TM4SF1 as a prognostic marker of pancreatic ductal adenocarcinoma is involved in migration and invasion of cancer cells

STsisal: a reference-free deconvolution pipeline for spatial transcriptomics data

Spatial transcriptomics has emerged as an invaluable tool, helping to reveal molecular status within complex tissues. Nonetheless, these techniques have a crucial challenge: the absence of single-cell resolution, resulting in the observation of multiple cells in each spatial spot. While reference-based deconvolution methods have aimed to solve the challenge, their effectiveness is contingent upon the quality and availability of single-cell RNA (scRNA) datasets, which may not always be accessible or comprehensive. In response to these constraints, our study introduces STsisal, a reference-free deconvolution method meticulously crafted for the intricacies of spatial transcriptomics (ST) data. STsisal leverages a novel approach that integrates marker gene selection, mixing ratio decomposition, and cell type characteristic matrix analysis to discern distinct cell types with precision and efficiency within complex tissues. The main idea of our method is its adaptation of the SISAL algorithm, which expertly disentangles the ratio matrix, facilitating the identification of simplices within the ST data. STsisal offers a robust means to unveil the intricate composition of cell types in spatially resolved transcriptomic data. To verify the efficacy of STsisal, we conducted extensive simulations and applied the method to real data, comparing its performance against existing techniques. Our findings highlight the superiority of STsisal, underscoring its utility in capturing the cell composition within complex tissues.

LETSmix: a spatially informed and learning-based domain adaptation method for cell-type deconvolution in spatial transcriptomics

Spatial transcriptomics (ST) enables the study of gene expression in spatial context, but many ST technologies face challenges due to limited resolution, leading to cell mixtures at each spot. We present LETSmix to deconvolve cell types by integrating spatial correlations through a tailored LETS filter, which leverages layer annotations, expression similarities, image texture features, and spatial coordinates to refine ST data. Additionally, LETSmix employs a mixup-augmented domain adaptation strategy to address discrepancies between ST and reference single-cell RNA sequencing data. Comprehensive evaluations across diverse ST platforms and tissue types demonstrate its high accuracy in estimating cell-type proportions and spatial patterns, surpassing existing methods (URL: https://github.com/ZhanYangen/LETSmix ).

Deconvolution and inference of spatial communication through optimization algorithm for spatial transcriptomics

Spatial transcriptomics technologies can capture gene expression at spatial loci. However, at certain resolutions, the obtained gene expression reflects the sum of either a heterogeneous or homogeneous set of cells, rather than individual cell. This limitation gives rise to the deconvolution algorithm to make cell-type inferences at each location. Yet, the vast majority of deconvolution methods that have been developed ignore the spatial information of the tissue and the communications between the cells or spots. To overcome these afflictions, we proposed a deconvolution method, non-negative least squares-based and optimization search-based deconvolution (NODE), that combines cell-type-specific information from single-cell RNA sequencing (scRNA-seq) and intercellular communications in tissue. NODE deconvolution algorithm, incorporating the spatial information of the tissue, allows us to quantify intercellular communications at the same instant. NODE can not only utilize optimization method to infer the deconvolution results of spatial transcriptomics data and reduce the probability of overfitting situations, but also make reasonable inferences for spatial communications. Subsequently, we applied NODE to four datasets to validate the correctness of the NODE deconvolution results and compare them with existing deconvolution algorithms. NODE also inferred spatial communications and validated them in tissue development of human heart.

Spatial transcriptomics deconvolution at single-cell resolution using Redeconve

Computational deconvolution with single-cell RNA sequencing data as reference is pivotal to interpreting spatial transcriptomics data, but the current methods are limited to cell-type resolution. Here we present Redeconve, an algorithm to deconvolute spatial transcriptomics data at single-cell resolution, enabling interpretation of spatial transcriptomics data with thousands of nuanced cell states. We benchmark Redeconve with the state-of-the-art algorithms on diverse spatial transcriptomics platforms and datasets and demonstrate the superiority of Redeconve in terms of accuracy, resolution, robustness, and speed. Application to a human pancreatic cancer dataset reveals cancer-clone-specific T cell infiltration, and application to lymph node samples identifies differential cytotoxic T cells between IgA+ and IgG+ spots, providing novel insights into tumor immunology and the regulatory mechanisms underlying antibody class switch.

