Evidence map›Paper›PMID 39774602›Full record

ReviewLab on a chip2025

Advances in microfluidic platforms for tumor cell phenotyping: from bench to bedside.

Rutwik Joshi, Hesaneh Ahmadi, Karl Gardner, Robert K Bright, Wenwen Wang, Wei Li

Abstract readReview
In one paragraph

Review in Lab on a chip, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Rutwik JoshiDepartment of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA. wei.li@ttu.edu.ORCID 0000-0003-2934-2672
Hesaneh AhmadiDepartment of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA. wei.li@ttu.edu.
Karl GardnerDepartment of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA. wei.li@ttu.edu.
Robert K BrightDepartment of Immunology & Molecular Microbiology, School of Medicine & Cancer Center, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA.
Wenwen WangDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Wei LiDepartment of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA. wei.li@ttu.edu.ORCID 0000-0002-4738-1475

Funding

IMAT-ITCR Collaboration: Develop deep learning-based methods to identify subtypes of circulating tumor cells from optical microscope imagesR21CA240185 · NCI · TEXAS TECH UNIVERSITY · PI LI, WEI · 2020 to 2022
$625k
National Science Foundation CBET, GRANT NO. 1935792NCI NIH HHS R21 CA240185
6 · The paper itself

Abstract

Heterogeneities among tumor cells significantly contribute towards cancer progression and therapeutic inefficiency. Hence, understanding the nature of cancer through liquid biopsies and isolation of circulating tumor cells (CTCs) has gained considerable interest over the years. Microfluidics has emerged as one of the most popular platforms for performing liquid biopsy applications. Various label-free and labeling techniques using microfluidic platforms have been developed, the majority of which focus on CTC isolation from normal blood cells. However, sorting and profiling of various cell phenotypes present amongst those CTCs is equally important for prognostics and development of personalized therapies. In this review, firstly, we discuss the biophysical and biochemical heterogeneities associated with tumor cells and CTCs which contribute to cancer progression. Moreover, we discuss the recently developed microfluidic platforms for sorting and profiling of tumor cells and CTCs. These techniques are broadly classified into biophysical and biochemical phenotyping methods. Biophysical methods are further classified into mechanical and electrical phenotyping. While biochemical techniques have been categorized into surface antigen expressions, metabolism, and chemotaxis-based phenotyping methods. We also shed light on clinical studies performed with these platforms over the years and conclude with an outlook for the future development in this field.

Indexed as

Lab-On-A-Chip DevicesMicrofluidic Analytical TechniquesNeoplasmsNeoplastic Cells, CirculatingCell SeparationHumansPhenotype

Identifiers

PMID39774602
PMCPMC11859771

What OpenQuestion holds

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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.