Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Filter by Categories
Abstracts
Book Review
Case Report
Case Series
CMAS‡ - Pancreas - EUS-FNA Cytopathology (PSC guidelines) S1:1 of 5
CMAS‡ - Pancreas - EUS-FNA Cytopathology (PSC guidelines) S1:3 of 5
CMAS‡ - Pancreas - EUS-FNA Cytopathology (PSC guidelines) S1:4 of 5
CMAS‡ - Pancreas -Sampling Techniques for Cytopathology (PSC guidelines) S1:2 of 5
CMAS‡ - Pancreas- EUS-FNA Cytopathology (PSC guidelines) S1:5 of 5
Commentary
Correction
CytoJournal Monograph Related Review Series
CytoJournal Monograph Related Review Series (CMAS), Editorial
CytoJournal Monograph Related Review Series: Editorial
Cytojournal Quiz Case
Editorial
Erratum
Letter to Editor
Letter to the Editor
Letters to Editor
Methodology
Methodology Article
Methodology Articles
Original Article
Pap Smear Collection and Preparation: Key Points
Quiz Case
Research
Research Article
Review
Review Article
Systematic Review and Meta Analysis
View Point
View/Download PDF

Translate this page into:

Editorial
2026
:23;
48
doi:
10.25259/Cytojournal_191_2025

Cancer stem cells: A roadblock in disease treatment

Department of Biological Sciences, Sunandan Divatia School of Science, SVKM’s NMIMS Deemed to be University, Mumbai, Maharashtra, India.
Author image
Corresponding author: Sonal M. Manohar, Department of Biological Sciences, Sunandan Divatia School of Science, SVKM’s NMIMS Deemed to be University, Mumbai, Maharashtra, India. sonal.manohar@nmims.edu
Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Manohar SM, Shah IM. Cancer stem cells: A roadblock in disease treatment. CytoJournal. 2026;23:48. doi: 10.25259/Cytojournal_191_2025

Dear Editor,

Cancer stem cells (CSCs) represent a rare subpopulation found within tumors, characterized by the ability to undergo self-renewal and continuous proliferation. Rather than being a static and rigidly organized subset, CSCs exhibit a highly dynamic state within tumors. This intrinsic plasticity enables CSCs to not just transition between quiescent and proliferative states but also adopt epithelial or mesenchymal phenotypes in response to various stresses, in turn making their eradication through conventional therapeutic approaches very difficult.

CSCs were successfully isolated for the first time in 1997 from acute myeloid leukemia and identified as cells having extensive proliferative potential along with CD34+CD38 phenotype.[1] Thereafter, the concept of CSCs was expanded to solid tumors, and CSC populations have been well-characterized for breast, colorectal, lung, pancreatic cancers, etc.[2]

CSCs exhibit a number of similarities with the normal stem cells (NSCs), particularly in terms of their self-renewal and differentiation capabilities. In fact, CSCs commonly take over the molecular mechanisms associated with self-renewal and differentiation of NSCs to accelerate tumor progression. CSC behavior is governed by an intricate signaling network mainly comprised of Notch, Sonic Hedgehog, wingless-related integration site (WNT)/β-catenin, transforming growth factor-beta (TGF-β), Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT3), phosphatidylinositol 3-kinase (PI3K)/Akt pathways. Several key stemness factors participate in the transcriptional control of CSCs across various cancer types, namely, octamer-binding transcription factor 4 (Oct4), SRY (sex-determining region Y)-box 2 (Sox2), c-Myc, kruppel-like factor 4 (KLF4), and NANOG.[3]

Surface markers play a key role in the identification and characterization of CSCs. Some of the commonly expressed stemness-related markers by CSCs have been listed in Supplementary Table 1. Nonetheless, these markers may differ in expression levels and/or patterns across cancer types. Western blotting remains the gold standard for CSC identification based on these specific marker/s’ expression. The evolution of cell sorting technologies, such as fluorescence-activated cell sorting (FACS), magnetic-activated cell sorting (MACS), and microfluidics, has progressed from exploiting physical properties of CSCs (e.g., these specific cell surface markers) to using functional characteristics such as dye efflux, Ca2+ concentration, and pH. Recent advancements in single-cell sequencing and spatial transcriptomics have further revealed the underlying heterogeneity among CSC populations. Next-Generation Sequencing (NGS) data analysis approaches such as Ribo-Seq, RIP-Seq, CLIP-Seq, and ribonucleic acid (RNA) velocity provide valuable insights into CSC heterogeneity, lineage dynamics, and stemness/differentiation traits.[4]

