Evidence map›Paper›PMID 41427221›Full record

ReviewACS omega2025

Implications of Single-Cell RNA Sequencing in Cervical Cancer: Unravelling the Molecular Landscape.

Blessy Kiruba, Raja Rishi Raghavendar Raja Karthikeyan, Saurav Ram Anilkumar, Vino Sundararajan, Sajitha Lulu S

Abstract readReview
In one paragraph

Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Blessy KirubaIntegrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore - 632 014 Tamil Nadu, India.
Raja Rishi Raghavendar Raja KarthikeyanIntegrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore - 632 014 Tamil Nadu, India.
Saurav Ram AnilkumarIntegrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore - 632 014 Tamil Nadu, India.
Vino SundararajanIntegrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore - 632 014 Tamil Nadu, India.
Sajitha Lulu SIntegrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore - 632 014 Tamil Nadu, India.ORCID https://orcid.org/0000-0002-3392-4168

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer (CC) is one of the most prevalent malignancies that affects women worldwide. It is strongly influenced by lifestyle and environmental factors, most notably persistent HPV infection and smoking. A defining feature of CC is its high degree of heterogeneity, which poses significant challenges for conventional sequencing and diagnostic approaches in fully capturing its oncogenetic landscape. The advent of single-cell RNA sequencing (scRNA-seq) has transformed this field, offering an unprecedented ability to dissect the tumor microenvironment at a single-cell resolution. By mapping cell-cell communication networks and characterizing gene expression across diverse cellular populations, scRNA-seq enables the identification of biomarkers with strong diagnostic and prognostic potential. Beyond biomarker discovery, this technology also facilitates the recognition of novel therapeutic targets, paving the way for more precise and effective treatment strategies. This review summarizes the applications of scRNA-seq in cervical cancer research, with a focus on methodological advances, key findings from recent studies, and their implications for improving diagnosis, prognosis, and therapeutic interventions.

Identifiers

PMID41427221
PMCPMC12713431

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.