TGF-β generates a population of cancer cells residing in G1 phase with high motility and metastatic potential via KRTAP2-3

TGF-β induces EMT in thyroid cancer cells by regulating transcription factors

BACKGROUND

Transforming growth factor-β (TGF-β) plays well-established roles in cancer cell invasion and epithelial-mesenchymal transition (EMT); however, its role in thyroid carcinoma (TC) remains unclear. This study aimed to evaluate the effects of TGF-β on EMT in TC and determine its underlying mechanisms.

METHODS

Treatment of TC cell lines with TGF-β the morphology of thyroid cancer cells changed, Immunofluorescence staining revealed that the localization of E-cadherin shifted from the cell membrane to the cytoplasm, and the fluorescence intensity decreases. Wound-healing assay in BCPAP and TPC-1 revealed that migration ability was significantly higher in the TGF-β (5 ng/mL) treatment group than in the control group (P < 0.01).

RESULTS

Transwell assays showed that the invasive abilities of TGF-β-treated BCPAP, TPC-1, and K1 cells were 7-, 10-, and 6-fold higher than those of the control group, respectively (P < 0.05). After TGF-β treatment, mRNA levels of SNAI1 significantly increased in TPC-1 and BCPAP cell lines. Treatment of TC cell lines with TGF-β downregulated the epithelial marker E-cadherin and upregulated the mesenchymal markers N-cadherin and vimentin, at the mRNA level. Western blotting indicated similar results at the protein level, TSH could enhance this process.

CONCLUSIONS

TGF-β promotes EMT-like phenotypic changes in thyroid cancer cells, accompanied by upregulation of SNAI1 and EMT-related markers, which is enhanced by TSH. Overall, this study provides a basis for the development of therapeutic strategies for TC targeting the EMT.

Targeting TGF-β: a promising strategy for cancer therapy

Transforming growth factor β (TGF-β) has important role in regulating the cellular processes including cell growth, differentiation, and migration. TGF-β exerts its effect by binding with transcellular membranes and kinases. Our findings demonstrate that TGF- β possess dual role as tumor suppressor and tumor promoter in different stages of cancer. TGF-β emerged as a promising anticancer agent that exhibits the apoptosis by acting on the suppressor of mothers against decapentaplegic (SMAD) and non-SMAD pathways. In this review we are focusing on the different types of TGF- β inhibitors active against skin cancer, breast cancer, colorectal cancer, lung cancer and ovarian cancer. TGF-β inhibitors includes ligand traps, monoclonal antibodies and receptor kinase inhibitors. In recent studies, TGF- β inhibitors have also been used in combination therapies in the treatment of cancer. The TGF-β has important role in vaccine therapy, Chemo and Radio Resistance in Cancer. TGF-β inhibitors present the novel therapeutic approach for the cancer therapy, highlighting the mechanism of action involved, clinical trials, challenges and exploring therapeutic opportunities. This will help to develop the novel TGF-β inhibitors as anticancer agents as well as help to resolve the problem of drug resistance by developing new drugs as anticancer agents.

Epithelial-mesenchymal transition couples with cell cycle arrest at various stages

Numerous computational approaches have been developed to infer cell state transition trajectories from snapshot single-cell data. Most approaches first require projecting high-dimensional data onto a low-dimensional representation, raising the question of whether the dynamics of the system become distorted. Using epithelial-to-mesenchymal transition (EMT) as a test system, we show that both biology-guided low-dimensional representations and stochastic trajectory simulations in high-dimensional state space, not representations obtained with brute force dimension-reduction methods, reveal multiple distinct paths of TGF-β-induced EMT. The paths arise from coupling between EMT and cell cycle arrest at either the G1/S, G2/M or M checkpoints, contributing to cell-cycle related EMT heterogeneity. The present study emphasizes that caution should be taken when inferring transition dynamics from snapshot single-cell data in two- or three-dimensional representations, and that incorporating dynamical information can improve prediction accuracy.

