BMP4 enhances anoikis resistance and chemoresistance of breast cancer cells through canonical BMP signaling

Prognostic Value and Immune Signatures of Anoikis-related Genes in Breast Cancer

From databases of the Cancer Genome Atlas (TCGA) and GSE42568, transcriptome data of breast cancer patients was obtained. Then, anoikis-related genes (ANRGs) were identified and constructed a risk score system. As a threshold value, the median risk score was used to stratify patients into low-risk and high-risk groups. Kaplan-Meier analysis was then conducted to evaluate the prognostic ability of the risk score system, which was validated using GSE7390. Furthermore, we identified potential enrichment of function and tumor immune infiltration in the model. Finally, the biological functions of a risk gene (EPB41L4B) in breast cancer were investigated through in vitro experiments. We constructed a risk score system via 9 prognosis ANRGs (CXCL2, EPB41L4B, SLC7A5, SFRP1, SDC1, BHLHE41, SPINT1, KRT15, and CD24). The Kaplan-Meier analysis showed that both TCGA-BRCA (training set) and GSE7390 (testing set) patients with high-risk status had significantly worse survival outcomes. In addition, the calibration plots were in good agreement with the prognosis prediction. Breast cancer patients with immunosuppressive microenvironment could be screened using risk groups since risk scores were correlated negatively with ESTIMATE score, tumor-infiltration lymphocytes, immune checkpoints, and chemotactic factors. Furthermore, cellular viability and cell migration of cancerous breast cells were inhibited and apoptosis was promoted by down-regulation of EPB41L4B gene expression. Based on ANRGs, a 9-gene prognostic model could be developed to predict breast cancer prognosis; moreover, patients of the high-risk group were in an immunosuppressed tumor microenvironment.

Overexpression of Bmp4 induces microphthalmia by disrupting embryonic neural retina

Microphthalmia, mostly an autosomal dominant disorder, is a worldwide severe congenital ocular malformation that causes visual impairment. Our investigation unveiled a total of 30 genes associated with microphthalmia. Employing the CytoHubba and PPI network, we identified Bmp4 as the most pivotal hub gene. Subsequently, the conditional overexpression of Bmp4 in the retina caused highly distinctive microphthalmia, manifested by retinal disorganization with ganglion cell misalignment. Significant reduction in the number and abnormal distribution location of retinal cells in microphthalmia model mice. Elevated Bmp4 was associated with an increase in retinal apoptosis and a decrease in proliferating cells, which exacerbates the development of microphthalmia. Here we identify Bmp4 as an extremely important gene responsible for microphthalmia and the involved mechanisms. Overexpression of Bmp4 induces retinal cell ectopic expression and developmental defects, highlighting the importance of a well-balanced Bmp4 level in shaping the embryonic retina during early development.

Exploring the interplay between triple-negative breast cancer stem cells and tumor microenvironment for effective therapeutic strategies

Triple-negative breast cancer (TNBC) is a highly aggressive and metastatic malignancy with poor treatment outcomes. The interaction between the tumor microenvironment (TME) and breast cancer stem cells (BCSCs) plays an important role in the development of TNBC. Owing to their ability of self-renewal and multidirectional differentiation, BCSCs maintain tumor growth, drive metastatic colonization, and facilitate the development of drug resistance. TME is the main factor regulating the phenotype and metastasis of BCSCs. Immune cells, cancer-related fibroblasts (CAFs), cytokines, mesenchymal cells, endothelial cells, and extracellular matrix within the TME form a complex communication network, exert highly selective pressure on the tumor, and provide a conducive environment for the formation of BCSC niches. Tumor growth and metastasis can be controlled by targeting the TME to eliminate BCSC niches or targeting BCSCs to modify the TME. These approaches may improve the treatment outcomes and possess great application potential in clinical settings. In this review, we summarized the relationship between BCSCs and the progression and drug resistance of TNBC, especially focusing on the interaction between BCSCs and TME. In addition, we discussed therapeutic strategies that target the TME to inhibit or eliminate BCSCs, providing valuable insights into the clinical treatment of TNBC.

