Androgen receptor decreases renal cell carcinoma bone metastases via suppressing the osteolytic formation through altering a novel circEXOC7 regulatory axis

The role of circular RNA during the urological cancer metastasis: exploring regulatory mechanisms and potential therapeutic targets

Metastasis is a major contributor to treatment failure and death in urological cancers, representing an important biomedical challenge at present. Metastases form as a result of cancer cells leaving the primary site, entering the vasculature and lymphatic vessels, and colonizing clones elsewhere in the body. However, the specific regulatory mechanisms of action underlying the metastatic process of urological cancers remain incompletely elucidated. With the deepening of research, circular RNAs (circRNAs) have been found to not only play a significant role in tumor progression and prognosis but also show aberrant expression in various tumor metastases, consequently impacting tumor metastasis through multiple pathways. Therefore, circRNAs are emerging as potential tumor markers and treatment targets. This review summarizes the research progress on elucidating how circRNAs regulate the urological cancer invasion-metastasis cascade response and related processes, as well as their role in immune microenvironment remodeling and circRNA vaccines. This body of work highlights circRNA regulation as an emerging therapeutic target for urological cancers, which should motivate further specific research in this regard.

Development and validation of prognostic nomogram for elderly patients with clear cell renal cell carcinoma based on the SEER database

This study sought to establish nomogram models of overall survival (OS) in patients with elderly clear cell renal cell carcinoma (ECCRCC). The Surveillance, Epidemiology, and End Results database provided data of the ECCRCC-afflicted patients diagnosed during the period from 2010 to 2015. This data was subsequently segregated into the training and validation sets randomly in a 7:3 ratio. The calibration curves, the receiver operating characteristic curves, the decision curve analysis and the Concordance index (C-index) were applied for the model evaluation. 9201 eligible cases from 2010 to 2015 were extracted; 6441 were included in the training cohort and 2760 in the validation cohort. The C-index for the training and validation sets were 0.710 and 0.709, respectively. The receiver operating characteristic and decision curve analysis curves demonstrated that nomograms outperformed the AJCC stage in predictive performance. Moreover, the nomogram was found to match closely with the actual observation, as indicated by the calibration plots. To make predictions with regard to the survival of the ECCRCC-afflicted individuals, and as a guide for treatment, the new nomogram could be used.

Sex differences in renal cell carcinoma: a single-cell analysis reveals exhausted CD8+ T-cells highly infiltrated in males

BACKGROUND

Although sex bias has been reported in the development and progression of renal cell carcinoma (RCC), the underlying mechanisms remain enigmatic. Here, we investigated the sex differences in the tumor microenvironment (TME) of RCC and explored a promising combination drug regimen to enhance the efficacy of immunotherapy.

METHODS

Single-cell RNA sequencing (scRNA-seq) data from four published datasets were analyzed to investigate the sex differences in RCC patients, and tumor tissues were collected to validate the sex differences using multiplex immunofluorescence (MxIF) and flow cytometry (FCM). The function of the androgen-androgen receptor axis in sex differences was explored in vivo and in vitro experiments.

RESULTS

Our analysis of scRNA-seq data from 220,156 cells, as well as MxIF and FCM assays, revealed that CD8+ T-cells infiltrated highly in the TME of male RCC, but were mostly in an exhausted and dysfunctional state. In vitro and in vivo experiments indicated that the dysfunction and exhaustion of CD8+ T-cells in male TME were induced by androgen. Clinically, higher serum androgen was significantly associated with a worse prognosis in male RCC patients receiving immunotherapy. Androgen receptor inhibitors could activate tumor-infiltrating CD8+ T-cells and enhance the efficacy of immunotherapy of RCC in vivo.

CONCLUSIONS

Our study delineated the difference in TME between male and female patients with RCC, and demonstrated that the androgen-androgen receptor axis plays an important role in immunosuppression in male RCC. Our findings suggest that androgen receptor inhibitors in combination with immunotherapy may be a promising treatment option for male RCC patients.