Three Members of Transmembrane-4-Superfamily, TM4SF1, TM4SF4, and TM4SF5, as Emerging Anticancer Molecular Targets against Cancer Phenotypes and Chemoresistance

There are six members of the transmembrane 4 superfamily (TM4SF) that have similar topology and sequence homology. Physiologically, they regulate tissue differentiation, signal transduction pathways, cellular activation, proliferation, motility, adhesion, and angiogenesis. Accumulating evidence has demonstrated, among six TM4SF members, the regulatory roles of transmembrane 4 L6 domain family members, particularly TM4SF1, TM4SF4, and TM4SF5, in cancer angiogenesis, progression, and chemoresistance. Hence, targeting derailed TM4SF for cancer therapy has become an emerging research area. As compared to others, this review aimed to present a focused insight and update on the biological roles of TM4SF1, TM4SF4, and TM4SF5 in the progression, metastasis, and chemoresistance of various cancers. Additionally, the mechanistic pathways, diagnostic and prognostic values, and the potential and efficacy of current anti-TM4SF antibody treatment were also deciphered. It also recommended the exploration of other interactive molecules to be implicated in cancer progression and chemoresistance, as well as potential therapeutic agents targeting TM4SF as future perspectives. Generally, these three TM4SF members interact with different integrins and receptors to significantly induce intracellular signaling and regulate the proliferation, migration, and invasion of cancer cells. Intriguingly, gene silencing or anti-TM4SF antibody could reverse their regulatory roles deciphered in different preclinical models. They also have prognostic and diagnostic value as their high expression was detected in clinical tissues and cells of various cancers. Hence, TM4SF1, TM4SF4, and TM4SF5 are promising therapeutic targets for different cancer types preclinically and deserve further investigation.

Immune-related gene TM4SF18 could promote the metastasis of gastric cancer cells and predict the prognosis of gastric cancer patients

Gastric cancer (GC) is one of the most common malignancies in the world, and the search for better markers has become one of the challenges today. It has been found that the L6 superfamily regulates the biological functions of numerous tumors, but transmembrane 4 L six family member 18 (TM4SF18) has been rarely reported. We found that TM4SF18 expression is upregulated in GC tissues and cells, which can be effectively diagnosed and dynamically monitored to assess the prognosis of GC patients. Furthermore, knockdown of TM4SF18 effectively inhibited proliferation, migration, and invasion of GC cells, and affected the epithelial-mesenchymal transition process. TM4SF18 was found to be an independent prognostic factor for GC by univariate and multifactorial Cox analyses as well as by establishing nomogram plots. In addition, in TM4SF18 and immune correlation analysis, TM4SF18 expression levels were found to be negatively correlated with most immune cell marker genes and associated with numerous immune cells and immune pathways, resulting in less benefit from treatment with immune checkpoint inhibitors. In summary, we found that TM4SF18 is a promising GC biomarker that promotes the proliferation, migration, and invasion abilities of GC cells, and is associated with immune response.

Spatially informed cell-type deconvolution for spatial transcriptomics

Many spatially resolved transcriptomic technologies do not have single-cell resolution but measure the average gene expression for each spot from a mixture of cells of potentially heterogeneous cell types. Here, we introduce a deconvolution method, conditional autoregressive-based deconvolution (CARD), that combines cell-type-specific expression information from single-cell RNA sequencing (scRNA-seq) with correlation in cell-type composition across tissue locations. Modeling spatial correlation allows us to borrow the cell-type composition information across locations, improving accuracy of deconvolution even with a mismatched scRNA-seq reference. CARD can also impute cell-type compositions and gene expression levels at unmeasured tissue locations to enable the construction of a refined spatial tissue map with a resolution arbitrarily higher than that measured in the original study and can perform deconvolution without an scRNA-seq reference. Applications to four datasets, including a pancreatic cancer dataset, identified multiple cell types and molecular markers with distinct spatial localization that define the progression, heterogeneity and compartmentalization of pancreatic cancer.

Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment

Transcriptional heterogeneity among malignant cells of a tumor has been studied in individual cancer types and shown to be organized into cancer cell states; however, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Here, we perform a pan-cancer single-cell RNA-sequencing analysis across 15 cancer types and identify a catalog of gene modules whose expression defines recurrent cancer cell states including 'stress', 'interferon response', 'epithelial-mesenchymal transition', 'metal response', 'basal' and 'ciliated'. Spatial transcriptomic analysis linked the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Using mouse models, we further found that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. Our work provides a framework for studying how cancer cell states interact with the tumor microenvironment to form organized systems capable of immune evasion, drug resistance and metastasis.

TM4SF1 promotes esophageal squamous cell carcinoma metastasis by interacting with integrin α6

Transmembrane-4 L-six family member-1 (TM4SF1) is a member of the L6 family and functions as a signal transducer to regulate tumor cell behaviors. However, the function and mechanism of TM4SF1 in esophageal squamous cell carcinoma (ESCC) metastasis remains unclear. Here, we find that TM4SF1 expression is increased and positively correlated with clinical TNM stage, N classification, differentiation, tumor size, and poor prognosis in ESCC patients. Interestingly, we demonstrate that TM4SF1 promotes ESCC cell adhesion, spreading, migration, and invasion, but not cell proliferation, in a laminin-dependent manner by interacting with integrin α6. Mechanistically, the TM4SF1/integrin α6/FAK axis signal pathway mediates cell migration under laminin-coating condition. Inhibiting FAK or knocking down TM4SF1 can attenuate TM4SF1-mediated cell migration and lung metastasis. Clinically, the TM4SF1/integrin α6/FAK axis positively correlates with ESCC. Altogether, these findings reveal a new mechanism of TM4SF1 in promoting ESCC metastasis via binding to integrin α6 and suggest that the cross-talk between TM4SF1 and integrin α6 may serve as a therapeutic target for ESCC.

MicroRNA-501-3p targeting TM4SF1 facilitates tumor-related behaviors of gastric cancer cells via EMT signaling pathway

BACKGROUND

Increasing evidence shows that Transmembrane 4 L6 family member 1(TM4SF1) exerts a critical role in mediating the progression of various tumors. Nevertheless, the exact mechanism of TM4SF1 in gastric cancer (GC) remains unclear.

METHODS

Bioinformatics analysis was utilized to analyze TM4SF1 expression in GC tissues. Also, MiRWalk and starBase databases were used to predict the upstream microRNAs which could regulate TM4SF1 expression. Gene set enrichment analysis (GSEA) for TM4SF1 was conducted to screen the potentially involved pathways. Dysregulation of microRNA-501-3p/TM4SF1 was implemented to investigate the regulatory roles of these genes in GC. qRT-PCR and western blot were employed to measure the expression changes of microRNA-501-3p, TM4SF1, and epithelial-mesenchymal transition (EMT) signaling pathway-associated proteins. CCK-8, colony formation, and transwell assays were introduced to examine the biological functions of GC cell lines.

RESULTS

TM4SF1 presented a significantly low level in mRNA and protein in GC cells. MicroRNA-501-3p could target TM4SF1 and reduce its expression. Cell function experiments revealed that microRNA-501-3p facilitated cell proliferation, migration, and invasion, while inhibiting cell apoptosis in GC by targeting TM4SF1. EMT-associated proteins were altered by changing microRNA-501-3p/TM4SF1 axis.

CONCLUSION

MicroRNA-501-3p regulated EMT signaling pathway by down-regulating TM4SF1 expression and therefore facilitated the malignant progression of GC, which may provide a new potential therapeutic target for the treatment of GC patients.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression

High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).

Identification of three hub genes related to the prognosis of idiopathic pulmonary fibrosis using bioinformatics analysis