Targeting anoikis resistance as a strategy for cancer therapy

Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. Uncovering the mechanisms of anoikis resistance will provide details about cancer metastasis, and potential strategies against cancer cell dissemination and metastasis. Here, we summarize the principal elements and core molecular mechanisms of anoikis and anoikis resistance. We discuss the latest progress of how anoikis and anoikis resistance are regulated in cancers. Furthermore, we summarize emerging data on selective compounds and nanomedicines, explaining how inhibiting anoikis resistance can serve as a meaningful treatment modality against cancers. Finally, we discuss the key limitations of this therapeutic paradigm and possible strategies to overcome them. In this review, we suggest that pharmacological modulation of anoikis and anoikis resistance by bioactive compounds could surmount anoikis resistance, highlighting a promising therapeutic regimen that could be used to overcome anoikis resistance in cancers.

Immunotherapeutic Strategies Targeting Breast Cancer Stem Cells

Breast cancer is the most commonly diagnosed cancer in women and is a leading cause of cancer death in women worldwide. Despite the implementation of multiple treatment options, including immunotherapy, breast cancer treatment remains a challenge. In this review, we aim to summarize present challenges in breast cancer immunotherapy and recent advancements in overcoming treatment resistance. We elaborate on the inhibition of signaling cascades, such as the Notch, Hedgehog, Hippo, and WNT signaling pathways, which regulate the self-renewal and differentiation of breast cancer stem cells and, consequently, disease progression and survival. Cancer stem cells represent a rare population of cancer cells, likely originating from non-malignant stem or progenitor cells, with the ability to evade immune surveillance and develop resistance to immunotherapeutic treatments. We also discuss the interactions between breast cancer stem cells and the immune system, including potential agents targeting breast cancer stem cell-associated signaling pathways, and provide an overview of the emerging approaches to breast cancer stem cell-targeted immunotherapy. Finally, we consider the development of breast cancer vaccines and adoptive cellular therapies, which train the immune system to recognize tumor-associated antigens, for eliciting T cell-mediated responses to target breast cancer stem cells.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction

Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.

Anoikis patterns via machine learning strategy and experimental verification exhibit distinct prognostic and immune landscapes in melanoma

BACKGROUND

Anoikis is a cell death programmed to eliminate dysfunctional or damaged cells induced by detachment from the extracellular matrix. Utilizing an anoikis-based risk stratification is anticipated to understand melanoma's prognostic and immune landscapes comprehensively.

METHODS

Differential expression genes (DEGs) were analyzed between melanoma and normal skin tissues in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data sets. Next, least absolute shrinkage and selection operator, support vector machine-recursive feature elimination algorithm, and univariate and multivariate Cox analyses on the 308 DEGs were performed to build the prognostic signature in the TCGA-melanoma data set. Finally, the signature was validated in GSE65904 and GSE22155 data sets. NOTCH3, PIK3R2, and SOD2 were validated in our clinical samples by immunohistochemistry.

RESULTS

The prognostic model for melanoma patients was developed utilizing ten hub anoikis-related genes. The overall survival (OS) of patients in the high-risk subgroup, which was classified by the optimal cutoff value, was remarkably shorter in the TCGA-melanoma, GSE65904, and GSE22155 data sets. Low-risk patients exhibited low immune cell infiltration and high expression of immunophenoscores and immune checkpoints. They also demonstrated increased sensitivity to various drugs, including dasatinib and dabrafenib. NOTCH3, PIK3R2, and SOD2 were notably associated with OS by univariate Cox analysis in the GSE65904 data set. The clinical melanoma samples showed remarkably higher protein expressions of NOTCH3 (P = 0.003) and PIK3R2 (P = 0.009) than the para-melanoma samples, while the SOD2 protein expression remained unchanged.

CONCLUSIONS

In this study, we successfully established a prognostic anoikis-connected signature using machine learning. This model may aid in evaluating patient prognosis, clinical characteristics, and immune treatment modalities for melanoma.

