CSChighE-cadherinlow immunohistochemistry panel predicts poor prognosis in oral squamous cell carcinoma.

Identifying marker combinations for robust prognostic validation in primary tumour compartments remains challenging. We aimed to assess the prognostic significance of CSC markers (ALDH1, CD44, p75NTR, BMI-1) and E-cadherin biomarkers in OSCC. We analysed 94 primary OSCC and 67 metastatic lymph node samples, including central and invasive tumour fronts (ITF), along with clinicopathological data. We observed an increase in ALDH1+/CD44+/BMI-1- tumour cells in metastatic lesions compared to primary tumours. Multivariate analysis highlighted that elevated p75NTR levels (at ITF) and reduced E-cadherin expression (at the tumour centre) independently predicted metastasis, whilst ALDH1high exhibited independent predictive lower survival at the ITF, surpassing the efficacy of traditional tumour staging. Then, specifically at the ITF, profiles characterized by CSChighE-cadherinlow (ALDH1highp75NTRhighE-cadherinlow) and CSCintermediateE-cadherinlow (ALDH1 or p75NTRhighE-cadherinlow) were significantly associated with worsened overall survival and increased likelihood of metastasis in OSCC patients. In summary, our study revealed diverse tumour cell profiles in OSCC tissues, with varying CSC and E-cadherin marker patterns across primary tumours and metastatic sites. Given the pivotal role of reduced survival rates as an indicator of unfavourable prognosis, the immunohistochemistry profile identified as CSChighE-cadherinlow at the ITF of primary tumours, emerges as a preferred prognostic marker closely linked to adverse outcomes in OSCC.

Clinical significance of PNO1 as a novel biomarker and therapeutic target of hepatocellular carcinoma.

The RNA-binding protein PNO1 plays an essential role in ribosome biogenesis. Recent studies have shown that it is involved in tumorigenesis; however, its role in hepatocellular carcinoma (HCC) is not well understood. The purpose of this study was to examine whether PNO1 can be used as a biomarker of HCC and also examine the therapeutic potential of PNO1 knockout for the treatment of HCC. PNO1 expression was upregulated in HCC and associated with poor prognosis. PNO1 expression was positively associated with tumour stage, lymph node metastasis and poor survival. PNO1 expression was significantly higher in HCC compared to that in fibrolamellar carcinoma or normal tissues. Furthermore, HCC tissues with mutant Tp53 expressed higher PNO1 than those with wild-type Tp53. PNO1 knockout suppressed cell viability, colony formation and EMT of HCC cells. Since activation of Notch signalling pathway promotes HCC, we measured the effects of PNO1 knockout on the components of Notch pathway and its targets. PNO1 knockout suppressed Notch signalling by modulating the expression of Notch ligands and their receptors, and downstream targets. PNO1 knockout also inhibited genes involved in surface adhesion, cell cycle, inflammation and chemotaxis. PNO1 knockout also inhibited colony and spheroid formation, cell migration and invasion, and markers of stem cells, pluripotency and EMT in CSCs. Overall, our data suggest that PNO1 can be used as a diagnostic and prognostic biomarker of HCC, and knockout of PNO1 by CRISPR/Cas9 can be beneficial for the management of HCC by targeting CSCs.

The Effect of Intratumor Heterogeneity in Pancreatic Ductal Adenocarcinoma Progression and Treatment.

BACKGROUND AND OBJECTIVES: Pancreatic cancer is one of the most lethal malignancies. Even though many substantial improvements in the survival rates for other major cancer forms were made, pancreatic cancer survival rates have remained relatively unchanged since the 1960s. Even more, no standard classification system for pancreatic cancer is based on cellular biomarkers. This review will discuss and provide updates about the role of stem cells in the progression of PC, the genetic changes associated with it, and the promising biomarkers for diagnosis. MATERIALS AND METHODS: The search process used PubMed, Cochrane Library, and Scopus databases to identify the relevant and related articles. Articles had to be published in English to be considered. RESULTS: The increasing number of studies in recent years has revealed that the diversity of cancer-associated fibroblasts is far greater than previously acknowledged, which highlights the need for further research to better understand the various cancer-associated fibroblast subpopulations. Despite the huge diversity in pancreatic cancer, some common features can be noted to be shared among patients. Mutations involving CDKN2, P53, and K-RAS can be seen in a big number of patients, for example. Similarly, some patterns of genes and biomarkers expression and the level of their expression can help in predicting cancer behavior such as metastasis and drug resistance. The current trend in cancer research, especially with the advancement in technology, is to sequence everything in hopes of finding disease-related mutations. CONCLUSION: Optimizing pancreatic cancer treatment requires clear classification, understanding CAF roles, and exploring stroma reshaping approaches.