A pan-cancer analysis of the expression and molecular mechanism of DHX9 in human cancers

Finding new targets is necessary for understanding tumorigenesis and developing cancer therapeutics. DExH-box helicase 9 (DHX9) plays a central role in many cellular processes but its expression pattern and prognostic value in most types of cancer remain unclear. In this study, we extracted pan-cancer data from TCGA and GEO databases to explore the prognostic and immunological role of DHX9. The expression levels of DHX9 were then verified in tumor specimens by western blot and immunohistochemistry (IHC). The oncogenic roles of DHX9 in cancers were further verified by in vitro experiments. We first verified that DHX9 is highly expressed in most tumors but significantly decreased in kidney and thyroid cancers, and it is prominently correlated with the prognosis of patients with different tumors. The phosphorylation level of DHX9 was also increased in cancers. Enrichment analysis revealed that DHX9 was involved in Spliceosome, RNA transport and mRNA surveillance pathway. Furthermore, DHX9 expression exhibited strong correlations with immune cell infiltration, immune checkpoint genes, and tumor mutational burden (TMB)/microsatellite instability (MSI). In liver, lung, breast and renal cancer cells, the knockdown or depletion of DHX9 significantly affected the proliferation, metastasis and EMT process of cancer cells. In summary, this pan-cancer investigation provides a comprehensive understanding of the prognostic and immunological role of DHX9 in human cancers, and experiments indicated that DHX9 was a potential target for cancer treatment.

Stranger Things: New Roles and Opportunities for Androgen Receptor in Oncology Beyond Prostate Cancer

The androgen receptor (AR) is one of the oldest therapeutic targets in oncology and continues to dominate the treatment landscape for advanced prostate cancer, where nearly all treatment regimens include some form of AR modulation. In this regard, AR remains the central driver of prostate cancer cell biology. Emerging preclinical and clinical data implicate key roles for AR in additional cancer types, thereby expanding the importance of this drug target beyond prostate cancer. In this mini-review, new roles for AR in other cancer types are discussed as well as their potential for treatment with AR-targeted agents. Our understanding of these additional functions for AR in oncology expand this receptor's potential as a therapeutic target and will help guide the development of new treatment approaches.

Molecular subtypes based on metabolic genes are potential biomarkers for predicting prognosis and immune responses of clear cell renal cell carcinoma

Due to the existence of tumor molecular heterogeneity, even patients having similar clinicopathological features could have vastly different survival rates. Hence, we aimed to explore novel metabolism-associated genes (MAGs) related molecular subtypes for clear cell renal cell carcinoma (ccRCC) and their immune landscapes for predicting prognosis and immune responses. Gene matrices and clinical information were downloaded from TCGA and ICGC datasets. Consensus clustering was conducted by the R "ConsensusClusterPlus" package. ccRCC patients were successfully divided into three clusters (MC1, MC2, and MC3) based on MAGs in both TCGA and ICGC datasets. Our established three MAGs were significantly associated with chemokine/chemokine receptor, IFN, CYT, angiogenesis, immune checkpoint molecules, tumor-infiltrating immune cells, oncogenic pathways, pan-cancer immune subtypes, and tumor microenvironment (TME) scores or expressions. Moreover, these three metabolic ccRCC subtypes could predict immunotherapeutic responses. We further constructed a characteristic index (LDAscore) in three metabolic ccRCC subtypes and identified LDAscore-related modules by WGCNA. After deep data mining, 10 hub genes were obtained and seven genes (ATRX, BPTF, DHX9, EP300, POLR2B, SIN3A, UBE3A) were finally validated by qRT-PCR. Our results successfully established a novel ccRCC subtype based on MAGs, providing novel insights into metabolism-related ccRCC tumor heterogeneity and facilitating individualized therapy for future work.