Therapeutic vulnerabilities in triple negative breast cancer: Stem-like traits explored within molecular classification

Triple Negative Breast Cancer (TNBC) is the most aggressive type of breast cancer (BC). Despite advances in the clinical management of TNBC, recurrence-related mortality remains a challenge. The stem-like phenotype of TNBC plays a significant role in the persistence of minimal disease residue after therapy. Individuals exhibiting stem-like characteristics are particularly prone to inducing malignant relapse accompanied by strong resistance. Therefore, stem-like traits have been broadly proposed as therapeutic vulnerabilities to treat TNBC and reduce recurrence. However, heterogeneity within TNBC often generally restricts the stability of the therapeutic efficacy. To understand the heterogeneity and manage TNBC more precisely, multiple TNBC subtyping categories have been reported, providing the basis for profile-according therapeutic regimens. To provide more insight into targeting stem-like traits to ablate TNBC and reduce recurrence in the context of heterogeneity, this paper reviewed the molecular subtyping of TNBC, identified the consensus subtypes with distinct stem-like phenotypes, characterized the stemness hierarchy of TNBC, outlined the biological models for stem-like TNBC subtypes, summarized the therapeutic vulnerabilities in stem-like traits of the subtypes, and proposed potential therapeutic regimens targeting stem-like characteristics to improve TNBC prognosis.

The anoikis-related gene signature predicts survival and correlates with immune infiltration in osteosarcoma

Anoikis is essential for the progression of many malignant tumors. However, the understanding of anoikis' roles in osteosarcoma remains scarce. This study conducted an extensive bioinformatics analysis to identify anoikis-related genes (ARGs), developed ARGs modeles for predicting OS and RFS, and evaluated the effect of these ARGs on osteosarcoma cell migration and invasion. The GSE16088 and GSE28425 datasets provided the differentially expressed genes (DEGs). The prognostic significance and functions of these DEGs were systematically investigated using several bioinformatics techniques. Transwell assays were conducted to determine the effect of OGT on osteosarcoma cell migration and invasion. Seven genes were identified as hub genes, including FN1, CD44, HRAS, TP53, PPARG, CTNNB1, and VEGFA, while 71 ARGs were identified as DEGs. Four ARGs-BRMS, COL4A2, FGF2, and OGT-were used to develop an RFS-predicting model, whereas seven ARGs-CD24, FASN, MMP2, EIF2AK3, ID2, PPARG, and PIK3R3-were used to develop an OS-predicting model in patients with osteosarcoma. In both the training and validation cohorts, high-risk group patients had significantly shorter OS and RFS duration than low-risk group patients. Furthermore, using the aforementioned ARGs, we developed clinically applicable nomograms for OS and RFS prediction. The proportion of tumor-infiltrating immune cells was significantly linked to risk scores. In vitro experiments revealed that knocking down OGT significantly inhibited the ability of MG63 and U2OS cells to invade and migrate. ARG-based gene signatures reliably predicted RFS and OS in osteosarcoma, and OGT showed promise as a potential biomarker. These findings contribute to a better understanding of ARGs' prognostic roles in osteosarcoma.

Anoikis regulator GLI2 promotes NC cell immunity escape by TGF-β-mediated non-classic hedgehog signaling in colorectal cancer: based on artificial intelligence and big data analysis

BACKGROUND

Anoikis is a speed-limited procedure to inhibit tumor metastasis during epithelial-mesenchymal transition (EMT). Previous studies have explored anoikis-related genes (ARG) in predicting prognosis and distinguishing tumoral immunity in many types of cancer. However, the role of ARGs in regulating NK cell exhaustion (NKE) and in predicting chemotherapy sensitivity is not clear. Therefore, it is necessary to work on it.

METHODS

Gene expression profiles and clinical features are collected from TCGA and GEO, and data analysis is performed in R4.2.0.

RESULTS

The ARGs-based no-supervised learning algorithm identifies three ARG subgroups, amongst which the prognosis is different. WCGNA and Artificial intelligence (AI) are applied to construct an NKE-related drug sensitivity stratification and prognosis identification model in digestive system cancer. Pathways association analysis screens out GLI2 is a key gene in regulating NKE by non-classic Hedgehog signaling (GLI2/TGF-β/IL6). In vitro experiments show that down-regulation of GLI2 enhances the CAPE-mediated cell toxicity and accompanies with down-regulation of PD-L1, tumor-derive IL6, and snial1 whereas the expression of cleaved caspas3, cleaved caspase4, cleaved PARP, and E-cadherin are up-regulated in colorectal cancer. Co-culture experiments show that GLI2- decreased colorectal tumor cells lead to down-regulation of TIM-3 and PD1 in NK cells, which are restored by TGF-bate active protein powder. Besides, the Elisa assay shows that GLI2-decreased colorectal tumor cells lead to up-regulation of IFN-gamma in NK cells.