Deciphering TGF-β1's role in drug resistance and leveraging plant bioactives for cancer therapy

The intricate regulatory mechanisms governing TGF-β1 expression play pivotal roles in tumor progression. Key proteins such as FKBP1A, SMAD6, and SMAD7 trigger this process, modulating cell growth inhibition via p15INK4b and p21CIP1 induction. Despite TGF-β's tumor-suppressive functions, cancer cells adeptly evade its effects, fueling disease advancement. Tumor microenvironmental TGF-β1 prompts epithelial-mesenchymal transition (EMT), facilitated by transcription factors like slug, twist-1, and snail. Notably, cancer-associated fibroblasts (CAFs) amplify this effect by secreting TGF-β1, fostering drug resistance. Of particular concern is the resistance observed with BRAF/MEK inhibitors (BRAFi/MEKi), highlighting the clinical significance of TGF-β signaling in cancer therapeutics. However, emerging interest in natural anti-cancer agents, with their distinct pharmacological actions on signaling proteins offers promising avenues for therapeutic intervention. This review emphasizes the multifaceted interplay between TGF-β signaling, tumor microenvironment dynamics, and therapeutic resistance mechanisms, illuminating potential targets for combating cancer progression by plant-derived-natural-bioactive compounds. However, this review additionally explores the currently available advanced methods for detecting various types of cancer. Not only that, but it also discussed the function of plant-derived compounds in clinical aspects, as well as its limitations.

HIF1α Counteracts TGFβ1-Driven TSP1 Expression in Endothelial Cells to Stimulate Angiogenesis in the Hypoxic Tumor Microenvironment

Emerging evidence suggests that TGFβ1 can inhibit angiogenesis, contradicting the coexistence of active angiogenesis and high abundance of TGFβ1 in the tumor microenvironment. Here, we investigated how tumors overcome the antiangiogenic effect of TGFβ1. TGFβ1 treatment suppressed physiologic angiogenesis in chick chorioallantoic membrane and zebrafish models but did not affect angiogenesis in mouse hepatoma xenografts. The suppressive effect of TGFβ1 on angiogenesis was recovered in mouse xenografts by a hypoxia-inducible factor 1α (HIF1α) inhibitor. In contrast, a HIF1α stabilizer abrogated angiogenesis in zebrafish, indicating that hypoxia may attenuate the antiangiogenic role of TGFβ1. Under normoxic conditions, TGFβ1 inhibited angiogenesis by upregulating antiangiogenic factor thrombospondin 1 (TSP1) in endothelial cells (EC) via TGFβ type I receptor (TGFβR1)-SMAD2/3 signaling. In a hypoxic microenvironment, HIF1α induced miR145 expression; miR145 abolished the inhibitory effect of TGFβ1 on angiogenesis by binding and repressing SMAD2/3 expression and subsequently reducing TSP1 levels in ECs. Primary ECs isolated from human hepatocellular carcinoma displayed increased miR145 and decreased SMAD3 and TSP1 compared with ECs from adjacent nontumor livers. The reduced SMAD3 or TSP1 in ECs was associated with increased angiogenesis in hepatocellular carcinoma tissues. Collectively, this study identified that TGFβ1-TGFβR1-SMAD2/3-TSP1 signaling in ECs inhibits angiogenesis. This inhibition can be circumvented by a hypoxia-HIF1α-miR145 axis, elucidating a mechanism by which hypoxia promotes angiogenesis. Significance: Suppression of angiogenesis by TGFβ1 is mediated by TSP1 upregulation in endothelial cells and abrogated by HIF1α-miR145 activity in the hypoxic tumor microenvironment, providing potential targets to remodel the tumor vasculature.

Structure, unique biological properties, and mechanisms of action of transforming growth factor β

Transforming growth factor β (TGF-β) is a ubiquitous molecule that is extremely conserved structurally and plays a systemic role in human organism. TGF-β is a homodimeric molecule consisting of two subunits joined through a disulphide bond. In mammals, three genes code for TGF-β1, TGF-β2, and TGF-β3 isoforms of this cytokine with a dominating expression of TGF-β1. Virtually, all normal cells contain TGF-β and its specific receptors. Considering the exceptional role of fine balance played by the TGF-β in anumber of physiological and pathological processes in human body, this cytokine may be proposed for use in medicine as an immunosuppressant in transplantology, wound healing and bone repair. TGFb itself is an important target in oncology. Strategies for blocking members of TGF-β signaling pathway as therapeutic targets have been considered. In this review, signalling mechanisms of TGF-β1 action are addressed, and their role in physiology and pathology with main focus on carcinogenesis are described.

