StemChecker: a web-based tool to discover and explore stemness signatures in gene sets

Integrated analysis of ferroptosis and stemness based on single-cell and bulk RNA-sequencing data provide insights into the prognosis and treatment of esophageal carcinoma

BACKGROUND

Cancer stem cells (CSCs) play a significant role in the recurrence and drug resistance of esophageal carcinoma (ESCA). Ferroptosis is a promising anticancer therapeutic strategy that effectively targets CSCs exhibiting high tumorigenicity and treatment resistance. However, there is a lack of research on the combined role of ferroptosis-related genes (FRGs) and stemness signature in the prognosis of ESCA.

METHODS

The cellular compositions were characterized using single-cell RNA sequencing (scRNA-seq) data from 18 untreated ESCA samples. 50 ferroptosis-related stemness genes (FRSGs) were identified by integrating FRGs with stemness-related genes (SRGs), and then the cells were grouped by AUCell analysis. Next, functional enrichment, intercellular communication, and trajectory analyses were performed to characterize the different groups of cells. Subsequently, the stem-ferr-index was calculated using machine learning algorithms based on the expression profiles of the identified risk genes. Additionally, therapeutic drugs were predicted by analyzing the GDSC2 database. Finally, the expression and functional roles of the identified marker genes were validated through in vitro experiments.

RESULTS

The analysis of scRNA-seq data demonstrates the diversity and cellular heterogeneity of ESCA. Then, we identified 50 FRSGs and classified cells into high or low ferroptosis score stemness cells accordingly. Functional enrichment analysis conducted on the differentially up-regulated genes between these groups revealed predominant enrichment in pathways associated with intercellular communication and cell differentiation. Subsequently, we identified 9 risk genes and developed a prognostic signature, termed stem_ferr_index, based on these identified risk genes. We found that the stem-ferr-index was correlated with the clinical characteristics of patients, and patients with high stem-ferr-index had poor prognosis. Furthermore, we identified four drugs (Navitoclax, Foretinib, Axitinib, and Talazoparib) with potential efficacy targeting patients with a high stem_ferr_index. Additionally, we delineated two marker genes (STMN1 and SLC2A1). Particularly noteworthy, SLC2A1 exhibited elevated expression levels in ESCA tissues and cells. We provided evidence suggesting that SLC2A1 could influence the migration, invasion, and stemness of ESCA cells, and it was associated with sensitivity to Foretinib.

CONCLUSION

This study constructed a novel ferroptosis-related stemness signature, identified two marker genes for ESCA, and provided valuable insights for developing more effective therapeutic targets targeting ESCA CSCs in the future.

ncStem: a comprehensive resource of curated and predicted ncRNAs in cancer stemness

Cancer stemness plays an important role in cancer initiation and progression, and is the major cause of tumor invasion, metastasis, recurrence, and poor prognosis. Non-coding RNAs (ncRNAs) are a class of RNA transcripts that generally cannot encode proteins and have been demonstrated to play a critical role in regulating cancer stemness. Here, we developed the ncStem database to record manually curated and predicted ncRNAs associated with cancer stemness. In total, ncStem contains 645 experimentally verified entries, including 159 long non-coding RNAs (lncRNAs), 254 microRNAs (miRNAs), 39 circular RNAs (circRNAs), and 5 other ncRNAs. The detailed information of each entry includes the ncRNA name, ncRNA identifier, disease, reference, expression direction, tissue, species, and so on. In addition, ncStem also provides computationally predicted cancer stemness-associated ncRNAs for 33 TCGA cancers, which were prioritized using the random walk with restart (RWR) algorithm based on regulatory and co-expression networks. The total predicted cancer stemness-associated ncRNAs included 11 132 lncRNAs and 972 miRNAs. Moreover, ncStem provides tools for functional enrichment analysis, survival analysis, and cell location interrogation for cancer stemness-associated ncRNAs. In summary, ncStem provides a platform to retrieve cancer stemness-associated ncRNAs, which may facilitate research on cancer stemness and offer potential targets for cancer treatment. Database URL: http://www.nidmarker-db.cn/ncStem/index.html.

Development of stemness-related signature to optimize prognosis prediction and identify XMD8-85 as a novel therapeutic compound for glioma

Glioma is a highly invasive and aggressive type of brain cancer with poor treatment response. Stemness-related transcription factors form a regulatory network that sustains the malignant phenotype of gliomas. We conducted an integrated analysis of stemness-related transcription factors using The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, established the characteristics of stemness-related transcription factors, including Octamer-Binding Protein 4 (OCT4), Meis Homeobox 1 (MEIS1), E2F Transcription Factor 1 (E2F1), Transcription Factor CP2 Like 1 (TFCP2L1), and RUNX Family Transcription Factor 1 (RUNX1). The characteristic of stemness-related transcription factors was identified as an independent prognostic factor for glioma patients. Patients in the high-risk group have a worse prognosis than those in the low-risk group. The glioma microenvironment in the high-risk group exhibited a more active immune status. Single-cell level analysis revealed that stem cell-like cells exhibited stronger intercellular communication than glioma cells. Meanwhile, patients in different risk stratification exhibited varying sensitivities to immunotherapy and small molecule drug therapy. XMD8-85 was more effective in the high-risk group, and its antitumor effects were validated both in vivo and in vitro. Our results indicate that this prognostic feature will assist clinicians in predicting the prognosis of glioma patients, guiding immunotherapy and personalized treatment, as well as the potential clinical application of XMD8-85 in glioma treatment, and helping to develop effective treatment strategies.

Generation of novel lipid metabolism-based signatures to predict prognosis and immunotherapy response for colorectal adenocarcinoma

Lipid metabolism reprogramming involves in epithelial-mesenchymal transition (EMT), cancer stemness and immune checkpoints (ICs), which influence the metastasis of cancer. This study aimed to generate lipid metabolism-based signatures to predict prognosis, immunotherapy and chemotherapy response for colorectal adenocarcinoma (COAD). Transcriptome data and clinical information of COAD patients were collected from the cancer genome atlas (TCGA) database. The expression of EMT-, stem cell-, and IC-related genes were assessed between COAD and control samples. Modules and genes correlated EMT, ICs and stemness signatures were identified through weighted gene co-expression network analysis (WGCNA). Prognostic signatures were generated and then the distribution of risk genes was evaluated using single-cell RNA sequencing (scRNA-seq) data from GSE132465 dataset. COAD patients exhibited increased EMT score and stemness along with decreased ICs. Next, 12 hub genes (PIK3CG, ALOX5AP, PIK3R5, TNFAIP8L2, DPEP2, PIK3CD, PIK3R6, GGT5, ELOVL4, PTGIS, CYP7B1 and PRKD1) were found within green and yellow modules correlated with EMT, stemness and ICs. Lipid metabolism-based prognostic signatures were generated based on PIK3CG, GGT5 and PTGIS. Patients with high-risk group had poor prognosis, elevated ESTIMATEScore and StromalScore, 100% mutation rate and higher TIDE score. Samples in low-risk group had more immunogenicity on ICIs. Notably, PIK3CG was expressed in B cells, while GGT5 and PTGIS were expressed in stromal cells. This study generates lipid metabolism-based signatures correlated with EMT, stemness and ICs for predicting prognosis of COAD, and provides potential therapeutic targets for immunotherapy in COAD.

Combined inhibition of EZH2 and CDK4/6 perturbs endoplasmic reticulum-mitochondrial homeostasis and increases antitumor activity against glioblastoma

He, we show that combined use of the EZH2 inhibitor GSK126 and the CDK4/6 inhibitor abemaciclib synergistically enhances antitumoral effects in preclinical GBM models. Dual blockade led to HIF1α upregulation and CalR translocation, accompanied by massive impairment of mitochondrial function. Basal oxygen consumption rate, ATP synthesis, and maximal mitochondrial respiration decreased, confirming disrupted endoplasmic reticulum-mitochondrial homeostasis. This was paralleled by mitochondrial depolarization and upregulation of the UPR sensors PERK, ATF6α, and IRE1α. Notably, dual EZH2/CDK4/6 blockade also reduced 3D-spheroid invasion, partially inhibited tumor growth in ovo, and led to impaired viability of patient-derived organoids. Mechanistically, this was due to transcriptional changes in genes involved in mitotic aberrations/spindle assembly (Rb, PLK1, RRM2, PRC1, CENPF, TPX2), histone modification (HIST1H1B, HIST1H3G), DNA damage/replication stress events (TOP2A, ATF4), immuno-oncology (DEPDC1), EMT-counterregulation (PCDH1) and a shift in the stemness profile towards a more differentiated state. We propose a dual EZH2/CDK4/6 blockade for further investigation.