Development of adaptive anoikis resistance promotes metastasis that can be overcome by CDK8/19 Mediator kinase inhibition

Anoikis resistance or evasion of cell death triggered by cell detachment into suspension is a hallmark of cancer that is concurrent with cell survival and metastasis. The effects of frequent matrix detachment encounters on the development of anoikis resistance in cancer remains poorly defined. Here we show using a panel of ovarian cancer models, that repeated exposure to suspension stress in vitro followed by attached recovery growth leads to the development of anoikis resistance paralleling in vivo development of anoikis resistance in ovarian cancer ascites. This resistance is concurrent with enhanced invasion, chemoresistance and the ability of anoikis adapted cells to metastasize to distant sites. Adapted anoikis resistant cells show a heightened dependency on oxidative phosphorylation and can also evade immune surveillance. We find that such acquired anoikis resistance is not genetic, as acquired resistance persists for a finite duration in the absence of suspension stress. Transcriptional reprogramming is however essential to this process, as acquisition of adaptive anoikis resistance in vitro and in vivo is exquisitely sensitive to inhibition of CDK8/19 Mediator kinase, a pleiotropic regulator of transcriptional reprogramming. Our data demonstrate that growth after recovery from repeated exposure to suspension stress is a direct contributor to metastasis and that inhibition of CDK8/19 Mediator kinase during such adaptation provides a therapeutic opportunity to prevent both local and distant metastasis in cancer.

Self-Renewal Inhibition in Breast Cancer Stem Cells: Moonlight Role of PEDF in Breast Cancer

Breast cancer is the leading cause of death among females in developed countries. Although the implementation of screening tests and the development of new therapies have increased the probability of remission, relapse rates remain high. Numerous studies have indicated the connection between cancer-initiating cells and slow cellular cycle cells, identified by their capacity to retain long labeling (LT+). In this study, we perform new assays showing how stem cell self-renewal modulating proteins, such as PEDF, can modify the properties, percentage of biomarker-expressing cells, and carcinogenicity of cancer stem cells. The PEDF signaling pathway could be a useful tool for controlling cancer stem cells' self-renewal and therefore control patient relapse, as PEDF enhances resistance in breast cancer patient cells' in vitro culture. We have designed a peptide consisting of the C-terminal part of this protein, which acts by blocking endogenous PEDF in cell culture assays. We demonstrate that it is possible to interfere with the self-renewal capacity of cancer stem cells, induce anoikis in vivo, and reduce resistance against docetaxel treatment in cancer patient cells in in vitro culture. We have also demonstrated that this modified PEDF protein produces a significant decrease in the percentage of expressed cancer stem cell markers.

A novel anoikis-related gene signature predicts prognosis in patients with breast cancer and reveals immune infiltration

Breast cancer (BRCA) is a common malignancy worldwide that is associated with a high mortality rate. Despite recent improvements in diagnosis and treatment, there is an urgent need to investigate the processes underlying cancer progression and identify novel prognostic indicators. Anoikis, which plays a role in the development of human malignant tumors, has been gaining increasing interest from researchers. However, the potential role of anoikis-related genes (ANRGs) in the advancement of BRCA remains unknown. In this study, we aimed to assess the predictive value of ANRGs in BRCA, construct a prognostic model based on ANRGs, and explore the tumor microenvironment in different prognostic score groups. This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect clinical information and RNA sequencing data from patients with BRCA. Information on ANRGs was gathered from GeneCards and Harmonizome portals. A risk score model based on ANRGs was created using least absolute shrinkage and selection operator Cox (LASSO) regression analysis. Additionally, the study explored the tumor microenvironment and enriched pathways in different risk groups. Finally, a novel ANRG-based nomogram is developed. A total of 142 differentially expressed genes associated with survival were identified, of which 5 genes were selected to create the ANRG signature. The risk score based on this signature proved to be an independent prognostic factor. Further analysis revealed that different risk subgroups exhibited variations in the tumor microenvironment and drug sensitivities. Subsequently, a nomogram was developed using risk scores and clinicopathological factors. The decision curve analysis results suggest that patients with BRCA might derive clinical treatment benefits from utilizing this prognostic model. Based on the results of this study, the ANRG signature and nomograph established can be used for clinical decision-making in patients with BRCA.