Tumor glucose metabolism and the T cell glycocalyx: implication for T cell function

The T cell is an immune cell subset highly effective in eliminating cancer cells. Cancer immunotherapy empowers T cells and occupies a solid position in cancer treatment. The response rate, however, remains relatively low (<30%). The efficacy of immunotherapy is highly dependent on T cell infiltration into the tumor microenvironment (TME) and the ability of these infiltrated T cells to sustain their function within the TME. A better understanding of the inhibitory impact of the TME on T cells is crucial to improve cancer immunotherapy. Tumor cells are well described for their switch into aerobic glycolysis (Warburg effect), resulting in high glucose consumption and a metabolically distinct TME. Conversely, glycosylation, a predominant posttranslational modification of proteins, also relies on glucose molecules. Proper glycosylation of T cell receptors influences the immunological synapse between T cells and tumor cells, thereby affecting T cell effector functions including their cytolytic and cytostatic activities. This review delves into the complex interplay between tumor glucose metabolism and the glycocalyx of T cells, shedding light on how the TME can induce alterations in the T cell glycocalyx, which can subsequently influence the T cell's ability to target and eliminate tumor cells.

Identifying Key Regulatory Genes in Drug Resistance Acquisition: Modeling Pseudotime Trajectories of Breast Cancer Single-Cell Transcriptome

Single-cell RNA-sequencing (scRNA-seq) technology has provided significant insights into cancer drug resistance at the single-cell level. However, understanding dynamic cell transitions at the molecular systems level remains limited, requiring a systems biology approach. We present an approach that combines mathematical modeling with a pseudotime analysis using time-series scRNA-seq data obtained from the breast cancer cell line MCF-7 treated with tamoxifen. Our single-cell analysis identified five distinct subpopulations, including tamoxifen-sensitive and -resistant groups. Using a single-gene mathematical model, we discovered approximately 560-680 genes out of 6000 exhibiting multistable expression states in each subpopulation, including key estrogen-receptor-positive breast cancer cell survival genes, such as RPS6KB1. A bifurcation analysis elucidated their regulatory mechanisms, and we mapped these genes into a molecular network associated with cell survival and metastasis-related pathways. Our modeling approach comprehensively identifies key regulatory genes for drug resistance acquisition, enhancing our understanding of potential drug targets in breast cancer.

Insights into metastatic roadmap of head and neck cancer squamous cell carcinoma based on clinical, histopathological and molecular profiles

The incidence of head and neck cancer (HNC), constituting approximately one in ten cancer cases worldwide, affects approximately 644,000 individuals annually. Managing this complex disease involves various treatment modalities such as systemic therapy, radiation, and surgery, particularly for patients with locally advanced disease. HNC treatment necessitates a multidisciplinary approach due to alterations in patients' genomes affecting their functionality. Predominantly, squamous cell carcinomas (SCCs), the majority of HNCs, arise from the upper aerodigestive tract epithelium. The epidemiology, staging, diagnosis, and management techniques of head and neck squamous cell carcinoma (HNSCC), encompassing clinical, image-based, histopathological and molecular profiling, have been extensively reviewed. Lymph node metastasis (LNM) is a well-known predictive factor for HNSCC that initiates metastasis and significantly impacts HNSCC prognosis. Distant metastasis (DM) in HNSCC has been correlated to aberrant expression of cancer cell-derived cytokines and growth factors triggering abnormal activation of several signaling pathways that boost cancer cell aggressiveness. Recent advances in genetic profiling, understanding tumor microenvironment, oligometastatic disease, and immunotherapy have revolutionized treatment strategies and disease control. Future research may leverage genomics and proteomics to identify biomarkers aiding individualized HNSCC treatment. Understanding the molecular basis, genetic landscape, atypical signaling pathways, and tumor microenvironment have enhanced the comprehension of HNSCC molecular etiology. This critical review sheds light on regional and distant metastases in HNSCC, presenting major clinical and laboratory features, predictive biomarkers, and available therapeutic approaches.