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic respiratory disease characterized by peripheral distribution of bilateral pulmonary fibrosis that is more pronounced at the base. IPF has a short median survival time and a poor prognosis. Therefore, it is necessary to identify effective prognostic indicators to guide the treatment of patients with IPF. Methods: We downloaded microarray data of bronchoalveolar lavage cells from the Gene Expression Omnibus (GEO), containing 176 IPF patients and 20 controls. The top 5,000 genes in the median absolute deviation were classified into different color modules using weighted gene co-expression network analysis (WGCNA), and the modules significantly associated with both survival time and survival status were identified as prognostic modules. We used Lasso Cox regression and multivariate Cox regression to search for hub genes related to prognosis from the differentially expressed genes (DEGs) in the prognostic modules and constructed a risk model and nomogram accordingly. Moreover, based on the risk model, we divided IPF patients into high-risk and low-risk groups to determine the biological functions and immune cell subtypes associated with the prognosis of IPF using gene set enrichment analysis and immune cell infiltration analysis. Results: A total of 153 DEGs located in the prognostic modules, three (TPST1, MRVI1, and TM4SF1) of which were eventually defined as prognostic hub genes. A risk model was constructed based on the expression levels of the three hub genes, and the accuracy of the model was evaluated using time-dependent receiver operating characteristic (ROC) curves. The areas under the curve for 1-, 2-, and 3-year survival rates were 0.862, 0.885, and 0.833, respectively. The results of enrichment analysis showed that inflammation and immune processes significantly affected the prognosis of patients with IPF. The degree of mast and natural killer (NK) cell infiltration also increases the prognostic risk of IPF. Conclusions: We identified three hub genes as independent molecular markers to predict the prognosis of patients with IPF and constructed a prognostic model that may be helpful in promoting therapeutic gains for IPF patients.

Role of Transmembrane 4 L Six Family 1 in the Development and Progression of Cancer

Transmembrane 4 L six family 1 (TM4SF1) is a protein with four transmembrane domains that belongs to the transmembrane 4 L six family members (TM4SFs). Structurally, TM4SF1 consists of four transmembrane domains (TM1-4), N- and C-terminal intracellular domains, two extracellular domains, a smaller domain between TM1 and TM2, and a larger domain between TM3 and TM4. Within the cell, TM4SF1 is located at the cell surface where it transmits extracellular signals into the cytoplasm. TM4SF1 interacts with tetraspanins, integrin, receptor tyrosine kinases, and other proteins to form tetraspanin-enriched microdomains. This interaction affects the pro-migratory activity of the cells, and thus it plays important roles in the development and progression of cancer. TM4SF1 has been shown to be overexpressed in many malignant tumors, including gliomas; malignant melanomas; and liver, prostate, breast, pancreatic, bladder, colon, lung, gastric, ovarian, and thyroid cancers. TM4SF1 promotes the migration and invasion of cancer cells by inducing epithelial-mesenchymal transition, self-renewal ability, tumor angiogenesis, invadopodia formation, and regulating the related signaling pathway. TM4SF1 is an independent prognostic indicator and biomarker in several cancers. It also promotes drug resistance, which is a major cause of therapeutic failure. These characteristics make TM4SF1 an attractive target for antibody-based immunotherapy. Here, we review the many functions of TM4SF1 in malignant tumors, with the aim to understand the interaction between its expression and the biological behaviors of cancer and to supply a basis for exploring new therapeutic targets.

Current updates on the role of reactive oxygen species in bladder cancer pathogenesis and therapeutics

Bladder cancer (BCa) is the fourth most common urological malignancy in the world, it has become the costliest cancer to manage due to its high rate of recurrence and lack of effective treatment modalities. As a natural byproduct of cellular metabolism, reactive oxygen species (ROS) have an important role in cell signaling and homeostasis. Although up-regulation of ROS is known to induce tumorigenesis, growing evidence suggests a number of agents that can selectively kill cancer cells through ROS induction. In particular, accumulation of ROS results in oxidative stress-induced apoptosis in cancer cells. So, ROS is a double-edged sword. A modest level of ROS is required for cancer cells to survive, whereas excessive levels kill them. This review summarizes the up-to-date findings of oxidative stress-regulated signaling pathways and transcription factors involved in the etiology and progression of BCa and explores the possible therapeutic implications of ROS regulators as therapeutic agents for BCa.