BMP signaling inhibition overcomes chemoresistance of prostate cancer

Chemoresistance is a major therapeutic challenge to prostate cancer and its underlying molecular mechanism is poorly understood. Previously, it has been suggested that bone morphogenetic protein (BMP) signaling is down-regulated during the prostate cancer progression from the early androgen-sensitive stage to the metastatic castration-resistant stage. However, no literature reports are available for BMP signaling in more advanced-chemoresistant prostate cancer. In this study, we found the expression levels of the BMP type I receptor members, Activin-like kinase-2 (ALK2) and Activin-like kinase-3 (ALK3), were significantly higher in the chemoresistant prostate cancer cells than those in the chemosensitive prostate cancer cells. In addition, the phospho-Smad1/5/9 proteins, the pivotal intracellular effectors of the BMP signaling, were notably elevated in the chemoresistant prostate cancer cells over the chemosensitive prostate cancer cells, indicating that BMP signaling is highly activated in the chemoresistant prostate cancer cells. We also found that BMP signaling inhibition with either DMH1 or the knockdown of ALK2/ALK3 sensitized chemoresistant prostate cancer cells to the chemotherapy drug docetaxel in a dose-dependent manner. Our further study indicates that DMH1 suppressed the migration and invasion of chemoresistant prostate cancer cells in vitro, and attenuated chemoresistant prostate tumor growth in the mouse xenograft model in vivo. In addition, we showed that DMH1 disrupted the sphere formation in DU145-TxR and PC3-TxR cells, and suppressed the expression of marker genes of the cancer stem cells (CSCs). In conclusion, our study demonstrates that BMP signaling is associated with prostate cancer chemoresistance and BMP signaling inhibition effectively overcomes the cancer chemoresistance potentially through the disruption of CSCs' stemness.

Predicting the immune microenvironment and prognosis with a anoikis - related signature in breast cancer

Background

Tumor heterogeneity is widely recognized as a crucial factor impacting the prognosis of breast cancer (BC) patients. However, there remains an insufficient understanding of the underlying impact of anoikis on the prognosis of BC patients.

Methods

The researchers utilized the TCGA-BRCA dataset to screen and analyze the differentially expressed genes of anoikis-related genes (ARGs) in BC and normal breast tissue. Prognostic gene signatures were established through univariate, LASSO, and multivariate Cox regression analyses. These signatures were evaluated using Kaplan-Meier curve and receiver operating characteristic (ROC) analyses, resulting in the development of an anoikis-related index (ACI). The training dataset was TCGA-BRCA, while METABRIC and GSE96058 were used for external validation. Additionally, nomograms were developed by combining risk scores and clinical parameters, enabling gene set enrichment analysis (GSEA) and tumor immunoassay. Furthermore, an exploration of small molecule compounds was conducted to identify potential therapeutic benefits.

Results

A six-gene anoikis-related signature was constructed, which divided BC patients into high- and low-ACI groups based on median ACI scores. The ACI accurately predicted prognosis and acted as an independent prognostic factor for BC patients. Patients in the high-ACI group exhibited poorer overall survival (OS) across all cohorts and showed more severe clinical manifestations compared to the low-ACI group. The study also explored the potential impacts of anoikis on immune cells infiltrating tumors, immune checkpoints, growth factors, and cytokine levels. Additionally, the potential implications of anoikis in BC immunotherapy were discussed, along with highlighting small molecule compounds that could offer therapeutic benefits.

Conclusions

Anoikis was found to hold significant prognostic value in breast cancer, providing a novel approach for managing patients with different prognoses and implementing more precise immunotherapy strategies.

PCTAIRE Protein Kinase 1 (PCTK1) Suppresses Proliferation, Stemness, and Chemoresistance in Colorectal Cancer through the BMPR1B-Smad1/5/8 Signaling Pathway