Gain-of-Function p53 Mutation Acts as a Genetic Switch for TGFβ Signaling-Induced Epithelial-to-Mesenchymal Transition in Intestinal Tumors

Signaling by TGFβ family cytokines plays a tumor-suppressive role by inducing cell differentiation, while it promotes malignant progression through epithelial-to-mesenchymal transition (EMT). Identification of the mechanisms regulating the switch from tumor suppression to tumor promotion could identify strategies for cancer prevention and treatment. To identify the key genetic alterations that determine the outcome of TGFβ signaling, we used mouse intestinal tumor-derived organoids carrying multiple driver mutations in various combinations to examine the relationship between genotypes and responses to the TGFβ family cytokine activin A. KrasG12D mutation protected organoid cells from activin A-induced growth suppression by inhibiting p21 and p27 expression. Furthermore, Trp53R270H gain-of-function (GOF) mutation together with loss of wild-type Trp53 by loss of heterozygosity (LOH) promoted activin A-induced partial EMT with formation of multiple protrusions on the organoid surface, which was associated with increased metastatic incidence. Histologic analysis confirmed that tumor cells at the protrusions showed loss of apical-basal polarity and glandular structure. RNA sequencing analysis indicated that expression of Hmga2, encoding a cofactor of the SMAD complex that induces EMT transcription factors, was significantly upregulated in organoids with Trp53 GOF/LOH alterations. Importantly, loss of HMGA2 suppressed expression of Twist1 and blocked activin A-induced partial EMT and metastasis in Trp53 GOF/LOH organoids. These results indicate that TP53 GOF/LOH is a key genetic state that primes for TGFβ family-induced partial EMT and malignant progression of colorectal cancer. Activin signaling may be an effective therapeutic target for colorectal cancer harboring TP53 GOF mutations.

SIGNIFICANCE

KRAS and TP53 mutations shift activin-mediated signaling to overcome growth inhibition and promote partial EMT, identifying a subset of patients with colorectal cancer that could benefit from inhibition of TGFβ signaling.

Identification of long noncoding RNAs downregulated specifically in ovarian high-grade serous carcinoma

Purpose

To investigate whether long noncoding RNAs (lncRNAs) are involved in the development or malignant behavior of ovarian high-grade serous carcinoma (HGSC), we attempted to identify lncRNAs specific to HGSC.

Methods

Total RNAs were isolated from HGSC, normal ovarian, and fallopian tube tissue samples and were subjected to a PCR array that can analyze 84 cancer-associated lncRNAs. The lncRNAs that were upregulated and downregulated in HGSC in comparison to multiple samples of normal ovary and fallopian tube were validated by real-time RT-PCR. To infer the function, ovarian cancer cell lines that overexpress the identified lncRNAs were established, and the activation of cell proliferation, migration, and invasion was analyzed.

Results

Eleven lncRNAs (ACTA2-AS1, ADAMTS9-AS2, CBR3-AS1, HAND2-AS1, IPW, LINC00312, LINC00887, MEG3, NBR2, TSIX, and XIST) were downregulated in HGSC samples. We established the cell lines that overexpress ADAMTS9-AS2, CBR3-AS1, or NBR2. In cell lines overexpressing ADAMTS9-AS2, cell proliferation was suppressed, but migration and invasion were promoted. In cell lines overexpressing CBR3-AS1 or NBR2, cell migration tended to be promoted, although cell proliferation and invasion were unchanged.

Conclusion

We identified eleven lncRNAs that were specifically downregulated in HGSC. Of these, CBR3-AS1, NBR2, and ADAMTS9-AS2 had unique functions in the malignant behaviors of HGSC.

Population dynamics of EMT elucidates the timing and distribution of phenotypic intra-tumoral heterogeneity

The Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of cancer metastasis and morbidity. EMT is a non-binary process, and cells can be stably arrested en route to EMT in an intermediate hybrid state associated with enhanced tumor aggressiveness and worse patient outcomes. Understanding EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing (scRNA-seq) data that enable in-depth analyses of EMT at the single-cell resolution, current inferential approaches are limited to bulk microarray data. There is thus a great need for computational frameworks to systematically infer and predict the timing and distribution of EMT-related states at single-cell resolution. Here, we develop a computational framework for reliable inference and prediction of EMT-related trajectories from scRNA-seq data. Our model can be utilized across a variety of applications to predict the timing and distribution of EMT from single-cell sequencing data.