Pervasive structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programs.

Glioblastoma multiforme (GBM) encompasses brain malignancies marked by phenotypic and transcriptional heterogeneity thought to render these tumors aggressive, resistant to therapy, and inevitably recurrent. However, little is known about how the spatial organization of GBM genomes underlies this heterogeneity and its effects. Here, we compile a cohort of 28 patient-derived glioblastoma stem cell-like lines (GSCs) known to reflect the properties of their tumor-of-origin; six of these were primary-relapse tumor pairs from the same patient. We generate and analyze 5 kbp-resolution chromosome conformation capture (Hi-C) data from all GSCs to systematically map thousands of standalone and complex structural variants (SVs) and the multitude of neoloops arising as a result. By combining Hi-C, histone modification, and gene expression data with chromatin folding simulations, we explain how the pervasive, uneven, and idiosyncratic occurrence of neoloops sustains tumor-specific transcriptional programs via the formation of new enhancer-promoter contacts. We also show how even moderately recurrent neoloops can relate to patient-specific vulnerabilities. Together, our data provide a resource for dissecting GBM biology and heterogeneity, as well as for informing therapeutic approaches.

Circ-0075305 hinders gastric cancer stem cells by indirectly disrupting TCF4-ß-catenin complex and downregulation of SOX9.

CircRNAs are covalently closed, single-stranded RNA that form continuous loops and play a crucial role in the initiation and progression of tumors. Cancer stem cells (CSCs) are indispensable for cancer development; however, the regulation of cancer stem cell-like properties in gastric cancer (GC) and its specific mechanism remain poorly understood. We elucidate the specific role of Circ-0075305 in GC stem cell properties. Circ-0075305 associated with chemotherapy resistance was identified by sequencing GC cells. Subsequent confirmation in both GC tissues and cell lines revealed that patients with high expression of Circ-0075305 had significantly better overall survival (OS) rates than those with low expression, particularly when treated with postoperative adjuvant chemotherapy for GC. In vitro and in vivo experiments confirmed that overexpression of Circ-0075305 can effectively reduce stem cell-like properties and enhance the sensitivity of GC cells to Oxaliplatin compared with the control group. Circ-0075305 promotes RPRD1A expression by acting as a sponge for corresponding miRNAs. The addition of LF3 (a ß-catenin/TCF4 interaction antagonist) confirmed that RPRD1A inhibited the formation of the TCF4-ß-catenin transcription complex through competitive to ß-catenin and suppressed the transcriptional activity of stem cell markers such as SOX9 via the Wnt/ß-catenin signaling pathway. This leads to the downregulation of stem cell-like property-related markers in GC. This study revealed the underlying mechanisms that regulate Circ-0075305 in GCSCs and suggests that its role in reducing ß-catenin signaling may serve as a potential therapeutic candidate.

NANOG controls testicular germ cell tumour stemness through regulation of MIR9-2.