Colorectal cancer (CRC) is the third most common cancer and a leading cause of cancer-related mortality worldwide. Even with advances in therapy, CRC mortality remains high. Therefore, there is an urgent need to develop effective therapeutics for CRC. PCTAIRE protein kinase 1 (PCTK1) is an atypical member of the cyclin-dependent kinase (CDK) family, and the function of PCTK1 in CRC is poorly understood. In this study, we found that patients with elevated PCTK1 levels had a better overall survival rate in CRC based on the TCGA dataset. Functional analysis also showed that PCTK1 suppressed cancer stemness and cell proliferation by using PCTK1 knockdown (PCTK1-KD) or knockout (PCTK1-KO) and PCTK1 overexpression (PCTK1-over) CRC cell lines. Furthermore, overexpression of PCTK1 decreased xenograft tumor growth and knockout of PCTK1 significantly increased in vivo tumor growth. Moreover, knockout of PCTK1 was observed to increase the resistance of CRC cells to both irinotecan (CPT-11) alone and in combination with 5-fluorouracil (5-FU). Additionally, the fold change of the anti-apoptotic molecules (Bcl-2 and Bcl-xL) and the proapoptotic molecules (Bax, c-PARP, p53, and c-caspase3) was reflected in the chemoresistance of PCTK1-KO CRC cells. PCTK1 signaling in the regulation of cancer progression and chemoresponse was analyzed using RNA sequencing and gene set enrichment analysis (GSEA). Furthermore, PCTK1 and Bone Morphogenetic Protein Receptor Type 1B (BMPR1B) in CRC tumors were negatively correlated in CRC patients from the Timer2.0 and cBioPortal database. We also found that BMPR1B was negatively correlated with PCTK1 in CRC cells, and BMPR1B expression was upregulated in PCTK1-KO cells and xenograft tumor tissues. Finally, BMPR1B-KD partially reversed cell proliferation, cancer stemness, and chemoresistance in PCTK1-KO cells. Moreover, the nuclear translocation of Smad1/5/8, a downstream molecule of BMPR1B, was increased in PCTK1-KO cells. Pharmacological inhibition of Smad1/5/8 also suppressed the malignant progression of CRC. Taken together, our results indicated that PCTK1 suppresses proliferation and cancer stemness and increases the chemoresponse of CRC through the BMPR1B-Smad1/5/8 signaling pathway.

Aberrant expression of bone morphogenetic proteins in the disease progression and metastasis of breast cancer

Background

Bone morphogenetic proteins (BMPs) play crucial roles in the tumorigenesis and metastasis of cancers. Controversy remains about the exact implications of BMPs and their antagonists in breast cancer (BC), due to their diverse and complex biological functions and signalling. A comprehensive study of the whole family and their signalling in breast cancer is provoked.

Methods

Aberrant expression of BMP, BMP receptors and antagonists in primary tumours in breast cancer were analysed by using TCGA-BRCA and E-MTAB-6703 cohorts. Related biomarkers including ER, HER, proliferation, invasion, angiogenesis, lymphangiogenesis and bone metastasis were involved to identify the relationship with BMPs in breast cancer.

Results

The present study showed BMP8B was significantly increased in breast tumours, while BMP6 and ACVRL1 were decreased in breast cancer tissues. The expressions of BMP2, BMP6, TGFBR1 and GREM1 were significantly correlated with BC patients' poor overall survival. Aberrant expression of BMPs, together with BMP receptors, were explored in different subtypes of breast cancer according to ER, PR and HER2 status. Furthermore, higher levels of BMP2, BMP6 and GDF5 were revealed in triple negative breast cancer (TNBC) whilst BMP4, GDF15, ACVR1B, ACVR2B and BMPR1B were relatively higher in Luminal type BC. ACVR1B and BMPR1B were positively correlated with ERα but were inversely correlated with ERβ. High expression of GDF15, BMP4 and ACVR1B were associated with poorer overall survival in HER2 positive BC. BMPs also play dual roles in tumour growth and metastasis of BC.

Conclusion

A shift pattern of BMPs was showed in different subtypes of breast cancer suggesting a subtype specific involvement. It provokes more research to shed light on the exact role of these BMPs and receptors in the disease progression and distant metastasis through a regulation of proliferation, invasion and EMT.

Vestigial-like 1 (VGLL1): An ancient co-transcriptional activator linking wing, placenta, and tumor development

Vestigial-like 1 (VGLL1) is a recently discovered driver of proliferation and invasion that is expressed in many aggressive human malignancies and is strongly associated with poor prognosis. The VGLL1 gene encodes for a co-transcriptional activator that shows intriguing structural similarity to key activators in the hippo pathway, providing important clues to its functional role. VGLL1 binds to TEADs in an analogous fashion to YAP1 but appears to activate a distinct set of downstream gene targets. In mammals, VGLL1 expression is found almost exclusively in placental trophoblasts, cells that share many hallmarks of cancer. Due to its role as a driver of tumor progression, VGLL1 has become a target of interest for potential anticancer therapies. In this review, we discuss VGLL1 from an evolutionary perspective, contrast its role in placental and tumor development, summarize the current knowledge of how signaling pathways can modulate VGLL1 function, and discuss potential approaches for targeting VGLL1 therapeutically.

