Cancer Cell Populations Research Articles

Profiling the cancer-prone microenvironment in a zebrafish model for MPNST.

Microenvironmental contributions to soft tissue sarcoma progression are relatively undefined, particularly during sarcoma onset. Use of animal models to reveal these contributions is impeded by difficulties in discriminating between microenvironmental, precancerous, and cancer cells, and challenges in defining a precancerous microenvironment. We developed a zebrafish model that allows segregation of microenvironmental, precancerous, and cancerous cell populations by fluorescence-activated cell sorting. This model has high predilection for malignant peripheral nerve sheath tumor (MPNST), a type of soft tissue sarcoma that exhibits rapid, aggressive growth. Using RNA-seq, we profiled the transcriptomes of microenvironmental, precancerous, and cancer cells from our zebrafish MPNST model. We show broad activation of inflammation/immune-associated signaling networks, describe gene expression patterns that uniquely characterize the transition from precancerous to cancer ME, and identify macrophages as potential contributors to microenvironmental phenotypes. We identify conserved gene expression changes and candidate genes of interest by comparative genomics analysis of MPNST versus benign lesions in both humans and zebrafish. Finally, we functionally validate a candidate extracellular matrix protein, periostin (POSTN), in human MPNST. This work provides insight into how the microenvironment may regulate MPNST initiation and progression.

Fractional-Order Mathematical Modeling of Breast Cancer: Comparing Adaptive Immune Responses and Estrogen Dynamics with Experimental Data

Breast cancer is a significant global health concern that requires innovative approaches to understand its behavior and improve treatment strategies. This paper introduces a new fractional-order mathematical model to explain the complex dynamics of breast cancer progression, including adaptive immune responses and estrogen dynamics. Utilizing Caputo fractional derivatives, our model reveals insights into the impact of fractional-order dynamics on cancer cell populations. Simulation results demonstrate a notable increase in cell populations with higher fractional orders, suggesting heightened aggressiveness, while lower orders correspond to subdued progression. Unlike traditional integer-order models, fractional-order derivatives offer a more nuanced depiction of nonlinear dynamics, crucial for capturing the complexities of cancer progression. Importantly, our findings underscore the potential clinical relevance of fractional-order models in informing personalized treatment strategies, particularly through the modulation of estrogen levels. By integrating treatment considerations, such as hormone therapy, our model holds promise for advancing precision medicine approaches tailored to individual patient characteristics.

Exploring the Anticancer Potential of Triazine Derivatives: An Outlook of Designing Strategies, Docking Studies, and Structure‐Activity Relationships (SAR)

AbstractCancer is a disease characterized by uncontrolled cell growth resulting from genetic and epigenetic changes accumulating within a cancer cell population. Despite the milestone discovery of chemotherapeutic drugs against cancer, cancer remains tough to cure. Therefore, cancer has the second‐highest global death rate. There are certain factors such as genetic mutation, cancer cell diversity, metastasis, and resistance, which limit chemotherapy. To combat cancer, it's crucial to find novel therapeutic tactics and produce novel drugs that target cancer cells without affecting healthy cells. Heterocyclic compounds influence certain molecular targets to find novel lead structures can be a noteworthy strategy for the development of potential anticancer agents. Triazine, a low‐cost and widely available heterocyclic scaffold, has piqued researchers’ interest in developing innovative designing strategies. This review presents the advancement of three different isomers of triazines as anticancer agents. The main focus of this review is to provide the advancement of designing strategies, structure‐activity relationships, and docking studies of triazine derivatives as anticancer agents the available triazine‐containing drugs, and the status of clinical trials of triazine‐containing drugs were also highlighted. Lastly, we have also concluded the most potent derivatives and their hybridization with another ring to justify the particular anticancer activity.

Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations

Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression and there is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet systems to study these processes in vitro are limited. Single-cell RNA sequencing (scRNA-seq) has revealed that some cancer cell lines include distinct subpopulations. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. With clusterCleaver, ESAM and BST2/tetherin were experimentally validated as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification of surface markers for tracking and isolating transcriptomically distinct subpopulations within cell lines. This tool paves the way for studies on coexisting cancer cell subpopulations in well-defined in vitro systems.