The potential of cancer stem cells for personalized risk assessment and therapeutic intervention in individuals with intrahepatic cholangiocarcinoma

BACKGROUND

Accumulating evidence suggests that intrahepatic cholangiocarcinoma (ICC) is a stem cell-based disease, but information on the biology of cancer stem cells (CSC) in ICC is very limited.

METHODS

ICC RNA-seq cohorts from three different public databases were integrated and the protein-coding genes were divided into different modules using "WGCNA" to screen the most relevant modules with CSC scores. Least Absolute Shrinkage and Selection Operator (LASSO) regression were introduced to construct prognostic classification models. In addition, the extent of immune cell infiltration in patients in different risk groups was assessed based on the ESTIMATE, CIBERSORT, MCP-Counter, and single sample gene set enrichment analysis (ssGSEA) algorithms. Finally, the correlation between different risk scores and common drugs was analyzed by pRRophetic package and Spearman method.

RESULTS

In the present study, we found that a high CSC score was associated with a poorer prognosis in patients with ICC. The yellow module obtained by WGCNA was significantly positively correlated with the CSCs score, in which 8 genes were served to build a prognostic classification model, and the obtained risk score was negatively correlated with CSCs score and prognosis. The low-risk score was more suitable for immunotherapy, and the high-risk score was more suitable for treatment with 11 antitumor drugs.

CONCLUSION

This study revealed the regulatory role of CSC-mediated EMT, angiogenesis, and immunomodulatory biological processes in ICC, and applied a prognostic classification model to highlight the great potential of CSC for personalized risk assessment, chemotherapy, and immunotherapy intervention in ICC individuals.

The Epigenetic Modifiers HDAC2 and HDAC7 Inversely Associate with Cancer Stemness and Immunity in Solid Tumors

Dysregulation of histone deacetylases (HDACs) is closely associated with cancer development and progression. Here, we comprehensively analyzed the association between all HDAC family members and several clinicopathological and molecular traits of solid tumors across 22 distinct tumor types, focusing primarily on cancer stemness and immunity. To this end, we used publicly available TCGA data and several bioinformatic tools (i.e., GEPIA2, TISIDB, GSCA, Enrichr, GSEA). Our analyses revealed that class I and class II HDAC proteins are associated with distinct cancer phenotypes. The transcriptomic profiling indicated that class I HDAC members, including HDAC2, are positively associated with cancer stemness, while class IIA HDAC proteins, represented by HDAC7, show a negative correlation to cancer stem cell-like phenotypes in solid tumors. In contrast to tumors with high amounts of HDAC7 proteins, the transcriptome signatures of HDAC2-overexpressing cancers are significantly enriched with biological terms previously determined as stemness-associated genes. Moreover, high HDAC2-expressing tumors are depleted with immune-related processes, and HDAC2 expression correlates with tumor immunosuppressive microenvironments. On the contrary, HDAC7 upregulation is significantly associated with enhanced immune responses, followed by enriched infiltration of CD4+ and CD8+ T cells. This is the first comprehensive report demonstrating robust and versatile associations between specific HDAC family members, cancer dedifferentiation, and anti-tumor immune statuses in solid tumors.

Exploring the potential of predicted miRNAs on the genes involved in the expansion of hematopoietic stem cells

A major challenge in therapeutic approaches applying hematopoietic stem cells (HSCs) is the cell quantity. The primary objective of this study was to predict the miRNAs and anti-miRNAs using bioinformatics tools and investigate their effects on the expression levels of key genes predicted in the improvement of proliferation, and the inhibition of differentiation in HSCs isolated from Human umbilical cord blood (HUCB). A network including genes related to the differentiation and proliferation stages of HSCs was constructed by enriching data of text (PubMed) and StemChecker server with KEGG signaling pathways, and was improved using GEO datasets. Bioinformatics tools predicted a profile from miRNAs containing miR-20a-5p, miR-423-5p, and chimeric anti-miRNA constructed from 5'-miR-340/3'-miR-524 for the high-score genes (RB1, SMAD4, STAT1, CALML4, GNG13, and CDKN1A/CDKN1B genes) in the network. The miRNAs and anti-miRNA were transferred into HSCs using polyethylenimine (PEI). The gene expression levels were estimated using the RT-qPCR technique in the PEI + (miRNA/anti-miRNA)-contained cell groups (n = 6). Furthermore, CD markers (90, 16, and 45) were evaluated using flow cytometry. Strong relationships were found between the high-score genes, miRNAs, and chimeric anti-miRNA. The RB1, SMAD4, and STAT1 gene expression levels were decreased by miR-20a-5p (P < 0.05). Additionally, the anti-miRNA increased the gene expression level of GNG13 (P < 0.05), whereas the miR-423-5p decreased the CDKN1A gene expression level (P < 0.01). The cellular count also increased significantly (P < 0.05) but the CD45 differentiation marker did not change in the cell groups. The study revealed the predicted miRNA/anti-miRNA profile expands HSCs isolated from HUCB. While miR-20a-5p suppressed the RB1, SMAD4, and STAT1 genes involved in cellular differentiation, the anti-miRNA promoted the GNG13 gene related to the proliferation process. Notably, the mixed miRNA/anti-miRNA group exhibited the highest cellular expansion. This approach could hold promise for enhancing the cell quantity in HSC therapy.

Stemness subtypes in lower-grade glioma with prognostic biomarkers, tumor microenvironment, and treatment response

Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Stratification of glioma based on stemness scores in bulk and single-cell transcriptomes

BACKGROUND

Brain tumours are known to have a high mortality and morbidity rate due to their localised and frequent invasive growth. The concept that glioma resistance could originate from the dissimilarity in the vulnerability of clonogenic glial stem cells to chemotherapeutic drugs and radiation has driven the scientific community to reexamine the comprehension of glioma growth and strategies that target these cells or modify their stemness.

METHODS

Based on the enrichment scores of 12 stemness signatures, we identified glioma subtypes in both tumour bulks and single cells by clustering analysis. Furthermore, we comprehensively compared molecular and clinical features among the glioma subtypes.

RESULTS

Consistently, in seven different datasets, hierarchical clustering uncovered three subtypes of glioma, termed Stem-H, Stem-M, and Stem-L, with high, medium, and low stemness signatures, respectively. Stem-H and Stem-L exhibited the most unfavorable and favourable overall and disease-free survival, respectively. Stem-H showed the highest enrichment scores of the EMT, invasion, proliferation, differentiation, and metastasis processes signatures, while Stem-L displayed the lowest. Stem-H harboured a greater proportion of late-stage tumours compared to Stem-L. Moreover, Stem-H manifested higher tumour mutation burden, DNA damage repair and cell cycle activity, intratumour heterogeneity, and a more frequent incidence of TP53 and EGFR mutations than Stem-L. In contrast, Stem-L had higher O6-Methylguanine-DNA Methyltransferase (MGMT) methylation levels.

CONCLUSION

The classification of glioma based on stemness may offer new insights into the biology of the tumour, as well as more accurate clinical management of the disease.