The DNA/RNA helicase DHX9 contributes to the transcriptional program of the androgen receptor in prostate cancer

Background

Prostate cancer (PC) is the most commonly diagnosed male malignancy and an important cause of mortality. Androgen deprivation therapy is the first line treatment but, unfortunately, a large part of patients evolves to a castration-resistant stage, for which no effective cure is currently available. The DNA/RNA helicase DHX9 is emerging as an important regulator of cellular processes that are often deregulated in cancer.

Methods

To investigate whether DHX9 modulates PC cell transcriptome we performed RNA-sequencing analyses upon DHX9 silencing in the androgen-responsive cell line LNCaP. Bioinformatics and functional analyses were carried out to elucidate the mechanism of gene expression regulation by DHX9. Data from The Cancer Genome Atlas were mined to evaluate the potential role of DHX9 in PC.

Results

We found that up-regulation of DHX9 correlates with advanced stage and is associated with poor prognosis of PC patients. High-throughput RNA-sequencing analysis revealed that depletion of DHX9 in androgen-sensitive LNCaP cells affects expression of hundreds of genes, which significantly overlap with known targets of the Androgen Receptor (AR). Notably, AR binds to the DHX9 promoter and induces its expression, while Enzalutamide-mediated inhibition of AR activity represses DHX9 expression. Moreover, DHX9 interacts with AR in LNCaP cells and its depletion significantly reduced the recruitment of AR to the promoter region of target genes and the ability of AR to promote their expression in response to 5α-dihydrotestosterone. Consistently, silencing of DXH9 negatively affected androgen-induced PC cell proliferation and migration.

Conclusions

Collectively, our data uncover a new role of DHX9 in the control of the AR transcriptional program and establish the existence of an oncogenic DHX9/AR axis, which may represent a new druggable target to counteract PC progression.

Circular RNA circPOLR2A promotes clear cell renal cell carcinoma progression by facilitating the UBE3C-induced ubiquitination of PEBP1 and, thereby, activating the ERK signaling pathway

Background

Increasing evidence has demonstrated that circular RNAs (circRNAs) are implicated in cancer progression. However, the aberrant expression and biological functions of circRNAs in clear cell renal cell carcinoma (cRCC) remain largely elusive.

Method

Differentially expressed circRNAs in cRCC were filtered via bioinformatics analysis. Aberrant circPOLR2A expression was validated in cRCC tissues and cell lines via qRT-PCR. Sanger sequencing was used to identify the backsplicing site of circPOLR2A. In vitro and in vivo functional experiments were performed to evaluate the role of circPOLR2A in cRCC malignancy. RNA pull-down, mass spectrometry, RIP, FISH and immunofluorescence assays were used to identify and validate the circPOLR2A-interacting proteins. Ubiquitination modification and interaction between proteins were detected via Co-IP and western blotting. The m6A modification in circPOLR2A was validated by the meRIP assay.

Results

Bioinformatics analysis revealed that circPOLR2A was highly expressed in cRCC tissues and metastatic cRCC tissues. CircPOLR2A expression was associated with tumor size and TNM stage in cRCC patients. In vitro and in vivo functional assays revealed that circPOLR2A accelerated cRCC cell proliferation, migration, invasion and angiogenesis, while inhibiting apoptosis. Further mechanistic research suggested that circPOLR2A could interact with UBE3C and PEBP1 proteins, and that UBE3C could act as a specific ubiquitin E3 ligase for the PEBP1 protein. The UBE3C/circPOLR2A/PEBP1 protein-RNA ternary complex enhanced the UBE3C-mediated ubiquitination and degradation of the PEBP1 protein which could inactivate the ERK signaling pathway. Rescue experiments revealed that the PEBP1 protein was the functional downstream target of circPOLR2A. Furthermore, m6A modification in circPOLR2A was confirmed, and the m6A reader YTHDF2 could regulate circPOLR2A expression.