Lost miR-141 and upregulated TM4SF1 expressions associate with poor prognosis of pancreatic cancer: regulation of EMT and angiogenesis by miR-141 and TM4SF1 via AKT

Background: Transmembrane-4-L-six-family-1 (TM4SF1) functions to regulate cell growth and mobility and TM4SF1 expression was upregulated in pancreatic cancer. This study further investigated the role of TM4SF1 in regulating pancreatic cancer epithelial-mesenchymal transition (EMT) and angiogenesis and the underlying molecular events.Methods: Tissue specimens were collected from 90 pancreatic cancer patients for immunohistochemical and qRT-PCR analysis of miR-141 and TM4SF1 levels, respectively. Pancreatic cancer cell lines were used for in vitro assays, while nude mice were used for the in vivo assay.Results: TM4SF1 expression was upregulated, whereas miR-141 expression was lost in pancreatic cancer tissues, both of which was associated with advanced clinicopathological features and poor survival of pancreatic cancer patients. Furthermore, miR-141 was able to target and reduce TM4SF1 expression in pancreatic cancer cells and miR-141 expression inhibited pancreatic cancer cell EMT in vitro and Matrigel plug angiogenesis and lung metastasis in nude mice. At the gene level, miR-141 directly targeted and reduced TM4SF1 expression and in turn induced E-cadherin expression and reduced VEGF-A expression by suppressing activation of the AKT signaling pathway.Conclusions: This study demonstrated that upregulated TM4SF1 and lost miR-141 expression were associated with advanced clinicopathological features and poor survival of pancreatic cancer patients. Lost miR-141 expression but induced TM4SF1 expression altered expression of VEGF-A and E-cadherin and promoted pancreatic cancer cell EMT and angiogenesis via the AKT signaling pathway, suggesting that targeting of miR-141 and TM4SF1 may be a potential therapeutic strategy to control pancreatic cancer.

Targeting Epithelial Mesenchymal Plasticity in Pancreatic Cancer: A Compendium of Preclinical Discovery in a Heterogeneous Disease

Pancreatic Ductal Adenocarcinoma (PDAC) is a particularly insidious and aggressive disease that causes significant mortality worldwide. The direct correlation between PDAC incidence, disease progression, and mortality highlights the critical need to understand the mechanisms by which PDAC cells rapidly progress to drive metastatic disease in order to identify actionable vulnerabilities. One such proposed vulnerability is epithelial mesenchymal plasticity (EMP), a process whereby neoplastic epithelial cells delaminate from their neighbours, either collectively or individually, allowing for their subsequent invasion into host tissue. This disruption of tissue homeostasis, particularly in PDAC, further promotes cellular transformation by inducing inflammatory interactions with the stromal compartment, which in turn contributes to intratumoural heterogeneity. This review describes the role of EMP in PDAC, and the preclinical target discovery that has been conducted to identify the molecular regulators and effectors of this EMP program. While inhibition of individual targets may provide therapeutic insights, a single 'master-key' remains elusive, making their collective interactions of greater importance in controlling the behaviours' of heterogeneous tumour cell populations. Much work has been undertaken to understand key transcriptional programs that drive EMP in certain contexts, however, a collaborative appreciation for the subtle, context-dependent programs governing EMP regulation is needed in order to design therapeutic strategies to curb PDAC mortality.

TM4SF18 is aberrantly expressed in pancreatic cancer and regulates cell growth

Current therapies for pancreatic ductal adenocarcinoma (PDAC) only modestly impact survival and can be highly toxic. A greater understanding of the molecules regulating this disease is critical for identifying new drug targets and developing more effective therapies. The L6 family of proteins are known to be positive regulators of tumor growth and metastasis among various cancers. However, little is known about the L6 family member TM4SF18. We investigated the expression and localization of the TM4SF18 protein in normal human pancreas and in PDAC tissue. Utilizing immunohistochemistry (IHC) and western blot analysis, our studies for the first time demonstrate that TM4SF18 is highly expressed in PDAC tumor epithelium. Furthermore, we identified TM4SF18 to be expressed in normal acinar tissue and weakly expressed in normal ducts. Although there is minimal expression in normal ducts, we observed increased TM4SF18 levels in preneoplastic ducts and tumor epithelium. To investigate a functional role of TM4SF18 in PDAC we developed stably-expressing inducible shRNA pancreatic cancer cell lines. Knockdown of the TM4SF18 protein led to a significant decrease in Capan-1 cell growth as measured by the MTT assay, demonstrating this molecule to be a novel regulator of PDAC. Uniquely there is no ortholog of the TM4SF18 gene in mouse or rat prompting us to seek other in vivo experimental models. Using IHC and western blot analysis, expression of TM4SF18 was confirmed in the porcine PDAC model, thus we establish an alternative model to investigate this gene. TM4SF18 represents a promising novel biomarker and therapeutic target for pancreatic cancer.