Aberrant activation of TGF-β/ROCK1 enhances stemness during prostatic stromal hyperplasia

Benign prostatic hyperplasia (BPH) is a multifactorial disease in which abnormal growth factor activation and embryonic reawakening are considered important factors. Here we demonstrated that the aberrant activation of transforming growth factor β (TGF-β)/Rho kinase 1 (ROCK1) increased the stemness of BPH tissue by recruiting mesenchymal stem cells (MSCs), indicating the important role of embryonic reawakening in BPH. When TGF-β/ROCK1 is abnormally activated, MSCs are recruited and differentiate into fibroblasts/myofibroblasts, leading to prostate stromal hyperplasia. Further research showed that inhibition of ROCK1 activation suppressed MSC migration and their potential for stromal differentiation. Collectively, our findings suggest that abnormal activation of TGF-β/ROCK1 regulates stem cell lineage specificity, and the small molecule inhibitor GSK269962A could target ROCK1 and may be a potential treatment for BPH.

YBX1 promotes stemness and cisplatin insensitivity in intrahepatic cholangiocarcinoma via the AKT/β-catenin axis

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignancy characterized by a poor prognosis and closely linked to tumor stemness. However, the key molecules that regulate ICC stemness remain elusive. Although Y-box binding protein 1 (YBX1) negatively affects prognosis in various cancers by enhancing stemness and chemoresistance, its effect on stemness and cisplatin sensitivity in ICC remains unclear.

METHODS

Three bulk and single-cell RNA-seq datasets were analyzed to investigate YBX1 expression in ICC and its association with stemness. Clinical samples and colony/sphere formation assays validated the role of YBX1 in stemness and sensitivity to cisplatin. AZD5363 and KYA1979K explored the interaction of YBX1 with the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB/AKT) and WNT/β-catenin pathways.

RESULTS

YBX1 was significantly upregulated in ICC, correlated with worse overall survival and shorter postoperative recurrence time, and was higher in chemotherapy-non-responsive ICC tissues. The YBX1-high group exhibited significantly elevated stemness scores, and genes linked to YBX1 upregulation were enriched in multiple stemness-related pathways. Moreover, YBX1 expression is significantly correlated with several stemness-related genes (SOX9, OCT4, CD133, CD44 and EPCAM). Additionally, YBX1 overexpression significantly enhanced the colony- and spheroid-forming abilities of ICC cells, accelerated tumor growth in vivo and reduced their sensitivity to cisplatin. Conversely, the downregulation of YBX1 exerted the opposite effect. The transcriptomic analysis highlighted the link between YBX1 and the PI3K/AKT and WNT/β-catenin pathways. Further, AZD5363 and KYA1979K were used to clarify that YBX1 promoted ICC stemness through the regulation of the AKT/β-catenin axis.

CONCLUSIONS

YBX1 is upregulated in ICC and promotes stemness and cisplatin insensitivity via the AKT/β-catenin axis. Our study describes a novel potential therapeutic target for improving ICC prognosis.

Integrated Analysis of Clinical Outcome of Mesenchymal Stem Cell-related Genes in Pan-cancer

Background

Although the application of mesenchymal stem cells (MSCs) in engineered medicine, such as tissue regeneration, is well known, new evidence is emerging that shows that MSCs can also promote cancer progression, metastasis, and drug resistance. However, no large-scale cohort analysis of MSCs has been conducted to reveal their impact on the prognosis of cancer patients.

Objectives

We propose the MSC score as a novel surrogate for poor prognosis in pan-cancer.

Methods

We used single sample gene set enrichment analysis to quantify MSC-related genes into a signature score and identify the signature score as a potential independent prognostic marker for cancer using multivariate Cox regression analysis. TIDE algorithm and neural network were utilized to assess the predictive accuracy of MSC-related genes for immunotherapy.

Results

MSC-related gene expression significantly differed between normal and tumor samples across the 33 cancer types. Cox regression analysis suggested the MSC score as an independent prognostic marker for kidney renal papillary cell carcinoma, mesothelioma, glioma, and stomach adenocarcinoma. The abundance of fibroblasts was also more representative of the MSC score than the stromal score. Our findings supported the combined use of the TIDE algorithm and neural network to predict the accuracy of MSC-related genes for immunotherapy.

Conclusion

We comprehensively characterized the transcriptome, genome, and epigenetics of MSCs in pan-cancer and revealed the crosstalk of MSCs in the tumor microenvironment, especially with cancer-related fibroblasts. It is suggested that this may be one of the key sources of resistance to cancer immunotherapy.

The role of proliferating stem-like plasma cells in relapsed or refractory multiple myeloma: Insights from single-cell RNA sequencing and proteomic analysis

The management and comprehension of relapsed or refractory multiple myeloma (RRMM) continues to pose a significant challenge. By integrating single-cell RNA sequencing (scRNA-seq) data of 15 patients with plasma cell disorders (PCDs) and proteomic data obtained from mass spectrometry-based analysis of CD138+ plasma cells (PCs) from 144 PCDs patients, we identified a state of malignant PCs characterized by high stemness score and increased proliferation originating from RRMM. This state has been designated as proliferating stem-like plasma cells (PSPCs). NUCKS1 was identified as the gene marker representing the stemness of PSPCs. Comparison of differentially expressed genes among various PC states revealed a significant elevation in LGALS1 expression in PSPCs. Survival analysis on the MMRF CoMMpass dataset and GSE24080 dataset established LGALS1 as a gene associated with unfavourable prognostic implications for multiple myeloma. Ultimately, we discovered three specific ligand-receptor pairs within the midkine (MDK) signalling pathway network that play distinct roles in facilitating efficient cellular communication between PSPCs and the surrounding microenvironment cells. These insights have the potential to contribute to the understanding of molecular mechanism and the development of therapeutic strategies involving the application of stem-like cells in RRMM treatment.

siRNA treatment targeting integrin α11 overexpressed via EZH2-driven axis inhibits drug-resistant breast cancer progression

BACKGROUND

Breast cancer, the most prevalent cancer in women worldwide, faces treatment challenges due to drug resistance, posing a serious threat to patient survival. The present study aimed to identify the key molecules that drive drug resistance and aggressiveness in breast cancer cells and validate them as therapeutic targets.

METHODS

Transcriptome microarray and analysis using PANTHER pathway and StemChecker were performed to identify the most significantly expressed genes in tamoxifen-resistant and adriamycin-resistant MCF-7 breast cancer cells. Clinical relevance of the key genes was determined using Kaplan-Meier survival analyses on The Cancer Genome Atlas dataset of breast cancer patients. Gene overexpression/knockdown, spheroid formation, flow cytometric analysis, chromatin immunoprecipitation, immunocytochemistry, wound healing/transwell migration assays, and cancer stem cell transcription factor activation profiling array were used to elucidate the regulatory mechanism of integrin α11 expression. Tumour-bearing xenograft models were used to demonstrate integrin α11 is a potential therapeutic target.

RESULTS

Integrin α11 was consistently upregulated in drug-resistant breast cancer cells, and its silencing inhibited cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT) while restoring sensitivity to anticancer drugs. HIF1α, GLI-1, and EZH2 contributed the most to the regulation of integrin α11 and EZH2 expression, with EZH2 being more necessary for EZH2 autoinduction than HIF1α and GLI-1. Additionally, unlike HIF1α or EZH2, GLI-1 was the sole transcription factor activated by integrin-linked focal adhesion kinase, indicating GLI-1 as a key driver of the EZH2-integrin α11 axis operating for cancer stem cell survival and EMT. Kaplan-Meier survival analysis using The Cancer Genome Atlas (TCGA) dataset also revealed both EZH2 and integrin α11 could be strong prognostic factors of relapse-free and overall survival in breast cancer patients. However, the superior efficacy of integrin α11 siRNA therapy over EZH2 siRNA treatment was demonstrated by enhanced inhibition of tumour growth and prolonged survival in murine models bearing tumours.

CONCLUSION

Our findings elucidate that integrin α11 is upregulated by EZH2, forming a positive feedback circuit involving FAK-GLI-1 and contributing to drug resistance, cancer stem cell survival and EMT. Taken together, the results suggest integrin α11 as a promising prognostic marker and a powerful therapeutic target for drug-resistant breast cancer.