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

An anoikis-based signature for predicting prognosis in hepatocellular carcinoma with machine learning

Background: Hepatocellular carcinoma (HCC) is a common malignancy with high mortality worldwide. Despite advancements in diagnosis and treatment in recent years, there is still an urgent unmet need to explore the underlying mechanisms and novel prognostic markers. Anoikis has received considerable attention because of its involvement in the progression of human malignancies. However, the potential mechanism of anoikis-related genes (ANRGs) involvement in HCC progression remains unclear. Methods: We use comprehensive bioinformatics analyses to determine the expression profile of ANRGs and their prognostic implications in HCC. Next, a risk score model was established by least absolute shrinkage and selection operator (Lasso) Cox regression analysis. Then, the prognostic value of the risk score in HCC and its correlation with clinical characteristics of HCC patients were further explored. Additionally, machine learning was utilized to identify the outstanding ANRGs to the risk score. Finally, the protein expression of DAP3 was examined on a tissue microarray (TMA), and the potential mechanisms of DAP3 in HCC was explored. Results: ANRGs were dysregulated in HCC, with a low frequency of somatic mutations and associated with prognosis of HCC patients. Then, nine ANRGs were selected to construct a risk score signature based on the LASSO model. The signature presented a strong ability of risk stratification and prediction for overall survival in HCC patients.Additionally, high risk scores were closely correlated with unfavorable clinical features such as advanced pathological stage, poor histological differentiation and vascular invasion. Moreover, The XGBoost algorithm verified that DAP3 was an important risk score contributor. Further immunohistochemistry determined the elevated expression of DAP3 in HCC tissues compared with nontumor tissues. Finally, functional analyses showed that DAP3 may promote HCC progression through multiple cancer-related pathways and suppress immune infiltration. Conclusion: In conclusion, the anoikis-based signature can be utilized as a novel prognostic biomarker for HCC, and DAP3 may play an important role in the development and progression of HCC.

Construction of a novel anoikis-related prognostic model and analysis of its correlation with infiltration of immune cells in neuroblastoma

Background

Anoikis resistance (AR) plays an important role in the process of metastasis, which is an important factor affecting the risk stage of neuroblastoma (NB). This study aims to construct an anoikis-related prognostic model and analyze the characteristics of hub genes, important pathways and tumor microenvironment of anoikis-related subtypes of NB, so as to provide help for the clinical diagnosis, treatment and research of NB.

Methods

We combined transcriptome data of GSE49710 and E-MTAB-8248, screened anoikis-related genes (Args) closely related to the prognosis of NB by univariate cox regression analysis, and divided the samples into anoikis-related subtypes by consistent cluster analysis. WGCNA was used to screen hub genes, GSVA and GSEA were used to analyze the differentially enriched pathways between anoikis-related subtypes. We analyzed the infiltration levels of immune cells between different groups by SsGSEA and CIBERSORT. Lasso and multivariate regression analyses were used to construct a prognostic model. Finally, we analyzed drug sensitivity through the GDSC database.

Results

721 cases and 283 Args were included in this study. All samples were grouped into two subtypes with different prognoses. The analyses of WGCNA, GSVA and GSEA suggested the existence of differentially expressed hub genes and important pathways in the two subtypes. We further constructed an anoikis-related prognostic model, in which 15 Args participated. This model had more advantages in evaluating the prognoses of NB than other commonly used clinical indicators. The infiltration levels of 9 immune cells were significantly different between different risk groups, and 13 Args involved in the model construction were correlated with the infiltration levels of immune cells. There was a relationship between the infiltration levels of 6 immune cells and riskscores. Finally, we screened 15 drugs with more obvious effects on NB in high-risk group.

Conclusion

There are two anoikis-related subtypes with different prognoses in the population of NB. The anoikis-related prognostic model constructed in this study can accurately predict the prognoses of children with NB, and has a good guiding significance for clinical diagnosis, treatment and research of NB.