Supplementary Table 1

The tumor microenvironment (TME) significantly influences the pathological role of CSCs. Various components of TME, including extracellular matrix and non-tumor cells such as immune cells, cancer-associated fibroblasts (CAF), and endothelial cells, are well-known for their ability to modulate CSC activity through paracrine signaling.[5] Hypoxic TME allows CSCs to remain in a relatively dormant and undifferentiated state. Epithelial to mesenchymal transition (EMT), a hallmark of cancers, has been extensively linked to increased invasiveness and resistance to apoptosis. Tumor-associated macrophages promote EMT and maintain stemness features through TGF-β signaling in CSCs. Interestingly, hypoxia and EMT are closely correlated since hypoxia-inducible factor-1 (HIF-1) activates numerous transcription factors involved in EMT, including twist and snail.[6] EMT also prompts CSC-like phenotype, since EMT transcription factors activate pluripotency regulators (Oct4, Sox2, and NANOG) and sustained signaling through WNT/β-catenin, Notch, and Hedgehog pathways.[7]

CSCs exhibit metabolic adaptability, which enables them to switch between different energy sources depending on the diverse environmental conditions. This metabolic plasticity is intimately regulated by Notch, Hedgehog, and PI3K signaling pathways in CSCs, resulting in the development of distinct signaling-metabolism feedback loops, which ensure that CSC characteristics are maintained.[2] The role of CSCs in disease progression and relapse has been depicted in Figure 1.

Tumor microenvironment (TME) acts as a niche for cancer stem cells (CSCs) and plays an essential role in the promotion and maintenance of CSCs. Cells within TME, including tumor-associated macrophages, cancer-associated fibroblasts, tumor endothelial cells, and extracellular matrix components, govern CSC behavior. CSCs play a crucial role in tumor initiation, progression, maintenance, metastasis, therapeutic resistance, and relapse.
Figure 1: Tumor microenvironment (TME) acts as a niche for cancer stem cells (CSCs) and plays an essential role in the promotion and maintenance of CSCs. Cells within TME, including tumor-associated macrophages, cancer-associated fibroblasts, tumor endothelial cells, and extracellular matrix components, govern CSC behavior. CSCs play a crucial role in tumor initiation, progression, maintenance, metastasis, therapeutic resistance, and relapse.

Due to their active involvement in metastasis as well as therapy resistance, CSCs are being considered as key targets for improving cancer treatment outcomes. CSCs resist therapy through a wide range of intrinsic and extrinsic mechanisms, which include metabolic reprogramming, drug efflux transporters, aldehyde dehydrogenase (ALDH) activity, and quiescence. CSCs actively interact with adjacent stromal cells within the TME, causing impaired responses to immunotherapy.[8] Several therapeutic approaches aimed at specifically targeting these mechanisms are currently in preclinical and clinical development. For example, targeting proliferative CSCs having high telomerase activity using cyclin-dependent kinase 4/6 (CDK 4/6) inhibitors[9] or promoting CSC differentiation.[10,11] Various novel compounds and distinct epigenetic modulators are also currently under investigation for their potential to selectively target CSC phenotypes. Furthermore, there is a rising interest in chimeric antigen receptor T-cells (CAR T-cells) for effective targeting of antigens enriched on the surface of CSCs.[12] Other cutting-edge technologies, such as clustered regularly interspaced short palindromic repeats (CRISPR)-based functional screening and multi-omics-based profiling, have significantly contributed towards the characterization of CSC vulnerabilities.

A substantial limitation that is hindering the clinical translation of several CSC-targeted therapies is CSC’s adaptive plasticity, which enables them to bypass most of the single-target therapeutic interventions. Therefore, designing multi-target interventions so that there is no compensatory shift in the energy utilization of CSCs is essential.[1]

Combinatorial regimens have been proposed that target both the rapidly proliferating tumor cells and quiescent CSCs along with their immunosuppressive niche.[6]

CSC research should also prioritize establishing early detection strategies since CSCs are believed to be closely associated with the disease pathology. This involves inclusion of exosomal RNA signatures and liquid biopsy approaches for the identification of CSCs. Similarly, extracellular vesicles are potential non-invasive biomarkers for monitoring the activity of CSCs.[2]

Altogether, the ultimate challenge lies in translating fundamental biological insights into clinically viable diagnostic and therapeutic strategies. Incorporation of advanced technologies, such as single-cell monitoring in association with spatial profiling, into clinical trials for efficient tracking of CSC dynamics in real time is warranted.[12] As we progress toward the clinical application of CSC-targeted therapies, a multidisciplinary approach that integrates various concepts of immunotherapy, systems biology, synthetic biology, and bioinformatics-guided precision medicine is essential to disrupt CSC-driven tumor progression and thereby improve long-term patient outcomes.[13]

ACKNOWLEDGMENTS

We would like to thank SVKM’s NMIMS for providing access to www.biorender.com.