Exploring MiR-484 Regulation by Polyalthia longifolia: A Promising Biomarker and Therapeutic Target in Cervical Cancer through Integrated Bioinformatics and an In Vitro Analysis

BACKGROUND

MiR-484, implicated in various carcinomas, holds promise as a prognostic marker, yet its relevance to cervical cancer (CC) remains unclear. Our prior study demonstrated the Polyalthia longifolia downregulation of miR-484, inhibiting HeLa cells. This study investigates miR-484's potential as a biomarker and therapeutic target in CC through integrated bioinformatics and an in vitro analysis.

METHODS

MiR-484 levels were analyzed across cancers, including CC, from The Cancer Genome Atlas. The limma R package identified differentially expressed genes (DEGs) between high- and low-miR-484 CC cohorts. We assessed biological functions, tumor microenvironment (TME), immunotherapy, stemness, hypoxia, RNA methylation, and chemosensitivity differences. Prognostic genes relevant to miR-484 were identified through Cox regression and Kaplan-Meier analyses, and a prognostic model was captured via multivariate Cox regression. Single-cell RNA sequencing determined cell populations related to prognostic genes. qRT-PCR validated key genes, and the miR-484 effect on CC proliferation was assessed via an MTT assay.

RESULTS

MiR-484 was upregulated in most tumors, including CC, with DEGs enriched in skin development, PI3K signaling, and immune processes. High miR-484 expression correlated with specific immune cell infiltration, hypoxia, and drug sensitivity. Prognostic genes identified were predominantly epidermal and stratified patients with CC into risk groups, with the low-risk group showing enhanced survival and immunotherapeutic responses. qRT-PCR confirmed FGFR3 upregulation in CC cells, and an miR-484 mimic reversed the P. longifolia inhibitory effect on HeLa proliferation.

CONCLUSION

MiR-484 plays a crucial role in the CC progression and prognosis, suggesting its potential as a biomarker for targeted therapy.

N6-methyladenosine reader hnRNPA2B1 recognizes and stabilizes NEAT1 to confer chemoresistance in gastric cancer

BACKGROUND

Chemoresistance is a major cause of treatment failure in gastric cancer (GC). Heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) is an N6-methyladenosine (m6A)-binding protein involved in a variety of cancers. However, whether m6A modification and hnRNPA2B1 play a role in GC chemoresistance is largely unknown. In this study, we aimed to investigate the role of hnRNPA2B1 and the downstream mechanism in GC chemoresistance.

METHODS

The expression of hnRNPA2B1 among public datasets were analyzed and validated by quantitative PCR (qPCR), Western blotting, immunofluorescence, and immunohistochemical staining. The biological functions of hnRNPA2B1 in GC chemoresistance were investigated both in vitro and in vivo. RNA sequencing, methylated RNA immunoprecipitation, RNA immunoprecipitation, and RNA stability assay were performed to assess the association between hnRNPA2B1 and the binding RNA. The role of hnRNPA2B1 in maintenance of GC stemness was evaluated by bioinformatic analysis, qPCR, Western blotting, immunofluorescence, and sphere formation assays. The expression patterns of hnRNPA2B1 and downstream regulators in GC specimens from patients who received adjuvant chemotherapy were analyzed by RNAscope and multiplex immunohistochemistry.

RESULTS

Elevated expression of hnRNPA2B1 was found in GC cells and tissues, especially in multidrug-resistant (MDR) GC cell lines. The expression of hnRNPA2B1 was associated with poor outcomes of GC patients, especially in those who received 5-fluorouracil treatment. Silencing hnRNPA2B1 effectively sensitized GC cells to chemotherapy by inhibiting cell proliferation and inducing apoptosis both in vitro and in vivo. Mechanically, hnRNPA2B1 interacted with and stabilized long noncoding RNA NEAT1 in an m6A-dependent manner. Furthermore, hnRNPA2B1 and NEAT1 worked together to enhance the stemness properties of GC cells via Wnt/β-catenin signaling pathway. In clinical specimens from GC patients subjected to chemotherapy, the expression levels of hnRNPA2B1, NEAT1, CD133, and CD44 were markedly elevated in non-responders compared with responders.

CONCLUSION

Our findings indicated that hnRNPA2B1 interacts with and stabilizes lncRNA NEAT1, which contribute to the maintenance of stemness property via Wnt/β-catenin pathway and exacerbate chemoresistance in GC.

Identification and validation of stemness-based and ferroptosis-related molecular clusters in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

Activating p53 abolishes self-renewal of quiescent leukaemic stem cells in residual CML disease

Whilst it is recognised that targeting self-renewal is an effective way to functionally impair the quiescent leukaemic stem cells (LSC) that persist as residual disease in chronic myeloid leukaemia (CML), developing therapeutic strategies to achieve this have proved challenging. We demonstrate that the regulatory programmes of quiescent LSC in chronic phase CML are similar to that of embryonic stem cells, pointing to a role for wild type p53 in LSC self-renewal. In support of this, increasing p53 activity in primitive CML cells using an MDM2 inhibitor in combination with a tyrosine kinase inhibitor resulted in reduced CFC outputs and engraftment potential, followed by loss of multilineage priming potential and LSC exhaustion when combination treatment was discontinued. Our work provides evidence that targeting LSC self-renewal is exploitable in the clinic to irreversibly impair quiescent LSC function in CML residual disease - with the potential to enable more CML patients to discontinue therapy and remain in therapy-free remission.

Development of an invasion score based on metastasis-related pathway activity profiles for identifying invasive molecular subtypes of lung adenocarcinoma

The invasive capacity of lung adenocarcinoma (LUAD) is an important factor influencing patients' metastatic status and survival outcomes. However, there is still a lack of suitable biomarkers to evaluate tumor invasiveness. LUAD molecular subtypes were identified by unsupervised consistent clustering of LUAD. The differences in prognosis, tumor microenvironment (TME), and mutation were assessed among different subtypes. After that, the invasion-related gene score (IRGS) was constructed by genetic differential analysis, WGCNA analysis, and LASSO analysis, then we evaluated the relationship between IRGS and invasive characteristics, TME, and prognosis. The predictive ability of the IRGS was verified by in vitro experiments. Next, the "oncoPredict" R package and CMap were used to assess the potential value of IRGS in drug therapy. The results showed that LUAD was clustered into two molecular subtypes. And the C1 subtype exhibited a worse prognosis, higher stemness enrichment activity, less immune infiltration, and higher mutation frequency. Subsequently, IRGS developed based on molecular subtypes demonstrated a strong association with malignant characteristics such as invasive features, higher stemness scores, less immune infiltration, and worse survival. In vitro experiments showed that the higher IRGS LUAD cell had a stronger invasive capacity than the lower IRGS LUAD cell. Predictive analysis based on the "oncoPredict" R package showed that the high IRGS group was more sensitive to docetaxel, erlotinib, paclitaxel, and gefitinib. Among them, in vitro experiments verified the greater killing effect of paclitaxel on high IRGS cell lines. In addition, CMap showed that purvalanol-a, angiogenesis-inhibitor, and masitinib have potential therapeutic effects in the high IRGS group. In summary we identified and analyzed the molecular subtypes associated with the invasiveness of LUAD and developed IRGS that can efficiently predict the prognosis and invasive ability of the tumor. IRGS may be able to facilitate the precision treatment of LUAD to some extent.

Development of an m6A-Related lncRNAs Signature Predicts Tumor Stemness and Prognosis for Low-Grade Glioma Patients

Background

Growing evidence has revealed that m6A modification of long noncoding RNAs (lncRNAs) dynamically controls tumor stemness and tumorigenesis-related processes. However, the prognostic significance of m6A-related lncRNAs and their associations with stemness in low-grade glioma (LGG) remain to be clarified.

Methods

A multicenter transcriptome analysis of lncRNA expression in 1,247 LGG samples was performed in this study. The stemness landscape of LGG tumors was presented and associations with clinical features were revealed. The m6A-related lncRNAs were identified between stemness groups and were further prioritized via least absolute shrinkage and selection operator Cox regression analysis. A risk score model based on m6A-related lncRNAs was constructed and validated in external LGG datasets.