BACKGROUND: Testicular germ cell tumours (TGCTs) represent a clinical challenge; they are most prevalent in young individuals and are triggered by molecular mechanisms that are not fully understood. The origin of TGCTs can be traced back to primordial germ cells that fail to mature during embryonic development. These cells express high levels of pluripotency factors, including the transcription factor NANOG which is highly expressed in TGCTs. Gain or amplification of the NANOG locus is common in advanced tumours, suggesting a key role for this master regulator of pluripotency in TGCT stemness and malignancy. METHODS: In this study, we analysed the expression of microRNAs (miRNAs) that are regulated by NANOG in TGCTs via integrated bioinformatic analyses of data from The Cancer Genome Atlas and NANOG chromatin immunoprecipitation in human embryonic stem cells. Through gain-of-function experiments, MIR9-2 was further investigated as a novel tumour suppressor regulated by NANOG. After transfection with MIR9-2 mimics, TGCT cells were analysed for cell proliferation, invasion, sensitivity to cisplatin, and gene expression signatures by RNA sequencing. RESULTS: For the first time, we identified 86 miRNAs regulated by NANOG in TGCTs. Among these, 37 miRNAs were differentially expressed in NANOG-high tumours, and they clustered TGCTs according to their subtypes. Binding of NANOG within 2 kb upstream of the MIR9-2 locus was associated with a negative regulation. Low expression of MIR9-2 was associated with tumour progression and MIR9-2-5p was found to play a role in the control of tumour stemness. A gain of function of MIR9-2-5p was associated with reduced proliferation, invasion, and sensitivity to cisplatin in both embryonal carcinoma and seminoma tumours. MIR9-2-5p expression in TGCT cells significantly reduced the expression of genes regulating pluripotency and cell division, consistent with its functional effect on reducing cancer stemness. CONCLUSIONS: This study provides new molecular insights into the role of NANOG as a key determinant of pluripotency in TGCTs through the regulation of MIR9-2-5p, a novel epigenetic modulator of cancer stemness. Our data also highlight the potential negative feedback mediated by MIR9-2-5p on NANOG expression, which could be exploited as a therapeutic strategy for the treatment of TGCTs.

METTL8 links mt-tRNA m3C modification to the HIF1α/RTK/Akt axis to sustain GBM stemness and tumorigenicity.

Epitranscriptomic RNA modifications are crucial for the maintenance of glioma stem cells (GSCs), the most malignant cells in glioblastoma (GBM). 3-methylcytosine (m3C) is a new epitranscriptomic mark on RNAs and METTL8 represents an m3C writer that is dysregulated in cancer. Although METTL8 has an established function in mitochondrial tRNA (mt-tRNA) m3C modification, alternative splicing of METTL8 can also generate isoforms that localize to the nucleolus where they may regulate R-loop formation. The molecular basis for METTL8 dysregulation in GBM, and which METTL8 isoform(s) may influence GBM cell fate and malignancy remain elusive. Here, we investigated the role of METTL8 in regulating GBM stemness and tumorigenicity. In GSC, METTL8 is exclusively localized to the mitochondrial matrix where it installs m3C on mt-tRNAThr/Ser(UCN) for mitochondrial translation and respiration. High expression of METTL8 in GBM is attributed to histone variant H2AZ-mediated chromatin accessibility of HIF1α and portends inferior glioma patient outcome. METTL8 depletion impairs the ability of GSC to self-renew and differentiate, thus retarding tumor growth in an intracranial GBM xenograft model. Interestingly, METTL8 depletion decreases protein levels of HIF1α, which serves as a transcription factor for several receptor tyrosine kinase (RTK) genes, in GSC. Accordingly, METTL8 loss inactivates the RTK/Akt axis leading to heightened sensitivity to Akt inhibitor treatment. These mechanistic findings, along with the intimate link between METTL8 levels and the HIF1α/RTK/Akt axis in glioma patients, guided us to propose a HIF1α/Akt inhibitor combination which potently compromises GSC proliferation/self-renewal in vitro. Thus, METTL8 represents a new GBM dependency that is therapeutically targetable.

Assessing the distribution of cancer stem cells in tumorspheres.

Cancer Stem Cells presumably drive tumor growth and resistance to conventional cancer treatments. From a previous computational model, we inferred that these cells are not uniformly distributed in the bulk of a tumorsphere. To confirm this result, we cultivated tumorspheres enriched in stem cells, and performed immunofluorescent detection of the stemness marker SOX2 using confocal microscopy. In this article, we present an image processing method that reconstructs the amount and location of the Cancer Stem Cells in the spheroids. Its advantage is the use of a statistical criterion to classify the cells in Stem and Differentiated, instead of setting an arbitrary threshold. Moreover, the analysis of the experimental images presented in this work agrees with the results from our computational models, thus enforcing the notion that the distribution of Cancer Stem Cells in a tumorsphere is non-homogeneous. Additionally, the method presented here provides a useful tool for analyzing any image in which different kinds of cells are stained with different markers.

Epithelial-mesenchymal transition-related signaling pathways in gastric Cancer cells distinctively respond to long-term experimental ketosis.

