranscriptome Laboratory, Centre of Excellence in Emerging Diseases, Jaypee Institute of Information Technology, Block A, Industrial Area, Sector 62, Noida, Uttar Pradesh, 201309, India.
Jatin GuptaTranscriptome Laboratory, Centre of Excellence in Emerging Diseases, Jaypee Institute of Information Technology, Block A, Industrial Area, Sector 62, Noida, Uttar Pradesh, 201309, India.
Shivani SinghalTranscriptome Laboratory, Centre of Excellence in Emerging Diseases, Jaypee Institute of Information Technology, Block A, Industrial Area, Sector 62, Noida, Uttar Pradesh, 201309, India.
Hardeep TulliDepartment of Biotechnology, MMDU, Mullana Ambala, India.
Neetu MishraSymbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India.
Neha AtaleDepartment of Cardiothoracic Surgery, University of Pittsburgh, USA.
Buddhi Prakash JainDepartment of Zoology, Mahatma Gandhi Central University, Bihar, India.
Christophe GrossetUniv. Bordeaux, INSERM, Bordeaux Institute in Oncology, BRIC, U1312, 33000 Bordeaux, France.
Bhawna SaxenaDepartment of Computer Science and Engineering and Engineering & Information, Jaypee Institute of Information Technology, Block A, Industrial Area, Sector 62, Noida, Uttar Pradesh, India.
Vibha RaniTranscriptome Laboratory, Centre of Excellence in Emerging Diseases, Jaypee Institute of Information Technology, Block A, Industrial Area, Sector 62, Noida, Uttar Pradesh, 201309, India.

Funding

Indian Council of Medical Research (ICMR), Govt. of India 67/4/2022-DDI/BMS
6 · The paper itself

Abstract

Matrix metalloproteinase-9, also known as MMP-9, gelatinase B, or 92 kDa type IV collagenase, is an enzyme that belongs to the matrix metalloproteinase (MMP) family. It is involved in the remodeling of the extracellular matrix in various physiological and pathological processes. MMPs are expressed in low, tightly regulated concentrations; their overexpression or dysregulation can lead to diseases, including cancer. MMP-9 is increasingly recognized as a significant drug target in cancer therapy due to its involvement in tumorigenesis, including processes like cell migration, angiogenesis, and pro-apoptotic and anti-apoptotic activities. Despite MMP-9's significance as a cancer target, developing effective inhibitors remains challenging due to MMP structural similarities. Utilizing MMP-9 as a cancer biomarker could advance cancer diagnosis, prognosis, disease monitoring, recurrence prediction, and other procedures. Biosensors are emerging as pivotal tools in cancer diagnosis and treatment, leveraging their ability to detect specific biomarkers associated with various cancers. Recent advancements have led to the development of both cleavage-based and non-cleavage-based biosensors that enable rapid and sensitive analysis at clinically relevant concentrations of biomarkers while allowing specificity and low detection limits, enhancing point-of-care diagnostics. The cleavage-based biosensors leverage the enzymatic activity of MMP-9, utilizing substrates that are specifically cleaved by MMP-9, while the non-cleavage- based biosensors employ affinity methods, such as antibodies and aptamers for detection. The present review aims to evaluate the role of MMP-9 as a significant biomarker in cancer and its detection through innovative biosensor technologies, while exploring its involvement in various cancer- related processes. This review discusses the significance of MMP-9 in cancer progression, highlighting clinical trials that assess MMP-9 inhibitors as potential therapeutic agents to halt metastatic spread. Furthermore, MMP-9 is detected via biosensors, and insights into the translational potential of MMP-9 both as a biomarker for early cancer detection and a viable target for therapeutic intervention are provided, ultimately contributing to improved patient outcomes in oncology.

Indexed as

Biomarkers, TumorMatrix Metalloproteinase 9NeoplasmsAnimalsBiosensing TechniquesDisease ProgressionHumansMatrix Metalloproteinase InhibitorsPrognosisBiomarkers, TumorMatrix Metalloproteinase 9Matrix Metalloproteinase Inhibitorsbiomarkerbiomaterialcancerdiagnostics.extracellular matrixMatrix metalloproteinasesensors

Identifiers

What OpenQuestion holds

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Registered trials

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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.