Results

Based on the expression of LINC02984, PFKP-DT, and CRNDE, a risk model and nomogram were constructed; they successfully predicted the survival of patients and were extended to external datasets. Significant correlations were observed between the risk score and tumor stemness. Moreover, patients in different risk groups exhibited distinct tumor immune microenvironments and immune signatures. We finally provided several potential compounds suitable for specific risk groups, which may aid in LGG treatment.

Conclusions

This novel signature presents noteworthy value in the prediction of prognosis and stemness status for LGG patients and will foster future research on the development of clinical regimens.

Stem cell landscape aids in tumor microenvironment identification and selection of therapeutic agents in gastric cancer

Gastric cancer stem cells (GCSCs) are strongly associated with the refractory characteristics of gastric cancer, including drug resistance, recurrence, and metastasis. The prognosis for advanced gastric cancer patients treated with multimodal therapy after surgery remains discouraging. GCSCs hold promise as therapeutic targets for GC patients. We obtained 26 sets of stem cell-related genes from the StemChecker database. The Consensus clustering algorithm was employed to discern three distinct stemness subtypes. Prognostic outcomes, components of the tumor microenvironment (TME), and responses to therapies were compared among these subtypes. Following this, a stemness-risk model was formulated using weighted gene correlation network analysis (WGCNA), alongside Cox regression and random survival forest analyses. The C2 subtype predominantly showed enrichment in negative prognostic CSC gene sets and demonstrated an immunosuppressive TME. This specific subtype exhibited minimal responsiveness to immunotherapies and demonstrated reduced sensitivity to drugs. Four pivotal genes were integrated into the construction of the stemness model. Gastric cancer patients with higher stemness-risk scores demonstrated poorer prognoses, a greater presence of immunosuppressive components in TME, and lower rates of treatment response. Subset analysis indicated that only the low-stemness risk subtype derives benefit from 5-fluorouracil-based adjuvant chemotherapy. The model's effectiveness in immunotherapeutic prediction was further validated in the PRJEB25780 cohort. Our study categorized gastric cancer patients into three stemness subtypes, each demonstrating distinct prognoses, components of TME infiltration, and varying sensitivity or resistance to standard chemotherapy or targeted therapy. We propose that the stemness risk model may help the development of well-grounded treatment recommendations and prognostic assessments.

Senescence risk score: a multifaceted prognostic tool predicting outcomes, stemness, and immune responses in colorectal cancer

Colorectal cancer (CRC) remains a primary cause of cancer mortality globally, necessitating precise prognostic indicators for effective clinical management. Our study introduces the Senescence Risk Score (SRRS), based on several senescence-related genes (SRGs), a potent prognostic tool designed to measure cellular senescence in CRC. The higher SRRS predicts a poorer prognosis, providing a novel and efficient approach to patient stratification. Notably, we found that SRRS correlates with methylation and mutation variations, and increased immune infiltration in the tumor microenvironment, thus revealing potential therapeutic targets. We also discovered an inverse relationship between SRRS and cell stemness, which could have significant implications for cancer treatment strategies. Utilizing bioinformatics resources and machine learning, we identified LIMK1 and WRN as key genes associated with SRRS, further enhancing its prognostic value. Importantly, the modulation of these genes significantly impacts cellular senescence, proliferation, and stemness in CRC cells. In summary, our development of SRRS offers a powerful tool for CRC prognosis and paves the way for novel therapeutic strategies, underscoring its potential in transforming CRC patient management.

Construction of stemness gene score by bulk and single-cell transcriptome to characterize the prognosis of breast cancer

Breast cancer (BC) is a heterogeneous disease characterized by significant differences in prognosis and therapy response. Numerous prognostic tools have been developed for breast cancer. Usually these tools are based on bulk RNA-sequencing (RNA-Seq) and ignore tumor heterogeneity. Consequently, the goal of this study was to construct a single-cell level tool for predicting the prognosis of BC patients. In this study, we constructed a stemness-risk gene score (SGS) model based on single-sample gene set enrichment analysis (ssGSEA). Patients were divided into two groups based on the median SGS. Patients with a high SGS scores had a significantly worse prognosis than those with a low SGS, and these groups exhibited differences in several tumor characteristics, such as immune infiltration, gene mutations, and copy number variants. Our results indicate that the SGS is a reliable tool for predicting prognosis and response to immunotherapy in BC patients.

Identification of a novel stemness-related signature with appealing implications in discriminating the prognosis and therapy responses for prostate cancer

PURPOSE

Cancer stemness represents the tumor-initiation and self-renewal potentials of cancer stem cells. It is involved in prostate cancer progression and resistance to therapy. Herein, we aimed to unveil the stemness features, establish a novel prognostic model, and identify potential therapeutic targets.

METHODS

26 stemness-related signatures were obtained from StemChecker. The expression profiles and clinical traits of TCGA-PRAD were obtained from TCGA and cBioPortal, respectively. GSE5446 and GSE70769 cohorts were acquired from GEO. PRAD_MSKCC cohort was also retrieved via the cBioPortal. The consensus clustering method was used for stemness subclusters classification. WGCNA was used to identify hub genes related to the stemness subcluster. The most important feature was explored in vitro.

RESULTS

Prostate cancer patients of TCGA-PRAD were divided into two subclusters (C1 and C2) based on the enrichment scores of the 26 stemness-related signatures. C1 was characterized by decreased survival, rich infiltrations of M0 macrophages and regulatory T cells, minimum sensitivity to chemotherapy, and a low response to immunotherapy. Hub genes of the red module with the highest correlation with C1 were subsequently identified by WGCNA and subjected to stemness-related risk model construction based on the machine-learning framework. Prostate cancer patients with high stemness scores had unfavorable prognosis, immunosuppressive tumor microenvironment, minimum sensitivity to chemotherapy, and a low response to immunotherapy. MXD3, the most important factor of the model, can regulate the stemness traits of prostate cancer cells.

CONCLUSIONS

Our study depicted the stemness landscapes of prostate cancer and characterized two subclusters with diverse prognoses and tumor immune microenvironments. A stemness-risk signature was developed and demonstrated prospective implications in predicting prognosis and precision medicine.

Enhancer remodeling drives MLL oncogene-dependent transcriptional dysregulation in leukemia stem cells

Acute myeloid leukemia (AML) with mixed-lineage leukemia (MLL) gene rearrangement (MLLr) comprises a cellular hierarchy in which a subpopulation of cells serves as functional leukemia stem cells (LSCs). They are maintained by a unique gene expression program and chromatin states, which are thought to reflect the actions of enhancers. Here, we delineate the active enhancer landscape and observe pervasive enhancer malfunction in LSCs. Reconstruction of regulatory networks revealed a master set of hematopoietic transcription factors. We show that EP300 is an essential transcriptional coregulator for maintaining LSC oncogenic potential because it controls essential gene expression through modulation of H3K27 acetylation and assessments of transcription factor dependencies. Moreover, the EP300 inhibitor A-485 affects LSC growth by targeting enhancer activity via histone acetyltransferase domain inhibition. Together, these data implicate a perturbed MLLr-specific enhancer accessibility landscape, suggesting the possibility for disruption of the LSC enhancer regulatory axis as a promising therapeutic strategy in AML.

The characteristic of stem-related genes with pancreatic carcinoma cell after irradiation

Purpose

To investigate stem-related differentially expressed genes (DEGs) and their potential mechanism in pancreatic cancer cells (MIAPaCa-2) exposed to x-ray and proton radiation, as well as how these factors affected the prognosis of patients with pancreatic adenocarcinoma (PADC).

Methods

The stem-related DEGs were screened using the online tool Stemchecker after protons and x-rays were used to irradiate MIAPaCa-2 cells. Analysis was done on the probable processes and prognostic significance of the DEGs in PAC patients.

Results

Four datasets containing 401 DEGs were filtered, and the stem-related DEGs for each irradiation type indicated a variety of radiobiological characteristics. In pancreatic cancer cells, a number of stem-related DEGs may serve as biomarkers of radiation effects. Patients with pancreatic cancer demonstrated predictive significance for GRB7, B2M, and PMAIP1.