BACKGROUND: The interrelationship between cellular metabolism and the epithelial-to-mesenchymal transition (EMT) process has made it an interesting topic to investigate the adjuvant effect of therapeutic diets in the treatment of cancers. However, the findings are controversial. In this study, the effects of glucose limitation along and with the addition of beta-hydroxybutyrate (bHB) were examined on the expression of specific genes and proteins of EMT, Wnt, Hedgehog, and Hippo signaling pathways, and also on cellular behavior of gastric cancer stem-like (MKN-45) and non-stem-like (KATO III) cells. METHODS AND RESULTS: The expression levels of chosen genes and proteins studied in cancer cells gradually adopted a low-glucose condition of one-fourth, along and with the addition of bHB, and compared to the unconditioned control cells. The long-term switching of the metabolic fuels successfully altered the expression profiles and behaviors of both gastric cancer cells. However, the results for some changes were the opposite. Glucose limitation along and with the addition of bHB reduced the CD44+ population in MKN-45 cells. In KATO III cells, glucose restriction increased the CD44+ population. Glucose deprivation alleviated EMT-related signaling pathways in MKN-45 cells but stimulated EMT in KATO III cells. Interestingly, bHB enrichment reduced the beneficial effect of glucose starvation in MKN-45 cells, but also alleviated the adverse effects of glucose restriction in KATO III cells. CONCLUSIONS: The findings of this research clearly showed that some controversial results in clinical trials for ketogenic diet in cancer patients stemmed from the different signaling responses of various cells to the metabolic changes in a heterogeneous cancer mass.

Glioblastoma stem cells deliver ABCB4 transcribed by ATF3 via exosomes conferring glioblastoma resistance to temozolomide.

Glioblastoma stem cells (GSCs) play a key role in glioblastoma (GBM) resistance to temozolomide (TMZ) chemotherapy. With the increase in research on the tumour microenvironment, exosomes secreted by GSCs have become a new focus in GBM research. However, the molecular mechanism by which GSCs affect drug resistance in GBM cells via exosomes remains unclear. Using bioinformatics analysis, we identified the specific expression of ABCB4 in GSCs. Subsequently, we established GSC cell lines and used ultracentrifugation to extract secreted exosomes. We conducted in vitro and in vivo investigations to validate the promoting effect of ABCB4 and ABCB4-containing exosomes on TMZ resistance. Finally, to identify the transcription factors regulating the transcription of ABCB4, we performed luciferase assays and chromatin immunoprecipitation-quantitative PCR. Our results indicated that ABCB4 is highly expressed in GSCs. Moreover, high expression of ABCB4 promoted the resistance of GSCs to TMZ. Our study found that GSCs can also transmit their highly expressed ABCB4 to differentiated glioma cells (DGCs) through exosomes, leading to high expression of ABCB4 in these cells and promoting their resistance to TMZ. Mechanistic studies have shown that the overexpression of ABCB4 in GSCs is mediated by the transcription factor ATF3. In conclusion, our results indicate that GSCs can confer resistance to TMZ in GBM by transmitting ABCB4, which is transcribed by ATF3, through exosomes. This mechanism may lead to drug resistance and recurrence of GBM. These findings contribute to a deeper understanding of the mechanisms underlying drug resistance in GBM and provide novel insights into its treatment.

Hallmarks of cancer stemness.

Cancer stemness is recognized as a key component of tumor development. Previously coined "cancer stem cells" (CSCs) and believed to be a rare population with rigid hierarchical organization, there is good evidence to suggest that these cells exhibit a plastic cellular state influenced by dynamic CSC-niche interplay. This revelation underscores the need to reevaluate the hallmarks of cancer stemness. Herein, we summarize the techniques used to identify and characterize the state of these cells and discuss their defining and emerging hallmarks, along with their enabling and associated features. We also highlight potential future directions in this field of research.

AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data.

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties and represent a potentially effective therapeutic target toward long-term remission by means of differentiation induction. By leveraging an artificial intelligence approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human-induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the Library of Integrated Network-based Cellular Signatures (LINCS) database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of five out of six tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

Impact of the thyroid hormone T3 and its nuclear receptor TRα1 on colon cancer stem cell phenotypes and response to chemotherapies.