CD146 promotes migration and proliferation in pulmonary large cell neuroendocrine carcinoma cell lines

Dysregulated expression of the cell surface protein, CD146, has been implicated in various types of cancer in humans, including in lung cancer. The present study aimed to clarify the mechanism underlying abnormal CD146 expression in human pulmonary large cell neuroendocrine carcinoma (LCNEC) cell lines (NCI-H460 and NCI-H810). The functions of CD146 were investigated by measuring cell migration and viability following CD146 knockdown or overexpression via small interference RNA and plasmid transfection. The findings demonstrated that decreased protein expression of CD146 could inhibit migration and viability in LCNEC cells. Furthermore, CD146 was determined to influence the expression of epithelial-mesenchymal transition markers (epithelial cadherin, vimentin and Snail) and promoted AKT phosphorylation. The present results imply CD146 may function in the migration and proliferation of pulmonary LCNEC cells.

Clinical significance of TM4SF1 as a tumor suppressor gene in gastric cancer

Transmembrane‐4‐L‐six‐family member‐1 (TM4SF1), a tumor‐associated antigen, is overexpressed in most epithelial cell carcinomas and a potential target for antibody‐mediated therapy. However, the role of TM4SF1 in gastric cancer has not been elucidated. The aim of this study was to investigate the clinical significance of TM4SF1 expression in gastric carcinoma (GC) tissues using 152 GC tissue samples and matched adjacent nontumor tissue samples analyzed by immunohistochemistry, and 13 fresh GC tissue samples analyzed by Western blotting. The results showed that TM4SF1 was heterogeneously expressed in normal gastric mucosa, with a high expression rate in fundus mucosa. Higher levels and strong expression rate of TM4SF1 were associated with GC tissues of higher‐grade differentiation. TM4SF1 levels were lower in gastric cancer tissues than gastric noncancerous tissues. Expression of TM4SF1 was not correlated with USP10 (P = 0.157), S100A12 (P = 0.479), p53 (P = 0.249), or Ki67 (P = 0.166) in GC. The expression of TM4SF1 was significantly and negatively correlated with depth of invasion (P = 0.031), nodal metastasis (P = 0.042), TNM stage (P = 0.030), and Lauren classification (P = 0.026). There was no significant correlation between TM4SF1 expression and age, gender, tumor size, or distant metastasis (P > 0.05). The expression of TM4SF1 was associated with well overall survival (P = 0.0164). The 5‐year survival rate for patients with GC showing TM4SF1 positive was 58.82% (10/17), and the median survival time was 78 months, higher than that (12.90%, 12/93) of patients who were TM4SF1 negative, whose median survival time was 62 months. These data suggested that low expression of TM4SF1 is associated with carcinogenesis and development, tumor progression and invasion of gastric cancer, and poor overall survival of patients with GC. TM4SF1 is a tumor suppressor for GC and a novel prognostic marker for patients with GC.

TM4SF1 regulates apoptosis, cell cycle and ROS metabolism via the PPARγ-SIRT1 feedback loop in human bladder cancer cells

Transmembrane-4-L-Six-Family-1 (TM4SF1) is a member of the L6 family and functions as a signal transducer to regulate cell development, growth and motility. Here we show that TM4SF1 is strongly upregulated in human muscle invasive bladder cancer (MIBC) tissues, corroborating the bioinformatical results of transcriptome analysis. Moreover, tissue microarray (TMA) shows significant correlations (p < 0.05) between high expression of TM4SF1 and T stage, TNM stage, lymph node metastasis status and survival rate of MIBC patients, indicating a positive association between TM4SF1 expression and poorer prognosis. Furthermore, in vitro and in vivo studies indicate that the proliferation of human bladder cancer (BCa) cells is significantly suppressed by knockdown of TM4SF1 (p < 0.05). Functionally, the reduction of TM4SF1 could induce cell cycle arrest and apoptosis possibly via the upregulation of reactive oxygen species (ROS) in BCa cells. In addition, these observations could be recovered by treatment with GW9662 (antagonist of PPARγ) and resveratrol (activator of SIRT1). Taken together, our results suggest that high expression of TM4SF1 predicts poor prognosis of MIBC.