Conclusions

MIAPaCa-2 cells exposed to x-rays and protons repeatedly displayed heterogeneous expression of stem-related DEGs involved in complex radiosensitivity, radio-resistance, and radio-induced mortality pathways. GRB7 and B2M were considered potential radiation sensitivity indicators for pancreatic cancer.

Identification and validation of a novel cuproptosis-related stemness signature to predict prognosis and immune landscape in lung adenocarcinoma by integrating single-cell and bulk RNA-sequencing

Background

Cancer stem cells (CSCs) play vital roles in lung adenocarcinoma (LUAD) recurrence, metastasis, and drug resistance. Cuproptosis has provided a novel insight into the treatment of lung CSCs. However, there is a lack of knowledge regarding the cuproptosis-related genes combined with the stemness signature and their roles in the prognosis and immune landscape of LUAD.

Methods

Cuproptosis-related stemness genes (CRSGs) were identified by integrating single-cell and bulk RNA-sequencing data in LUAD patients. Subsequently, cuproptosis-related stemness subtypes were classified using consensus clustering analysis, and a prognostic signature was constructed by univariate and least absolute shrinkage operator (LASSO) Cox regression. The association between signature with immune infiltration, immunotherapy, and stemness features was also investigated. Finally, the expression of CRSGs and the functional roles of target gene were validated in vitro.

Results

We identified six CRSGs that were mainly expressed in epithelial and myeloid cells. Three distinct cuproptosis-related stemness subtypes were identified and associated with the immune infiltration and immunotherapy response. Furthermore, a prognostic signature was constructed to predict the overall survival (OS) of LUAD patients based on eight differently expressed genes (DEGs) with cuproptosis-related stemness signature (KLF4, SCGB3A1, COL1A1, SPP1, C4BPA, TSPAN7, CAV2, and CTHRC1) and confirmed in validation cohorts. We also developed an accurate nomogram to improve clinical applicability. Patients in the high-risk group showed worse OS with lower levels of immune cell infiltration and higher stemness features. Ultimately, further cellular experiments were performed to verify the expression of CRSGs and prognostic DEGs and demonstrate that SPP1 could affect the proliferation, migration, and stemness of LUAD cells.

Conclusion

This study developed a novel cuproptosis-related stemness signature that can be used to predict the prognosis and immune landscape of LUAD patients, and provided potential therapeutic targets for lung CSCs in the future.

Pancancer Analysis Revealed the Value of RAC2 in Immunotherapy and Cancer Stem Cell

Objective

To investigate the oncogenic effect and clinical significance of RAC2 in pancarcinoma from the perspective of tumor immunity and cancer stem cell.

Methods

After in-depth mining of TCGA, GEO, UCSC, and other databases, basic information of the RAC2 gene and its expression in tumor tissues as well as the relationship between RAC2 and tumor were analyzed based on survival, mutation, immune microenvironment, tumor stemness, and enrichment analysis on related pathways.

Results

RAC2 mRNA expression was increased in most tumor tissues and was associated with their prognosis. Compared to normal tissues, the RAC2 mutation rate was higher in patients with skin melanoma, uterine sarcoma, and endometrial cancer. RAC2 had a strong relation with immune cell infiltration, immunomodulators, immunotherapy markers, cancer stem cell of THYM, and immune-related pathways.

Conclusions

This study explored the potential importance of RAC2 in the prognosis, immunotherapy, and cancer stem cell of 33 cancers, laying the foundation for mechanistic experiments and its future application in clinical practice. However, the results using bioinformatics methods could be affected by the differences in patients across databases. Thus, the present results were preliminary and required further experimental validation.

Integration of Stemness Gene Signatures Reveals Core Functional Modules of Stem Cells and Potential Novel Stemness Genes

Stem cells encompass a variety of different cell types which converge on the dual capacity to self-renew and differentiate into one or more lineages. These characteristic features are key for the involvement of stem cells in crucial biological processes such as development and ageing. To decipher their underlying genetic substrate, it is important to identify so-called stemness genes that are common to different stem cell types and are consistently identified across different studies. In this meta-analysis, 21 individual stemness signatures for humans and another 21 for mice, obtained from a variety of stem cell types and experimental techniques, were compared. Although we observed biological and experimental variability, a highly significant overlap between gene signatures was identified. This enabled us to define integrated stemness signatures (ISSs) comprised of genes frequently occurring among individual stemness signatures. Such integrated signatures help to exclude false positives that can compromise individual studies and can provide a more robust basis for investigation. To gain further insights into the relevance of ISSs, their genes were functionally annotated and connected within a molecular interaction network. Most importantly, the present analysis points to the potential roles of several less well-studied genes in stemness and thus provides promising candidates for further experimental validation.

Crosstalk between Mesenchymal Stem Cells and Cancer Stem Cells Reveals a Novel Stemness-Related Signature to Predict Prognosis and Immunotherapy Responses for Bladder Cancer Patients

Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management.

RSL24D1 sustains steady-state ribosome biogenesis and pluripotency translational programs in embryonic stem cells

Embryonic stem cell (ESC) fate decisions are regulated by a complex circuitry that coordinates gene expression at multiple levels from chromatin to mRNA processing. Recently, ribosome biogenesis and translation have emerged as key pathways that efficiently control stem cell homeostasis, yet the underlying molecular mechanisms remain largely unknown. Here, we identified RSL24D1 as highly expressed in both mouse and human pluripotent stem cells. RSL24D1 is associated with nuclear pre-ribosomes and is required for the biogenesis of 60S subunits in mouse ESCs. Interestingly, RSL24D1 depletion significantly impairs global translation, particularly of key pluripotency factors and of components from the Polycomb Repressive Complex 2 (PRC2). While having a moderate impact on differentiation, RSL24D1 depletion significantly alters ESC self-renewal and lineage commitment choices. Altogether, these results demonstrate that RSL24D1-dependant ribosome biogenesis is both required to sustain the expression of pluripotent transcriptional programs and to silence PRC2-regulated developmental programs, which concertedly dictate ESC homeostasis.

Identification of SALL4 Expressing Islet-1+ Cardiovascular Progenitor Cell Clones

The utilization of cardiac progenitor cells (CPCs) has been shown to induce favorable regenerative effects. While there are various populations of endogenous CPCs in the heart, there is no consensus regarding which population is ideal for cell-based regenerative therapy. Early-stage progenitor cells can be differentiated into all cardiovascular lineages, including cardiomyocytes and endothelial cells. Identifying an Islet-1+ (Isl-1+) early-stage progenitor population with enhanced stemness, multipotency and differentiation potential would be beneficial for the development of novel regenerative therapies. Here, we investigated the transcriptome of human neonatal Isl-1+ CPCs. Isl-1+ human neonatal CPCs exhibit enhanced stemness properties and were found to express Spalt-like transcription factor 4 (SALL4). SALL4 plays a role in embryonic development as well as proliferation and expansion of hematopoietic progenitor cells. SALL4, SOX2, EpCAM and TBX5 are co-expressed in the majority of Isl-1+ clones isolated from neonatal patients. The pre-mesendodermal transcript TFAP2C was identified in select Isl-1, SALL4, SOX2, EpCAM and TBX5 expressing clones. The ability to isolate and expand pre-mesendodermal stage cells from human patients is a novel finding that holds potential value for applications in regenerative medicine.