Parameter estimation from single patient, single time-point sequencing data of recurrent tumors.

In this study, we develop consistent estimators for key parameters that govern the dynamics of tumor cell populations when subjected to pharmacological treatments. While these treatments often lead to an initial reduction in the abundance of drug-sensitive cells, a population of drug-resistant cells frequently emerges over time, resulting in cancer recurrence. Samples from recurrent tumors present as an invaluable data source that can offer crucial insights into the ability of cancer cells to adapt and withstand treatment interventions. To effectively utilize the data obtained from recurrent tumors, we derive several large number limit theorems, specifically focusing on the metrics that quantify the clonal diversity of cancer cell populations at the time of cancer recurrence. These theorems then serve as the foundation for constructing our estimators. A distinguishing feature of our approach is that our estimators only require a single time-point sequencing data from a single tumor, thereby enhancing the practicality of our approach and enabling the understanding of cancer recurrence at the individual level.

Serial single-cell RNA sequencing unveils drug resistance and metastatic traits in stage IV breast cancer

Metastasis is a complex process that remains poorly understood at the molecular levels. We profiled single-cell transcriptomic, genomic, and epigenomic changes associated with cancer cell progression, chemotherapy resistance, and metastasis from a Stage IV breast cancer patient. Pretreatment- and posttreatment-specimens from the primary tumor and distant metastases were collected for single-cell RNA sequencing and subsequent cell clustering, copy number variation (CNV) estimation, transcriptomic factor estimation, and pseudotime analyses. CNV analysis revealed that a small population of pretreatment cancer cells resisted chemotherapy and expanded. New clones including Metastatic Precursor Cells (MPCs), emerged in the posttreatment primary tumors in CNV similar to metastatic cells. MPCs exhibited expression profiles indicative of epithelial–mesenchymal transition. Comparison of MPCs with metastatic cancer cells also revealed dynamic changes in transcription factors and calcitonin pathway gene expression. These findings demonstrate the utility of single-patient clinical sample analysis for understanding tumor drug resistance, regrowth, and metastasis.

Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones

Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.

Stimulated Brillouin scattering flow cytometry.

We present the use of stimulated Brillouin scattering spectroscopy to achieve rapid measurements of cell biomechanics in a flow cytometer setup. Specifically, our stimulated Brillouin scattering flow cytometry can acquire at a rate of 200 Hz, with a spectral acquisition time of 5 ms, which marks a 10x improvement compared to previous demonstrations of spontaneous Brillouin scattering flow cytometry. We experimentally validate our stimulated Brillouin scattering flow cytometer by measuring cell populations of normal breast epithelial cells and metastatic breast epithelial cancer cells.

Correlating NAD(P)H lifetime shifts to tamoxifen resistance in breast cancer cells: A metabolic screening study with time-resolved flow cytometry

Time-resolved flow cytometry (TRFC) was used to measure metabolic differences in estrogen receptor-positive breast cancer cells. This specialty cytometry technique measures fluorescence lifetimes as a single-cell parameter thereby providing a unique approach for high-throughput cell counting and screening. Differences in fluorescence lifetime were detected and this was associated with sensitivity to the commonly prescribed therapeutic tamoxifen. Differences in fluorescence lifetime are attributed to the binding states of the autofluorescent metabolite NAD(P)H. The function of NAD(P)H is well described and in general involves cycling from a reduced to oxidized state to facilitate electron transport for the conversion of pyruvate to lactate. NAD(P)H fluorescence lifetimes depend on the bound or unbound state of the metabolite, which also relates to metabolic transitions between oxidative phosphorylation and glycolysis. To determine if fundamental metabolic profiles differ for cells that are sensitive to tamoxifen compared to those that are resistant, large populations of MCF-7 breast cancer cells were screened and fluorescence lifetimes were quantified. Additionally, metabolic differences associated with tamoxifen sensitivity were measured with a Seahorse HS mini metabolic analyzer (Agilent Technologies Inc. Santa Clara, CA) and confocal imaging. Results show that tamoxifen-resistant breast cancer cells have increased utilization of glycolysis for energy production compared to tamoxifen-sensitive breast cancer cells. This work is impacting because it establishes an early step toward developing a reliable screening technology in which large cell censuses can be differentiated for drug sensitivity in a label-free fashion.