Upregulation of transmembrane 4 L6 family member 1 predicts poor prognosis in invasive breast cancer: A STROBE-compliant article

Transmembrane 4 L6 family member 1 (TM4SF1) belongs to the 4-transmembrane-domain family and functions as an oncogene in multiple human cancers. In this work, we aim to determine TM4SF1 expression and its prognostic impact on patients with invasive breast cancer.Overall, we enrolled 209 invasive breast cancer patients and immunohistochemically examined the expression of TM4SF1 in tumor specimens. The relationship between TM4SF1 expression and clinicopathological parameter and patient survival of breast cancer patients was analyzed.Among the 209 cases, 137 (65.6%) exhibited high expression of TM4SF1. High TM4SF1 expression was significantly associated with advanced histological grade and negative estrogen receptor and progesterone receptor status. Triple-negative breast cancer (TNBC) tumors were more likely to express high levels of TM4SF1 than non-TNBC cases. Patients with high tumoral expression of TM4SF1 had a significantly shorter disease-free survival (DFS; P = .00) and overall survival (OS; P = .01) than those with low expression of TM4SF1. When survival analysis was restricted to the 167 patients (79.9%) receiving adjuvant chemotherapy, TM4SF1 expression was also correlated with poorer DFS and OS (P = .00). In multiple Cox regression analysis TM4SF1 expression remained an independent prognostic indicator for OS and DFS.TM4SF1 is upregulated and serves as an independent poor prognostic indicator in invasive breast cancer.

TM4SF1 promotes the self-renewal of esophageal cancer stem-like cells and is regulated by miR-141

Cancer stem-like cells have been identified in primary human tumors and cancer cell lines. Previously we found TM4SF1 gene was highly expressed in side population (SP) cells from esophageal squamous cell carcinoma (ESCC) cell lines, but the role and underlying mechanism of TM4SF1 in ESCC remain unclear. In this study, we observed TM4SF1 was up-regulated but miR-141 was down-regulated in SP cells isolated from ESCC cell lines. TM4SF1 could stimulate the self-renewal ability and carcinogenicity of esophageal cancer stem-like cells, and promote cell invasion and migration. In miR-141 overexpression cells, the expression of TM4SF1 was significantly reduced. We also found that overexpression of miR-141 could abolish the self-renewal ability and carcinogenicity of esophageal cancer stem-like cells and decrease cell invasion and migration by suppressing TM4SF1. Consequently, TM4SF1 is a direct target gene of miR-141. The regulation of TM4SF1 by miR-141 may play an important role in controlling self-renewals of esophageal cancer stem-like cells. It may also promote the development of new therapeutic strategies and efficient drugs to target ESCC stem-like cells.

SIRT 1 Overexpression is Associated with Metastasis of Pancreatic Ductal Adenocarcinoma (PDAC) and Promotes Migration and Growth of PDAC Cells

Background

SIRT 1, as a class III histone deacetylase (HDAC), is implicated in the initiation and progression of malignancies. However, the association of SIRT 1 with tumorigenesis or progression of pancreatic ductal adenocarcinoma (PDAC) is not clear.

Material/Methods

In our study we investigated SIRT 1 expression in PDAC samples and evaluated the association of SIRT 1 level with the clinical and pathological characteristics of PDAC patients. We investigated the role of SIRT 1 in the migration and growth of PDAC PANC-1 or BxPC-3 cells using gain-of-function and loss-of-function approach.

Results

We demonstrated that SIRT 1 mRNA level was significantly promoted in intra-tumor tissues compared to peri-tumor tissues of PDAC; and SIRT 1 overexpression was markedly associated with distant or lymph node (LN) metastasis of these PDAC tissues. Moreover, the in vitro wound healing assay demonstrated that SIRT 1 overexpression with lentivirus vector markedly promoted the migration of PANC-1 or BxPC-3 cells, whereas SIRT 1 knockdown using SIRT 1 specific siRNA transfection significantly inhibited the migration of PDAC cells. The colony forming assay confirmed SIRT 1 promotion of the growth of PANC-1 or BxPC-3 cells.

Conclusions

In summary, SIRT 1 overexpression is significantly associated with metastasis of PDAC, and overexpressed SIRT 1 plays an important role in pancreatic cancer cell migration and growth. Our data warrants further studies on SIRT 1 as a novel chemotherapeutic target in PDAC.