Conclusion

Our study demonstrated that circPOLR2A modulated the UBE3C-mediated ubiquitination and degradation of the PEBP1 protein, and further activated the ERK pathway during cRCC progression and metastasis. The m6A reader, YTHDF2, regulated circPOLR2A expression in cRCC. Hence, circPOLR2A could be a potential target for the diagnosis and treatment of cRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-022-01607-8.

Use of Circular RNAs in Diagnosis, Prognosis and Therapeutics of Renal Cell Carcinoma

Renal cell carcinoma is the most common type of kidney cancer, representing 90% of kidney cancer diagnoses, and the deadliest urological cancer. While the incidence and mortality rates by renal cell carcinoma are higher in men compared to women, in both sexes the clinical characteristics are the same, and usually unspecific, thereby hindering and delaying the diagnostic process and increasing the metastatic potential. Regarding treatment, surgical resection remains the main therapeutic strategy. However, even after radical nephrectomy, metastasis may still occur in some patients, with most metastatic renal cell carcinomas being resistant to chemotherapy and radiotherapy. Therefore, the identification of new biomarkers to help clinicians in the early detection, and treatment of renal cell carcinoma is essential. In this review, we describe circRNAs related to renal cell carcinoma processes reported to date and propose the use of some in therapeutic strategies for renal cell carcinoma treatment.

Hsa_circRNA_0088036 acts as a ceRNA to promote bladder cancer progression by sponging miR-140-3p

Circular RNAs (circRNAs) are a class of non-coding RNAs that play vital roles in cancer biology. However, the potential role of hsa_circRNA_0088036 in bladder cancer (BCa) remains unknown. Hsa_circRNA_0088036 was identified by microarray analysis and validated by quantitative real-time polymerase chain reaction. Functional assays were conducted to confirm the effects of hsa_circRNA_0088036 on the growth, migration, invasion, tumorigenesis, and metastasis of BCa cells. The luciferase reporter assay and RNA pull down assay were performed to investigate the interactions between hsa_circRNA_0088036, miR-140-3p, and forkhead box protein Q1 (FOXQ1). Upregulated expression of hsa_circRNA_0088036 in BCa tissues and cell lines was positively correlated with overall survival and clinicopathologic characteristics. Knockdown of hsa_circRNA_0088036 inhibited the growth, migration, and invasion of BCa cells both in vivo and in vitro. Mechanistically, hsa_circRNA_0088036 could directly interact with miR-140-3p and act as a miRNA sponge to modulate FOXQ1 expression. Knockdown of hsa_circRNA_0088036 inhibited the proliferation, migration, and metastasis of BCa cells via miR-140-3p/FOXQ1 signaling, suggesting that hsa_circRNA_0088036 is a potential biomarker and therapeutic target for BCa.

Risk Factors, Prognostic Factors, and Nomograms for Bone Metastasis in Patients with Newly Diagnosed Clear Cell Renal Cell Carcinoma: A Large Population-Based Study

Background

This study aimed to investigate risk factors and prognostic factors in patients with clear cell renal cell carcinoma (ccRCC) with bone metastasis (BM) and establish nomograms to provide a quantitative prediction of the risk of BM and survival probability.

Methods

The clinicopathological characteristics of patients with ccRCC between January 2010 and December 2015 were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Independent factors for BM in ccRCC patients were identified using univariate and multivariate logistic regression analyses. Prognostic factors for predicting cancer-specific death were evaluated using univariate and multivariate analyses based on a competing risk regression model. We then constructed a diagnostic nomogram and a prognostic nomogram. The two nomograms were evaluated using calibration curves, receiver operating characteristic curves, and decision curve analysis.