Abstract C045: Targeting metabolic heterogeneity in pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the US. This poor prognosis is related to the complex tumor microenvironment and tumor heterogeneity that drives resistance to chemotherapy. Here the heterogeneity of the stromal, immune, and malignant epithelial cell populations enables signaling and metabolic crosstalk mechanisms that drive immune suppression and resistance to therapy. Recently, our group unveiled that multiple distinct metabolic subclasses of cancer cells coexist within individual PDAC tumors. Among these, two PDAC clonal populations can engage in metabolic symbiosis that supports mitochondrial metabolism. One subtype has a constitutively high integrated stress response (ISR), enabling resistance to mitochondrial inhibitors. Further, these cells release asparagine that supports the mitochondrial metabolism of the other subtype that are more sensitive to mitochondrial inhibition. Given these observations, we are developing approaches to disrupt this metabolic symbiosis. Clonal PDAC cells with constitutively active ISR exhibit increased sensitivity to inhibition of the redox activity of Redox factor 1/Apurinic-apyrimidinic endonuclease 1 (Ref-1). Importantly, this can be leveraged to disrupt the support of the mitochondrial metabolism of clonal symbiotic pairs. Moreover, polyclonal PDAC cell lines representative of the heterogeneity seen in PDAC patients show a highly synergistic response to the combination of Ref-1 redox inhibitors with mitochondrial inhibitors. These data suggest this treatment combination will be synergistic in polyclonal tumors that exist in most PDAC patients. Overall, these data have the potential to lead to new avenues to directly target heterogenous populations of cancer cells to treat pancreatic cancer- an urgent clinical need. Citation Format: Taryn Morningstar, Cecily Anaraki, Lorenzo Scipioni, Giulia Tedeschi, Michelle Digman, Aimee Edinger, Claus Jorgensen, Melissa Fishel, Christopher J Halbrook. Targeting metabolic heterogeneity in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C045.

Post-Transcriptional Regulation of Rab7a in Lysosomal Positioning and Drug Resistance in Nutrient-Limited Cancer Cells.

Limited nutrient availability in the tumor microenvironment can cause the rewiring of signaling and metabolic networks to confer cancer cells with survival advantages. We show here that the limitation of glucose, glutamine and serum from the culture medium resulted in the survival of a population of cancer cells with high viability and capacity to form tumors in vivo. These cells also displayed a remarkable increase in the abundance and size of lysosomes. Moreover, lysosomes were located mainly in the perinuclear region in nutrient-limited cells; this translocation was mediated by a rapid post-transcriptional increase in the key endolysosomal trafficking protein Rab7a. The acidic lysosomes in nutrient-limited cells could trap weakly basic drugs such as doxorubicin, mediating resistance of the cells to the drug, which could be partially reversed with the lysosomal inhibitor bafilomycin A1. An in vivo chorioallantoic membrane (CAM) assay indicated a remarkable decrease in microtumor volume when nutrient-limited cells were treated with 5-Fluorouracil (5-FU) and bafilomycin A1 compared to cells treated with either agent alone. Overall, our data indicate the activation of complementary pathways with nutrient limitation that can enable cancer cells to survive, proliferate and acquire drug resistance.

Drug response-based precision therapeutic selection for tamoxifen-resistant triple-positive breast cancer