Colorectal cancers (CRCs) are highly heterogeneous and show a hierarchical organization, with cancer stem cells (CSCs) responsible for tumor development, maintenance, and drug resistance. Our previous studies showed the importance of thyroid hormone-dependent signaling on intestinal tumor development and progression through action on stem cells. These results have a translational value, given that the thyroid hormone nuclear receptor TRα1 is upregulated in human CRCs, including in the molecular subtypes associated with CSC features. We used an established spheroid model generated from the human colon adenocarcinoma cell line Caco2 to study the effects of T3 and TRα1 on spheroid formation, growth, and response to conventional chemotherapies. Our results show that T3 treatment and/or increased TRα1 expression in spheroids impaired the response to FOLFIRI and conferred a survival advantage. This was achieved by stimulating drug detoxification pathways and increasing ALDH1A1-expressing cells, including CSCs, within spheroids. These results suggest that clinical evaluation of the thyroid axis and assessing TRα1 levels in CRCs could help to select optimal therapeutic regimens for patients with CRC. Proposed mechanism of action of T3/TRα1 in colon cancer spheroids. In the control condition, TRα1 participates in maintaining homeostatic cell conditions. The presence of T3 in the culture medium activates TRα1 action on target genes, including the drug efflux pumps ABCG2 and ABCB1. In the case of chemotherapy FOLFIRI, the increased expression of ABC transcripts and proteins induced by T3 treatment is responsible for the augmented efflux of 5-FU and Irinotecan from the cancer cells. Taken together, these mechanisms contribute to the decreased efficacy of the chemotherapy and allow cells to escape the treatment. Created with BioRender.com .

Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma.

BACKGROUND: Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP. METHODS: RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors. RESULTS: In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP. CONCLUSIONS: We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments.

BACKGROUND: Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. METHODS: Utilizing RNA sequencing data and corresponding clinical information from the TCGA database, and employing Weighted Gene Co-expression Network Analysis (WGCNA) on TNBC mRNAsi sourced from an online database, stemness-related genes (SRGs) and SRlncRNAs were identified. A prognostic model was developed using univariate Cox and LASSO-Cox analysis based on SRlncRNAs. The performance of the model was evaluated using Kaplan-Meier analysis, ROC curves, and ROC-AUC. Additionally, the study delved into the underlying signaling pathways and immune status associated with the divergent prognoses of TNBC patients. RESULTS: The research identified a signature of six SRlncRNAs (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, and MIR193BHG) for TNBC. Risk scores derived from this signature were found to correlate with the abundance of plasma cells. Furthermore, the nominated chemotherapy drugs for TNBC exhibited considerable variability between different risk score groups. RT-qPCR validation confirmed abnormal expression patterns of these SRlncRNAs in TNBC stem cells, affirming the potential of the SRlncRNAs signature as a prognostic biomarker. CONCLUSION: The identified signature not only demonstrates predictive power in terms of patient outcomes but also provides insights into the underlying biology, signaling pathways, and immune status associated with TNBC prognosis. The findings suggest the possibility of guiding personalized treatments, including immune checkpoint gene therapy and chemotherapy strategies, based on the risk scores derived from the SRlncRNA signature. Overall, this research contributes valuable knowledge towards advancing precision medicine in the context of TNBC.

WNT5B drives osteosarcoma stemness, chemoresistance and metastasis.

BACKGROUND: Treatment for osteosarcoma, a paediatric bone cancer with no therapeutic advances in over three decades, is limited by a lack of targeted therapies. Osteosarcoma frequently metastasises to the lungs, and only 20% of patients survive 5 years after the diagnosis of metastatic disease. We found that WNT5B is the most abundant WNT expressed in osteosarcoma tumours and its expression correlates with metastasis, histologic subtype and reduced survival. METHODS: Using tumor-spheroids to model cancer stem-like cells, we performed qPCR, immunoblotting, and immunofluorescence to monitor changes in gene and protein expression. Additionally, we measured sphere size, migration and forming efficiency to monitor phenotypic changes. Therefore, we characterised WNT5B's relevance to cancer stem-like cells, metastasis, and chemoresistance and evaluated its potential as a therapeutic target. RESULTS: In osteosarcoma cell lines and patient-derived spheres, WNT5B is enriched in stem cells and induces the expression of the stemness gene SOX2. WNT5B promotes sphere size, sphere-forming efficiency, and cell proliferation, migration, and chemoresistance to methotrexate (but not cisplatin or doxorubicin) in spheres formed from conventional cell lines and patient-derived xenografts. In vivo, WNT5B increased osteosarcoma lung and liver metastasis and inhibited the glycosaminoglycan hyaluronic acid via upregulation of hyaluronidase 1 (HYAL1), leading to changes in the tumour microenvironment. Further, we identified that WNT5B mRNA and protein correlate with the receptor ROR1 in primary tumours. Targeting WNT5B through inhibition of WNT/ROR1 signalling with an antibody to ROR1 reduced stemness properties, including chemoresistance, sphere size and SOX2 expression. CONCLUSIONS: Together, these data define WNT5B's role in driving osteosarcoma cancer stem cell expansion and methotrexate resistance and provide evidence that the WNT5B pathway is a promising candidate for treating osteosarcoma patients. KEY POINTS: WNT5B expression is high in osteosarcoma stem cells leading to increased stem cell proliferation and migration through SOX2. WNT5B expression in stem cells increases rates of osteosarcoma metastasis to the lungs and liver in vivo. The hyaluronic acid degradation enzyme HYAL1 is regulated by WNT5B in osteosarcoma contributing to metastasis. Inhibition of WNT5B with a ROR1 antibody decreases osteosarcoma stemness.