AVAILABILITY OF DATA AND MATERIALS

Not applicable.

ABBREVIATIONS

ALDH: Aldehyde dehydrogenase

CAF: Cancer-associated fibroblasts

CAR: Chimeric antigen receptor

CDK: Cyclin-dependent kinase

CSC: Cancer stem cell

EMT: Epithelial to mesenchymal transition

FACS: Fluorescence-activated cell sorting

HIF-1: Hypoxia-inducible factor-1

JAK: Janus kinase

KLF4: Kruppel-like factor 4

MACS: Magnetic-activated cell sorting

NGS: Next-generation sequencing

Oct4: Octamer-binding transcription factor 4

PI3K: Phosphatidylinositol 3-kinase

Sox2: SRY (sex-determining region Y)-box 2

STAT3: Signal transducer and activator of transcription 3

TGF-β: Transforming growth factor-beta

TME: Tumor microenvironment

WNT: Wingless-related integration site

AUTHOR CONTRIBUTIONS

SM: Conceived the idea; IS: Conducted literature review, prepared the initial draft; SM: Revised the draft, supervised the study. Both authors critically reviewed the article and approved the final manuscript. Both authors possess the ability to be responsible for all aspects of the work, ensuring that any issues related to the accuracy or completeness of any part of the work are properly investigated and resolved. Both authors are eligible for ICMJE authorship.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

Not applicable.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

EDITORIAL/PEER REVIEW

To ensure the integrity and highest quality of CytoJournal publications, the review process of this manuscript was conducted under a double-blind model (authors are blinded for reviewers and vice versa) through an automatic online system.

FUNDING: Not applicable.

References

  1. , . Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med. 1997;3:730-7.
    [CrossRef] [PubMed] [Google Scholar]
  2. , , , , , , et al. Cancer stem cells: Landscape, challenges and emerging therapeutic innovations. Signal Transduct Target Ther. 2025;10:248.
    [CrossRef] [PubMed] [Google Scholar]
  3. , , , , , . Regulation and signaling pathways in cancer stem cells: Implications for targeted therapy for cancer. Mol Cancer. 2023;22:172.
    [CrossRef] [PubMed] [Google Scholar]
  4. , . Hallmarks of cancer stemness. Cell Stem Cell. 2024;31:617-39.
    [CrossRef] [PubMed] [Google Scholar]
  5. , , , , , , et al. Stem cell for cancer immunotherapy: Current approaches and challenges. Stem Cell Rev Rep. 2025;21:1931-54.
    [CrossRef] [PubMed] [Google Scholar]
  6. , , , , , , et al. Characteristics of the cancer stem cell niche and therapeutic strategies. Stem Cell Res Ther. 2022;13:233.
    [CrossRef] [PubMed] [Google Scholar]
  7. , . Stem cells in cancer: From Mechanisms to therapeutic strategies. Cells. 2025;14:538.
    [CrossRef] [PubMed] [Google Scholar]
  8. , , , . Cross-talk between cancer stem cells and immune cells: Potential therapeutic targets in the tumor immune microenvironment. Mol Cancer. 2023;22:38.
    [CrossRef] [PubMed] [Google Scholar]
  9. , , , , , . Targeting cancer stem cell propagation with palbociclib, a CDK4/6 inhibitor: Telomerase drives tumor cell heterogeneity. Oncotarget. 2017;8:9868-84.
    [CrossRef] [PubMed] [Google Scholar]
  10. , , . Targeting of cancer stem cells by differentiation therapy. Cancer Sci. 2020;111:2689-95.
    [CrossRef] [PubMed] [Google Scholar]
  11. , , . Cancer stem cells and differentiation therapy. Tumour Biol. 2017;39:1010428317729933.
    [CrossRef] [PubMed] [Google Scholar]
  12. , , , , , , et al. Unveiling the future of cancer stem cell therapy: A narrative exploration of emerging innovations. Discov Oncol. 2025;16:373.
    [CrossRef] [PubMed] [Google Scholar]
  13. , , . Drug resistance in cancer therapy: The Pandora's Box of cancer stem cells. Stem Cell Res Ther. 2022;13:181.
    [CrossRef] [PubMed] [Google Scholar]

Fulltext Views
2,573

PDF downloads
333
View/Download PDF
Download Citations
BibTeX
RIS
Show Sections