The Role of Mesenchymal Stem Cells in Modulating the Breast Cancer Microenvironment

The role of mesenchymal stem cells (MSCs) in the breast tumor microenvironment (TME) is significant and multifaceted. MSCs are recruited to breast tumor sites through molecular signals released by tumor sites. Once in the TME, MSCs undergo polarization and interact with various cell populations, including immune cells, cancer-associated fibroblasts (CAFs), cancer stem cells (CSCs), and breast cancer cells. In most cases, MSCs play roles in breast cancer therapeutic resistance, but there is also evidence that indicates their abilities to sensitize cancer cells to chemotherapy and radiotherapy. MSCs possess inherent regenerative and homing properties, making them attractive candidates for cell-based therapies. Therefore, MSCs can be engineered to express therapeutic molecules or deliver anti-cancer agents directly to tumor sites. Unraveling the intricate relationship between MSCs and the breast TME has the potential to uncover novel therapeutic targets and advance our understanding of breast cancer biology.

Effects of Wnt-β-catenin signaling and sclerostin on the phenotypes of rat pheochromocytoma PC12 cells

Pheochromocytomas and paragangliomas (PPGLs) are classified into 3 major categories with distinct driver genes: pseudohypoxia, kinase signaling, and Wnt-altered subtypes. PPGLs in the Wnt-altered subtype are sporadic and tend to be aggressive with metastasis, where somatic gene fusions affecting mastermind-like 3 (MAML3) and somatic mutations in cold shock domain containing E1 (CSDE1) cause overactivation of Wnt-β-catenin signaling. However, the relation between Wnt-β-catenin signaling and the biological behavior of PPGLs remains unexplored. In rat pheochromocytoma PC12 cells, Wnt3a treatment enhanced cell proliferation and suppressed mRNA expression of tyrosine hydroxylase (TH), i.e. the rate-limiting enzyme of catecholamine biosynthesis, and dopamine secretion. We identified the expression of sclerostin in PC12 cells, which is known as an osteocyte-derived negative regulator for Wnt signaling-driven bone formation. Inhibition of endogenous Wnt pathway by XAV939 or sclerostin resulted in attenuated cell proliferation and increased TH expression. Furthermore, Wnt3a pretreatment suppressed bone morphogenetic protein (BMP)-induced Smad1/5/9 phosphorylation whereas BMPs enhanced sclerostin expression in PC12 cells. In the Wnt-altered subtype, the increased Wnt-β-catenin pathway may contribute the aggressive clinical behavior with reduced catecholamine production. Furthermore, up-regulated expression of sclerostin by BMPs may explain the osteolytic metastatic lesions observed in metastatic PPGLs.

Bone Morphogenetic Protein Signaling in Cancer; Some Topics in the Recent 10 Years

Bone morphogenetic proteins (BMPs), members of the transforming growth factor-β (TGF-β) family, are multifunctional cytokines. BMPs have a broad range of functions, and abnormalities in BMP signaling pathways are involved in cancer progression. BMPs activate the proliferation of certain cancer cells. Malignant phenotypes of cancer cells, such as increased motility, invasiveness, and stemness, are enhanced by BMPs. Simultaneously, BMPs act on various cellular components and regulate angiogenesis in the tumor microenvironment. Thus, BMPs function as pro-tumorigenic factors in various types of cancer. However, similar to TGF-β, which shows both positive and negative effects on tumorigenesis, BMPs also act as tumor suppressors in other types of cancers. In this article, we review important findings published in the recent decade and summarize the pro-oncogenic functions of BMPs and their underlying mechanisms. The current status of BMP-targeted therapies for cancers is also discussed.

Potential of the miR-200 Family as a Target for Developing Anti-Cancer Therapeutics

MicroRNAs (miRNAs) are small non-coding RNAs (18–24 nucleotides) that play significant roles in cell proliferation, development, invasion, cancer development, cancer progression, and anti-cancer drug resistance. miRNAs target multiple genes and play diverse roles. miRNAs can bind to the 3′UTR of target genes and inhibit translation or promote the degradation of target genes. miR-200 family miRNAs mostly act as tumor suppressors and are commonly decreased in cancer. The miR-200 family has been reported as a valuable diagnostic and prognostic marker. This review discusses the clinical value of the miR-200 family, focusing on the role of the miR-200 family in the development of cancer and anti-cancer drug resistance. This review also provides an overview of the factors that regulate the expression of the miR-200 family, targets of miR-200 family miRNAs, and the mechanism of anti-cancer drug resistance regulated by the miR-200 family.