Breast cancer adaptability to the drug environment reduces the chemotherapeutic response and facilitates acquired drug resistance. Cancer-specific therapeutics can be more effective against advanced-stage cancer than standard chemotherapeutics. To extend the paradigm of cancer-specific therapeutics, clinically relevant acquired tamoxifen-resistant MCF-7 proteome was deconstructed to identify possible druggable targets (N = 150). Twenty-eight drug inhibitors were used against identified druggable targets to suppress non-resistant (NC) and resistant cells (RC). First, selected drugs were screened using growth-inhibitory response against NC and RC. Seven drugs were shortlisted for their time-dependent (10–12 days) cytotoxic effect and further narrowed to three effective drugs (e.g., cisplatin, doxorubicin, and hydroxychloroquine). The growth-suppressive effectiveness of selected drugs was validated in the complex spheroid model (progressive and regressive). In the progressive model, doxorubicin (RC: 83.64 %, NC: 54.81 %), followed by cisplatin (RC: 76.66 %, NC: 68.94 %) and hydroxychloroquine (RC: 68.70 %, NC: 61.78 %) showed a significant growth-suppressive effect. However, in fully grown regressive spheroid, after 4th drug treatment, cisplatin significantly suppressed RC (84.79 %) and NC (40.21 %), while doxorubicin and hydroxychloroquine significantly suppressed only RC (76.09 and 76.34 %). Our in-depth investigation effectively integrated the expression data with the cancer-specific therapeutic investigation. Furthermore, our three-step sequential drug-screening approach unbiasedly identified cisplatin, doxorubicin, and hydroxychloroquine as an efficacious drug to target heterogeneous cancer cell populations. Significance statementHormonal-positive BC grows slowly, and hormonal-inhibitors effectively suppress the oncogenesis. However, development of drug-resistance not only reduces the drug-response but also increases the chance of BC aggressiveness. Further, alternative chemotherapeutics are widely used to control advanced-stage BC. In contrast, we hypothesized that, compared to standard chemotherapeutics, cancer-specific drugs can be more effective against resistant-cancer. Although cancer-specific treatment identification is an uphill battle, our work shows proteome data can be used for drug selection. We identified multiple druggable targets and, using ex-vivo methods narrowed multiple drugs to disease-condition-specific therapeutics. We consider that our investigation successfully interconnected the expression data with the functional disease-specific therapeutic investigation and selected drugs can be used for effective resistant treatment with higher therapeutic response.

Enhanced desmosome assembly driven by acquired high-level desmoglein-2 promotes phenotypic plasticity and endocrine resistance in ER+ breast cancer

Acquired resistance to endocrine treatments remains a major clinical challenge. In this study, we found that desmoglein-2 (DSG2) plays a major role in acquired endocrine resistance and cellular plasticity in ER+ breast cancer (BC). By analysing the well-established fulvestrant-resistant ER+ BC model using single-cell RNA-seq, we revealed that ER inhibition leads to a specific increase in DSG2 in cancer cell populations, which in turn enhances desmosome formation in vitro and in vivo and cell phenotypic plasticity that promotes resistance to treatment. DSG2 depletion reduced tumorigenesis and metastasis in fulvestrant-resistant xenograft models and promoted fulvestrant efficiency. Mechanistically, DSG2 forms a desmosome complex with JUP and Vimentin and triggers Wnt/PCP signalling. We showed that elevated DSG2 levels, along with reduced ER levels and an activated Wnt/PCP pathway, predicted poor survival, suggesting that a DSG2high signature could be exploited for therapeutic interventions. Our analysis highlighted the critical role of DSG2-mediated desmosomal junctions following antiestrogen treatment.

Mapping the breast tumor microenvironment: proximity analysis reveals spatial relationships between macrophage subtypes and metastasis-initiating cancer cells.

Metastasis is responsible for the majority of cancer-related fatalities. We previously identified specific cancer cell populations responsible for metastatic events which are cytokeratin-14 (CK14) and E-cadherin positive in luminal tumors, and E-cadherin and vimentin positive in triple-negative tumors. Since cancer cells evolve within a complex ecosystem comprised of immune cells and stromal cells, we sought to decipher the spatial interactions of these aggressive cancer cell populations within the tumor microenvironment (TME). We used imaging mass cytometry to detect 36 proteins in tumor microarrays containing paired primary and metastatic lesions from luminal or triple-negative breast cancers (TNBC), resulting in a dataset of 1,477,337 annotated cells. Focusing on metastasis-initiating cell populations, we observed close proximity to specific fibroblast and macrophage subtypes, a relationship maintained between primary and metastatic tumors. Notably, high CK14 in luminal cancer cells and high vimentin in TNBC cells correlated with close proximity to specific macrophage subtypes (CD163intCD206intPDL1intHLA-DR+ or PDL1highARG1high). Our in-depth spatial analysis demonstrates that metastasis-initiating cancer cells consistently colocalizes with distinct cell populations within the TME, suggesting a role for these cell-cell interactions in promoting metastasis.