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.

Objective: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy. Methods: We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the "one-class logistic regression (OCLR)" algorithm to obtain the mRNAsi of patients with HCC. We performed "unsupervised consensus clustering" to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient's prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC. Results: We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient's prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines. Conclusion: The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

The Impact of Cancer Stem Cells in Colorectal Cancer.

Despite incessant research, colorectal cancer (CRC) is still one of the most common causes of fatality in both men and women worldwide. Over time, advancements in medical treatments have notably enhanced the survival rates of patients with colorectal cancer. Managing metastatic CRC involves a complex tradeoff between the potential benefits and adverse effects of treatment, considering factors like disease progression, treatment toxicity, drug resistance, and the overall impact on the patient's quality of life. An increasing body of evidence highlights the significance of the cancer stem cell (CSC) concept, proposing that CSCs occupy a central role in triggering cancer. CSCs have been a focal point of extensive research in a variety of cancer types, including CRC. Colorectal cancer stem cells (CCSCs) play a crucial role in tumor initiation, metastasis, and therapy resistance, making them potential treatment targets. Various methods exist for isolating CCSCs, and understanding the mechanisms of drug resistance associated with them is crucial. This paper offers an overview of the current body of research pertaining to the comprehension of CSCs in colorectal cancer.

A novel prognostic signature based on cancer stemness and metabolism-related genes for cervical squamous cell carcinoma and endocervical adenocarcinoma.

BACKGROUND: CESC is the second most commonly diagnosed gynecological malignancy. Given the pivotal involvement of metabolism-related genes (MRGs) in the etiology of multiple tumors, our investigation aims to devise a prognostic risk signature rooted in cancer stemness and metabolism. METHODS: The stemness index based on mRNA expression (mRNAsi) of samples from the TCGA dataset was computed using the One-class logistic regression (OCLR) algorithm. Furthermore, potential metabolism-related genes related to mRNAsi were identified through weighted gene co-expression network analysis (WGCNA). We construct a stemness-related metabolic gene signature through shrinkage estimation and univariate analysis, thereby calculating the corresponding risk scores. Moreover, we selected corresponding DEGs between groups with high- and low-risk score and conducted routine bioinformatic analyses. Furthermore, we validated the expression of four hub genes at the protein level through immunohistochemistry (IHC) in samples obtained from our patient cohort. RESULTS: According to the findings, it was found that six genes-AKR1B10, GNA15, ALDH1B1, PLOD2, LPCAT1, and GPX8- were differentially expressed in both TCGA-CSEC and GEO datasets among 23 differentially expressed metabolism-related genes (DEMRGs). mRNAsi exhibited a notable association with the extent of key oncogene mutation. The results showed that the AUC values for forecasting survival at 1, 3, and 5 years are 0.715, 0.689, and 0.748, individually. We observed a notable association between the risk score and different immune cell populations, along with enrichment in crucial signaling pathways in CESC. Four genes differentially expressed between different risk score groups were validated by IHC to be highly expressed in the CESC samples at the protein level. CONCLUSION: The current investigation indicated that a 3-gene signature based on stemness-related metabolic and 4 hub genes with differential expression between high and low-risk score subgroups may serve as valuable prognostic markers and potential therapeutic targets in CESC.