Results

Our study included 34,659 patients diagnosed with ccRCC in the SEER database, with 1,415 patients who presented with bone metastasis. Risk factors for BM in patients with ccRCC included age, stage T, stage N, brain metastasis, liver metastasis, lung metastasis, tumor size, and laterality. Independent prognostic factors for patients with ccRCC patients with BM were Fuhrman grade, tumor size, T stage, N stage, brain metastases, lung metastasis, and surgery. For the diagnostic nomogram, the area under the curve values in the training and testing cohorts were 0.863 (95% CI, 0.851–0.875) and 0.859 (95% CI, 0.839–0.878), respectively. In the prognostic cohort, the area under the curve values for 1-, 2-, and 3-year cancer-specific survival rates in the training cohort were 0.747, 0.774, and 0.780, respectively, and 0.671, 0.706, and 0.696, respectively, in the testing cohort. Through calibration curves and decision curve analyses, the nomograms displayed excellent performance.

Conclusions

Several factors related to the development and prognosis of BM in patients with ccRCC were identified. The nomograms constructed in this study are expected to become effective and precise tools for clinicians to improve cancer management.

External Validation of the Prognostic Value of an Immune-Associated Gene Panel for Clear Cell Renal Cell Carcinomas

Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrates, and many of them respond to immunotherapy with checkpoint inhibitors including anti-PD-L1 or anti-PD1 agents. However, the effect of immune genes on clinical outcomes in ccRCCs has not been fully studied. Here, we show in this study that an immune-associated gene panel has a prognostic value for clear cell renal cell carcinomas. We performed single-sample gene set enrichment analysis (ssGSEA) and cell type identification by estimating subsets of RNA transcripts (CIBERSORT) algorithms on patient-matched normal renal and RCC tissues to characterize two immunophenotypes and immunological characteristic subpopulations. Furthermore, LASSO Cox regression was applied to develop a novel prognosis-associated model for ccRCC patients based on an immune-gene panel. The results were verified by the Gene Expression Omnibus (GEO) dataset and coordinated with the clinicopathological characteristics of ccRCCs, along with genomic signatures. Finally, based on the above perspectives, we generated a nomogram with a high prognostic efficiency for ccRCC patients. Overall, this study offers a unique perspective that can contribute to improving the accuracy of prognosis prediction and treatment with immunotherapy.

Development and validation of a machine learning model to predict the risk of lymph node metastasis in renal carcinoma

SIMPLE SUMMARY

Studies have shown that about 30% of kidney cancer patients will have metastasis, and lymph node metastasis (LNM) may be related to a poor prognosis. Our retrospective study aims to provide a reliable machine learning-based model to predict the occurrence of LNM in kidney cancer. We screened the pathological grade, liver metastasis, M staging, primary site, T staging, and tumor size from the training group (n=39016) formed by the SEER database and the validation group (n=771) formed by the medical center. Independent predictors of LNM in cancer patients. Using six different algorithms to build a prediction model, it is found that the prediction performance of the XGB model in the training group and the validation group is significantly better than any other machine learning model. The results show that prediction tools based on machine learning can accurately predict the probability of LNM in patients with kidney cancer and have satisfactory clinical application prospects.

BACKGROUND

Lymph node metastasis (LNM) is associated with the prognosis of patients with kidney cancer. This study aimed to provide reliable machine learning-based (ML-based) models to predict the probability of LNM in kidney cancer.

METHODS

Data on patients diagnosed with kidney cancer were extracted from the Surveillance, Epidemiology and Outcomes (SEER) database from 2010 to 2017, and variables were filtered by least absolute shrinkage and selection operator (LASSO), univariate and multivariate logistic regression analyses. Statistically significant risk factors were used to build predictive models. We used 10-fold cross-validation in the validation of the model. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the model. Correlation heat maps were used to investigate the correlation of features using permutation analysis to assess the importance of predictors. Probability density functions (PDFs) and clinical utility curves (CUCs) were used to determine clinical utility thresholds.

RESULTS

The training cohort of this study included 39,016 patients, and the validation cohort included 771 patients. In the two cohorts, 2544 (6.5%) and 66 (8.1%) patients had LNM, respectively. Pathological grade, liver metastasis, M stage, primary site, T stage, and tumor size were independent predictive factors of LNM. In both model validation, the XGB model significantly outperformed any of the machine learning models with an AUC value of 0.916.A web calculator (https://share.streamlit.io/liuwencai4/renal_lnm/main/renal_lnm.py) were built based on the XGB model. Based on the PDF and CUC, we suggested 54.6% as a threshold probability for guiding the diagnosis of LNM, which could distinguish about 89% of LNM patients.