Use of atomic force microscopy to assess the biomechanical properties of 3D tumor cell models

Multicellular spheroids are a unique object-model for toxicological studies. Cells in a 3D cluster have microenvironment, intercellular communication, which allows spheroids to be used as more realistic model compared to traditional cell cultures. It is known that tumor microregions consist of heterogeneous populations of cancer cells, in which cell growth and response to antitumor drugs depend on their 3D architecture, intercellular contacts and interaction with the microenvironment. In addition, tumor growth and progression are also strongly influenced by mechanical cues Currently, 3D cell culture models are a powerful tool for studying the toxicity of drug compounds and nanomaterials of different composition and morphology. This review presents data on the use of various techniques, in particular atomic force microscopy, to investigate changes in the mechanical properties of cells in spheroids. In particular, the use of atomic force microscopy as a tool to reveal physicochemical parameters of cells during pathophysiological processes or drug exposure is considered. The relevance of this review is related to the increasing interest in the role of biomechanical properties of tissues, cells and subcellular structures as markers of pathophysiological conditions.

Synthesis, pharmaceutical properties, and in silico study of ZnO@TiO2 nanocomposite

The use of environmentally friendly production of nanoparticles has recently interest of scientists. The primary goal of this study is to create core–shell nanoparticles zinc oxide @ dioxide titanium (ZnO @ TiO2) for some biomedical application by a two-stage Nd: YAG pulsed laser ablation, the first stage involves laser ablation of a Zinc target to produce ZnO nanoparticles (the core) in colloidal form. Subsequently, in the second stage, TiO2 (the shell) is ablated within the colloidal ZnO Nanoparticles. The transmission electron microscope (TEM) findings approve the synthesis of ZnO @ TiO2, displays an average particle size of 13 nm for ZnO particles, 20 nm of TiO2NPs, and 34 nm of the ZnO@TiO2 NPs. The anti-bacterial efficiency was assessed against the bacterial strains' Bacillus cereus, Proteus mirabilis. Our results discovered inhibition zone of 19 mm and12.50 mm for Bacillus cereus, Proteus mirabilis, correspondingly, when by ZnONPs. Whereas inhibition zone of 20.50 mm and 21.50 mm for Bacillus cereus, Proteus mirabilis, correspondingly, when by TiO2NPs. While with ZnO@TiO2NPs, result was better to 27.50 mm for Bacillus cereus and 24 mm for Proteus mirabilis. The antioxidant efficiency was assessed by DPPH, The results show have strong antioxidant activity for ZnO @ TiO2 core–shell than ZnONPs alone, TiO2NPs alone. Cytotoxicity assay established a significant reduction in cancer cell population pole 72hr. Cytotoxicity of ZnO@TiO2NPs on breast cancer cells was 90.23 %. Computational innovation of TiO2, ZnO and ZnO@TiO2 nanoparticles against breast cancer line gave the highest correlation value and RMSD between ZnO and 6NLV receptors from other nanocomposites.

Roles of Micropillar Topography and Surface Energy on Cancer Cell Dynamics

Microstructured surfaces are renowned for their unique properties, such as waterproofing and low adhesion, making them highly applicable in the biomedical field. These surfaces play a crucial role in influencing cell response by mimicking the native microenvironment of biological tissues. In this study, we engineered a series of biomimetic micropatterned surfaces using polydimethylsiloxane (PDMS) to explore their effects on primary breast cancer cell lines, contrasting these effects with those observed on conventional flat surfaces. The surface topography was varied to direct cells’ attachment, growth, and morphology. Our findings elucidate that surface-free energy is not merely a background factor but plays a decisive role in cell dynamics, strongly correlating with the spreading behaviour of breast cancer cells. Notably, on micropillar surfaces with high surface-free energy, an increase in the population of cancer cells was observed. Conversely, surfaces characterised by lower surface-free energies noted a reduction in cell viability. Moreover, the structural parameters, such as the gaps and diameters of the pillars, were found to critically influence cellular dispersion and adherence, underscoring the importance of the microstructures’ topography in biomedical applications. These insights pave the way for designing advanced microstructured surfaces tailored to specific cellular responses, opening new avenues for targeted cancer therapies and tissue engineering.