Integrated Analysis Revealed an Inflammatory Cancer-Associated Fibroblast-Based Subtypes with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Bladder Cancer Patients

Inflammatory cancer-associated fibroblasts (iCAFs) are closely related to progression, anticancer therapeutic resistance, and poor prognosis of bladder cancer (BCa). However, the functional role of iCAFs in BCa has been poorly studied. In our study, two BCa scRNA-seq datasets (GSE130001 and GSE146137) were obtained and integrated by the Seurat pipeline. Based on reported markers (COL1A1 and PDGFRA), iCAFs were identified and the related signature of 278 markers was developed. Following unsupervised consensus clustering, two molecular subtypes of TCGA-BLCA were identified and characterized by distinct dysregulated cancer hallmarks, immunological tumor microenvironments, prognoses, responses to chemotherapy/immunotherapy, and stemness. Subsequently, the robustness of the signature-based clustering, in terms of prognosis and therapeutic response prediction, was validated in a GEO-meta cohort with seven independent GEO datasets of 519 BCa patients, and three immune checkpoint inhibitor (ICI)-treated cohorts. Considering the heterogeneity, re-clustering of iCAFs was performed and a subpopulation, named "LOXL2+ iCAFs", was identified. Co-culture CM derived from LOXL2 overexpression/silencing CAFs with T24 cells revealed that overexpression of LOXL2 in CAFs promoted while silencing LOXL2 inhibited the proliferation, migration, and invasion of T24 cells through IL32. Moreover, the positive correlation between LOXL2 and CD206, an M2 macrophage polarization marker, has been observed and validated. Collectively, integrated single-cell and bulk RNA sequencing analyses revealed an iCAF-related signature that can predict prognosis and response to immunotherapy for BCa. Additionally, the hub gene LOXL2 may serve as a promising target for BCa treatment.

RhoC in association with TET2/WDR5 regulates cancer stem cells by epigenetically modifying the expression of pluripotency genes

Emerging evidence illustrates that RhoC has divergent roles in cervical cancer progression where it controls epithelial to mesenchymal transition (EMT), migration, angiogenesis, invasion, tumor growth, and radiation response. Cancer stem cells (CSCs) are the primary cause of recurrence and metastasis and exhibit all of the above phenotypes. It, therefore, becomes imperative to understand if RhoC regulates CSCs in cervical cancer. In this study, cell lines and clinical specimen-based findings demonstrate that RhoC regulates tumor phenotypes such as clonogenicity and anoikis resistance. Accordingly, inhibition of RhoC abrogated these phenotypes. RNA-seq analysis revealed that RhoC over-expression resulted in up-regulation of 27% of the transcriptome. Further, the Infinium MethylationEPIC array showed that RhoC over-expressing cells had a demethylated genome. Studies divulged that RhoC via TET2 signaling regulated the demethylation of the genome. Further investigations comprising ChIP-seq, reporter assays, and mass spectrometry revealed that RhoC associates with WDR5 in the nucleus and regulates the expression of pluripotency genes such as Nanog. Interestingly, clinical specimen-based investigations revealed the existence of a subset of tumor cells marked by RhoC+/Nanog+ expression. Finally, combinatorial inhibition (in vitro) of RhoC and its partners (WDR5 and TET2) resulted in increased sensitization of clinical specimen-derived cells to radiation. These findings collectively reveal a novel role for nuclear RhoC in the epigenetic regulation of Nanog and identify RhoC as a regulator of CSCs. The study nominates RhoC and associated signaling pathways as therapeutic targets.

Gene interaction perturbation network deciphers a high-resolution taxonomy in colorectal cancer

Molecular subtypes of colorectal cancer (CRC) are currently identified via the snapshot transcriptional profiles, largely ignoring the dynamic changes of gene expressions. Conversely, biological networks remain relatively stable irrespective of time and condition. Here, we introduce an individual-specific gene interaction perturbation network-based (GIN) approach and identify six GIN subtypes (GINS1-6) with distinguishing features: (i) GINS1 (proliferative, 24%~34%), elevated proliferative activity, high tumor purity, immune-desert, PIK3CA mutations, and immunotherapeutic resistance; (ii) GINS2 (stromal-rich, 14%~22%), abundant fibroblasts, immune-suppressed, stem-cell-like, SMAD4 mutations, unfavorable prognosis, high potential of recurrence and metastasis, immunotherapeutic resistance, and sensitive to fluorouracil-based chemotherapy; (iii) GINS3 (KRAS-inactivated, 13%~20%), high tumor purity, immune-desert, activation of EGFR and ephrin receptors, chromosomal instability (CIN), fewer KRAS mutations, SMOC1 methylation, immunotherapeutic resistance, and sensitive to cetuximab and bevacizumab; (iv) GINS4 (mixed, 10%~19%), moderate level of stromal and immune activities, transit-amplifying-like, and TMEM106A methylation; (v) GINS5 (immune-activated, 12%~24%), stronger immune activation, plentiful tumor mutation and neoantigen burden, microsatellite instability and high CpG island methylator phenotype, BRAF mutations, favorable prognosis, and sensitive to immunotherapy and PARP inhibitors; (vi) GINS6, (metabolic, 5%~8%), accumulated fatty acids, enterocyte-like, and BMP activity. Overall, the novel high-resolution taxonomy derived from an interactome perspective could facilitate more effective management of CRC patients.

Mining Transcriptomic Data to Uncover the Association between CBX Family Members and Cancer Stemness

Genetic and epigenetic changes might facilitate the acquisition of stem cell-like phenotypes of tumors, resulting in worse patients outcome. Although the role of chromobox (CBX) domain proteins, a family of epigenetic factors that recognize specific histone marks, in the pathogenesis of several tumor types is well documented, little is known about their association with cancer stemness. Here, we have characterized the relationship between the CBX family members' expression and cancer stemness in liver, lung, pancreatic, and uterine tumors using publicly available TCGA and GEO databases and harnessing several bioinformatic tools (i.e., Oncomine, GEPIA2, TISIDB, GSCA, UALCAN, R2 platform, Enrichr, GSEA). We demonstrated that significant upregulation of CBX3 and downregulation of CBX7 are consistently associated with enriched cancer stem-cell-like phenotype across distinct tumor types. High CBX3 expression is observed in higher-grade tumors that exhibit stem cell-like traits, and CBX3-associated gene expression profiles are robustly enriched with stemness markers and targets for c-Myc transcription factor regardless of the tumor type. Similar to high-stemness tumors, CBX3-overexpressing cancers manifest a higher mutation load. On the other hand, higher-grade tumors are characterized by the significant downregulation of CBX7, and CBX7-associated gene expression profiles are significantly depleted with stem cell markers. In contrast to high-stemness tumors, cancer with CBX7 upregulation exhibit a lower mutation burden. Our results clearly demonstrate yet unrecognized association of high CBX3 and low CBX7 expression with cancer stem cell-like phenotype of solid tumors.

Characterization of stem cell landscape and identification of stemness-relevant prognostic gene signature to aid immunotherapy in colorectal cancer

Background

It is generally accepted that colorectal cancer (CRC) originates from cancer stem cells (CSCs), which are responsible for CRC progression, metastasis and therapy resistance. The high heterogeneity of CSCs has precluded clinical application of CSC-targeting therapy. Here, we aimed to characterize the stemness landscapes and screen for certain patients more responsive to immunotherapy.

Methods

Twenty-six stem cell gene sets were acquired from StemChecker database. Consensus clustering algorithm was applied for stemness subtypes identification on 1,467 CRC samples from TCGA and GEO databases. The differences in prognosis, tumor microenvironment (TME) components, therapy responses were evaluated among subtypes. Then, the stemness-risk model was constructed by weighted gene correlation network analysis (WGCNA), Cox regression and random survival forest analyses, and the most important marker was experimentally verified.

Results

Based on single-sample gene set enrichment analysis (ssGSEA) enrichments scores, CRC patients were classified into three subtypes (C1, C2 and C3). C3 subtype exhibited the worst prognosis, highest macrophages M0 and M2 infiltrations, immune and stromal scores, and minimum sensitivity to immunotherapies, but was more sensitive to drugs like Bosutinib, Docetaxel, Elesclomol, Gefitinib, Lenalidomide, Methotrexate and Sunitinib. The turquoise module was identified by WGCNA that it was most positively correlated with C3 but most negatively with C2, and five hub genes in turquoise module were identified for stemness model construction. CRC patients with higher stemness scores exhibited worse prognosis, more immunosuppressive components in TME and lower immunotherapeutic responses. Additionally, the model’s immunotherapeutic prediction efficacy was further confirmed from two immunotherapy cohorts (anti-PD-L1 in IMvigor210 cohort and anti-PD-1 in GSE78220 cohort). Mechanistically, Gene Set Enrichment Analysis (GSEA) results revealed high stemness score group was enriched in interferon gamma response, interferon alpha response, P53 pathway, coagulation, apoptosis, KRAS signaling upregulation, complement, epithelial–mesenchymal transition (EMT) and IL6-mediated JAK-STAT signaling gene sets.