CONCLUSIONS

The predictive tool based on machine learning can precisely indicate the probability of LNM in kidney cancer patients and has a satisfying application prospect in clinical practice.

Development and Validation of a Predictive Model to Evaluate the Risk of Bone Metastasis in Kidney Cancer

Background

Bone is a common target of metastasis in kidney cancer, and accurately predicting the risk of bone metastases (BMs) facilitates risk stratification and precision medicine in kidney cancer.

Methods

Patients diagnosed with kidney cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database to comprise the training group from 2010 to 2017, and the validation group was drawn from our academic medical center. Univariate and multivariate logistic regression analyses explored the statistical relationships between the included variables and BM. Statistically significant risk factors were applied to develop a nomogram. Calibration plots, receiver operating characteristic (ROC) curves, probability density functions (PDF), and clinical utility curves (CUC) were used to verify the predictive performance. Kaplan-Meier (KM) curves demonstrated survival differences between two subgroups of kidney cancer with and without BMs. A convenient web calculator was provided for users via “shiny” package.

Results

A total of 43,503 patients were recruited in this study, of which 42,650 were training group cases and 853 validation group cases. The variables included in the nomogram were sex, pathological grade, T-stage, N-stage, sequence number, brain metastases, liver metastasis, pulmonary metastasis, histological type, primary site, and laterality. The calibration plots confirmed good agreement between the prediction model and the actual results. The area under the curve (AUC) values in the training and validation groups were 0.952 (95% CI, 0.950–0.954) and 0.836 (95% CI, 0.809–0.860), respectively. Based on CUC, we recommend a threshold probability of 5% to guide the diagnosis of BMs.

Conclusions

The comprehensive predictive tool consisting of nomogram and web calculator contributes to risk stratification which helped clinicians identify high-risk cases and provide personalized treatment options.

Downregulated microRNA-149-3p triggers malignant development and predicts worse prognosis in oral squamous cell carcinoma

OBJECTIVE

Accumulating evidence reveals that aberrant expression of microRNAs contributes to the tumorigenesis and development of diverse human cancers. In the current study, we aimed to evaluate the functional role and prognostic value of miR-149-3p in oral squamous cell carcinoma (OSCC).

METHODS

Real-time polymerase chain reaction (PCR) analysis was performed to detect the expression of miR-149-3p in 70 OSCC patients (64.10 ± 11.97 years; 31 males and 39 females). The prognostic ability of miR-149-3p in OSCC patients was assessed by Kaplan-Meier survival analysis. Transwell assays and cell adhesion assays were used to investigate the impact of miR-149-3p on cell migration and invasion. The regulation of MMP2 expression by miR-149-3p was determined by real-time PCR, western blotting and dual luciferase reporter assay.

RESULTS

Our results revealed a lower level of miR-149-3p in OSCC tissues than in adjacent normal tissues. Downregulation of miR-149-3p was correlated with malignant development and poor outcomes in patients with OSCC. MiR-149-3p repressed the migratory and invasive abilities of OSCC cells. We confirmed that miR-149-3p targeted the 3'-untranslated region of MMP2 mRNA to suppress MMP2 expression. Moreover, the miR-149-3p-mediated decrease in metastasis was reversed by overexpression of MMP2 in OSCC cells.

CONCLUSION

Our findings provide an important molecular mechanism by which miR-149-3p inhibits OSCC cell migration and invasion via negative regulation of MMP2 and implicate miR-149-3p as a prospective biomarker and therapeutic target for OSCC.