Drug tolerance and persistence in bacteria, fungi and cancer cells: Role of non-genetic heterogeneity

A common feature of bacterial, fungal and cancer cell populations upon treatment is the presence of tolerant and persistent cells able to survive, and sometimes grow, even in the presence of usually inhibitory or lethal drug concentrations, driven by non-genetic differences among individual cells in a population. Here we review and compare data obtained on drug survival in bacteria, fungi and cancer cells to unravel common characteristics and cellular pathways, and to point their singularities. This comparative work also allows to cross-fertilize ideas across fields. We particularly focus on the role of gene expression variability in the emergence of cell-cell non-genetic heterogeneity because it represents a possible common basic molecular process at the origin of most persistence phenomena and could be monitored and tuned to help improve therapeutic interventions.

Neuronal substance P drives metastasis through an extracellular RNA-TLR7 axis.

Tumour innervation is associated with worse patient outcomes in multiple cancers1,2, which suggests that it may regulate metastasis. Here we observed that highly metastatic mouse mammary tumours acquired more innervation than did less-metastatic tumours. This enhanced innervation was driven by expression of the axon-guidance molecule SLIT2 in tumour vasculature. Breast cancer cells induced spontaneous calcium activity in sensory neurons and elicited release of the neuropeptide substance P (SP). Using three-dimensional co-cultures and in vivo models, we found that neuronal SP promoted breast tumour growth, invasion and metastasis. Moreover, patient tumours with elevated SP exhibited enhanced lymph node metastatic spread. SP acted on tumoral tachykinin receptors (TACR1) to drive death of a small population of TACR1high cancer cells. Single-stranded RNAs (ssRNAs) released from dying cells acted on neighbouring tumoural Toll-like receptor 7 (TLR7) to non-canonically activate a prometastatic gene expression program. This SP- and ssRNA-induced Tlr7 gene expression signature was associated with reduced breast cancer survival outcomes. Therapeutic targeting of this neuro-cancer axis with the TACR1 antagonist aprepitant, an approved anti-nausea drug, suppressed breast cancer growth and metastasis in multiple models. Our findings reveal that tumour-induced hyperactivation of sensory neurons regulates multiple aspects of metastatic progression in breast cancer through a therapeutically targetable neuropeptide/extracellular ssRNA sensing axis.

Novel Anti-Cancer Stem Cell Compounds: A Comprehensive Review.

Cancer stem cells (CSCs) possess a significant ability to renew themselves, which gives them a strong capacity to form tumors and expand to encompass additional body areas. In addition, they possess inherent resistance to chemotherapy and radiation therapies used to treat many forms of cancer. Scientists have focused on investigating the signaling pathways that are highly linked to the ability of CSCs to renew themselves and maintain their stem cell properties. The pathways encompassed are Notch, Wnt/β-catenin, hedgehog, STAT3, NF-κB, PI-3K/Akt/mTOR, sirtuin, ALDH, MDM2, and ROS. Recent studies indicate that directing efforts towards CSC cells is essential in eradicating the overall cancer cell population and reducing the likelihood of tumor metastasis. As our comprehension of the mechanisms that stimulate CSC activity, growth, and resistance to chemotherapy advances, the discovery of therapeutic drugs specifically targeting CSCs, such as small-molecule compounds, holds the potential to revolutionize cancer therapy. This review article examines and analyzes the novel anti-CSC compounds that have demonstrated effective and selective targeting of pathways associated with the renewal and stemness of CSCs. We also discussed their special drug metabolism and absorption mechanisms. CSCs have been the subject of much study in cancer biology. As a possible treatment for malignancies, small-molecule drugs that target CSCs are gaining more and more attention. This article provides a comprehensive review of the current state of key small-molecule compounds, summarizes their recent developments, and anticipates the future discovery of even more potent and targeted compounds, opening up new avenues for cancer treatment.