Circular RNAs in renal cell carcinoma: Functions in tumorigenesis and diagnostic and prognostic potentials

Circular RNAs (circRNAs) are non-coding RNAs with closed ends which makes them resistant to degrading enzyme RNAse R. These RNA molecules show cell, tissue or organ specific expression. Regulatory functions have been reported for a number of circRNAs. Particularly, they have been found to affect cell cycle and control cell proliferation. CircRNAs are involved in physiological processes like natural organ development. Their dysregulation in high-throughput technologies have been shown in a growing number of diseases especially many types of cancers such as renal cell carcinoma (RCC). Differentially expressed circRNAs in RCC tissues compared to normal tissues may affect carcinogenesis process. Overexpressed circRNAs promote tumorigenic functions of RCC cell lines while down-regulated transcripts repress them. Both dysregulated circRNAs are correlated with clinicopathological features, prognosis and survival in RCC patients which along with their acceptable diagnostic values suggest them as potential biomarkers in diagnosis or prediction of prognosis of RCC patients. In this review, we have assessed tumorigenic or tumor-suppressing effects of circRNAs and also their diagnostic and prognostic potentials in RCC.

Interaction between Non-Coding RNAs and Androgen Receptor with an Especial Focus on Prostate Cancer

The androgen receptor (AR) is a member of the nuclear receptor superfamily and has three functional domains, namely the N-terminal, DNA binding, and C-terminal domain. The N-terminal domain harbors potent transactivation functions, whereas the C-terminal domain binds to androgens and antiandrogens used to treat prostate cancer. AR has genomic activity being DNA binding-dependent or through interaction with other DNA-bound transcription factors, as well as a number of non-genomic, non-canonical functions, such as the activation of the ERK, AKT, and MAPK pathways. A bulk of evidence indicates that non-coding RNAs have functional interactions with AR. This type of interaction is implicated in the pathogenesis of human malignancies, particularly prostate cancer. In the current review, we summarize the available data on the role of microRNAs, long non-coding RNAs, and circular RNAs on the expression of AR and modulation of AR signaling, as well as the effects of AR on their expression. Recognition of the complicated interaction between non-coding RNAs and AR has practical importance in the design of novel treatment options, as well as modulation of response to conventional therapeutics.

Lipid raft-disrupting miltefosine preferentially induces the death of colorectal cancer stem-like cells

BACKGROUND

Lipid rafts (LRs), cholesterol-enriched microdomains on cell membranes, are increasingly viewed as signalling platforms governing critical facets of cancer progression. The phenotype of cancer stem-like cells (CSCs) presents significant hurdles for successful cancer treatment, and the expression of several CSC markers is associated with LR integrity. However, LR implications in CSCs remain unclear.

METHODS

This study evaluated the biological and molecular functions of LRs in colorectal cancer (CRC) by using an LR-disrupting alkylphospholipid (APL) drug, miltefosine. The mechanistic role of miltefosine in CSC inhibition was examined through normal or tumour intestinal mouse organoid, human CRC cell, CRC xenograft and miltefosine treatment gene expression profile analyses.

RESULTS

Miltefosine suppresses CSC populations and their self-renewal activities in CRC cells, a CSC-targeting effect leading to irreversible disruption of tumour-initiating potential in vivo. Mechanistically, miltefosine reduced the expression of a set of genes, leading to stem cell death. Among them, miltefosine transcriptionally inhibited checkpoint kinase 1 (CHEK1), indicating that LR integrity is essential for CHEK1 expression regulation. In isolated CD44high CSCs, we found that CSCs exhibited stronger therapy resistance than non-CSC counterparts by preventing cell death through CHEK1-mediated cell cycle checkpoints. However, inhibition of the LR/CHEK1 axis by miltefosine released cell cycle checkpoints, forcing CSCs to enter inappropriate mitosis with accumulated DNA damage and resulting in catastrophic cell death.

CONCLUSION

Our findings underscore the therapeutic potential of LR-targeting APLs for CRC treatment that overcomes the therapy-resistant phenotype of CSCs, highlighting the importance of the LR/CHEK1 axis as a novel mechanism of APLs.