Conclusions

Our study characterized three stemness-related subtypes with distinct prognosis and TME patterns in CRC patients, and a 5-gene stemness-risk model was constructed by comprehensive bioinformatic analyses. We suggest our stemness model has prospective clinical implications for prognosis evaluation and might facilitate physicians selecting prospective responders for preferential use of current immune checkpoint inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-02913-0.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets

PURPOSE

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC.

METHODS

After comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1-C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed.

RESULTS

The ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1's susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC.

CONCLUSION

The identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

Comparative whole-genome transcriptome analysis in renal cell populations reveals high tissue specificity of MAPK/ERK targets in embryonic kidney

Background

MAPK/ERK signaling is a well-known mediator of extracellular stimuli controlling intracellular responses to growth factors and mechanical cues. The critical requirement of MAPK/ERK signaling for embryonic stem cell maintenance is demonstrated, but specific functions in progenitor regulation during embryonic development, and in particular kidney development remain largely unexplored. We previously demonstrated MAPK/ERK signaling as a key regulator of kidney growth through branching morphogenesis and normal nephrogenesis where it also regulates progenitor expansion. Here, we performed RNA sequencing-based whole-genome expression analysis to identify transcriptional MAPK/ERK targets in two distinct renal populations: the ureteric bud epithelium and the nephron progenitors.

Results

Our analysis revealed a large number (5053) of differentially expressed genes (DEGs) in nephron progenitors and significantly less (1004) in ureteric bud epithelium, reflecting likely heterogenicity of cell types. The data analysis identified high tissue-specificity, as only a fraction (362) of MAPK/ERK targets are shared between the two tissues. Tissue-specific MAPK/ERK targets participate in the regulation of mitochondrial energy metabolism in nephron progenitors, which fail to maintain normal mitochondria numbers in the MAPK/ERK-deficient tissue. In the ureteric bud epithelium, a dramatic decline in progenitor-specific gene expression was detected with a simultaneous increase in differentiation-associated genes, which was not observed in nephron progenitors. Our experiments in the genetic model of MAPK/ERK deficiency provide evidence that MAPK/ERK signaling in the ureteric bud maintains epithelial cells in an undifferentiated state. Interestingly, the transcriptional targets shared between the two tissues studied are over-represented by histone genes, suggesting that MAPK/ERK signaling regulates cell cycle progression and stem cell maintenance through chromosome condensation and nucleosome assembly.

Conclusions

Using tissue-specific MAPK/ERK inactivation and RNA sequencing in combination with experimentation in embryonic kidneys, we demonstrate here that MAPK/ERK signaling maintains ureteric bud tip cells, suggesting a regulatory role in collecting duct progenitors. We additionally deliver new mechanistic information on how MAPK/ERK signaling regulates progenitor maintenance through its effects on chromatin accessibility and energy metabolism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01309-z.

Stemness Subtypes and Scoring System Predict Prognosis and Efficacy of Immunotherapy in Soft Tissue Sarcoma

Tumor stemness has been reported to play important roles in cancers. However, a comprehensive analysis of tumor stemness remains to be performed to investigate the specific mechanisms and practical values of stemness in soft tissue sarcomas (STS). Here, we applied machine learning to muti-omic data of patients from TCGA-SARC and GSE21050 cohorts to reveal important roles of stemness in STS. We demonstrated limited roles of existing mRNAsi in clinical application. Therefore, based on stemness-related signatures (SRSs), we identified three stemness subtypes with distinct stemness, immune, and metabolic characteristics using consensus clustering. The low-stemness subtype had better prognosis, activated innate and adaptive immunity (e.g., infiltrating B, DC, Th1, CD8+ T, activated NK, gamma delta T cells, and M1 macrophages), more enrichment of metabolic pathways, more sites with higher methylation level, higher gene mutations, CNA burdens, and immunogenicity indicators. Furthermore, the 16 SRS-based stemness prognostic index (SPi) was developed, and we found that low-SPi patients with low stemness had better prognosis and other characteristics similar to those in the low-stemness subtype. Besides, low-stemness subtype and low-SPi patients could benefit from immunotherapy. The predictive value of SPi in immunotherapy was more accurate after the addition of MSI into SPi. MSI^lowSPi^low patients might be more sensitive to immunotherapy. In conclusion, we highlighted mechanisms and practical values of the stemness in STS. We also recommended the combination of MSI and SPi which is a promising tool to predict prognosis and achieve precise treatments of immunotherapy in STS.

Uncovering Pharmacological Opportunities for Cancer Stem Cells-A Systems Biology View

Cancer stem cells (CSCs) represent a small fraction of the total cancer cell population, yet they are thought to drive disease propagation, therapy resistance and relapse. Like healthy stem cells, CSCs possess the ability to self-renew and differentiate. These stemness phenotypes of CSCs rely on multiple molecular cues, including signaling pathways (for example, WNT, Notch and Hedgehog), cell surface molecules that interact with cellular niche components, and microenvironmental interactions with immune cells. Despite the importance of understanding CSC biology, our knowledge of how neighboring immune and tumor cell populations collectively shape CSC stemness is incomplete. Here, we provide a systems biology perspective on the crucial roles of cellular population identification and dissection of cell regulatory states. By reviewing state-of-the-art single-cell technologies, we show how innovative systems-based analysis enables a deeper understanding of the stemness of the tumor niche and the influence of intratumoral cancer cell and immune cell compositions. We also summarize strategies for refining CSC systems biology, and the potential role of this approach in the development of improved anticancer treatments. Because CSCs are amenable to cellular transitions, we envision how systems pharmacology can become a major engine for discovery of novel targets and drug candidates that can modulate state transitions for tumor cell reprogramming. Our aim is to provide deeper insights into cancer stemness from a systems perspective. We believe this approach has great potential to guide the development of more effective personalized cancer therapies that can prevent CSC-mediated relapse.

Stemness Refines the Classification of Colorectal Cancer With Stratified Prognosis, Multi-Omics Landscape, Potential Mechanisms, and Treatment Options

Background

Stemness refers to the capacities of self-renewal and repopulation, which contributes to the progression, relapse, and drug resistance of colorectal cancer (CRC). Mounting evidence has established the links between cancer stemness and intratumoral heterogeneity across cancer. Currently, the intertumoral heterogeneity of cancer stemness remains elusive in CRC.

Methods

This study enrolled four CRC datasets, two immunotherapy datasets, and a clinical in-house cohort. Non-negative matrix factorization (NMF) was performed to decipher the heterogeneity of cancer stemness. Multiple machine learning algorithms were applied to develop a nine-gene stemness cluster predictor. The clinical outcomes, multi-omics landscape, potential mechanisms, and immune features of the stemness clusters were further explored.

Results

Based on 26 published stemness signatures derived by alternative approaches, we decipher two heterogeneous clusters, low stemness cluster 1 (C1) and high stemness cluster 2 (C2). C2 possessed a higher proportion of advanced tumors and displayed worse overall survival and relapse-free survival compared with C1. The MSI-H and CMS1 tumors tended to enrich in C1, and the mesenchymal subtype CMS4 was the prevalent subtype of C2. Subsequently, we developed a nine-gene stemness cluster predictor, which robustly validated and reproduced our stemness clusters in three independent datasets and an in-house cohort. C1 also displayed a generally superior mutational burden, and C2 possessed a higher burden of copy number deletion. Further investigations suggested that C1 enriched numerous proliferation-related biological processes and abundant immune infiltration, while C2 was significantly associated with mesenchyme development and differentiation. Given results derived from three algorithms and two immunotherapeutic cohorts, we observed C1 could benefit more from immunotherapy. For patients with C2, we constructed a ridge regression model and further identified nine latent therapeutic agents, which might improve their clinical outcomes.

Conclusions

This study proposed two stemness clusters with stratified prognosis, multi-omics landscape, potential mechanisms, and treatment options. Current work not only provided new insights into the heterogeneity of cancer stemness, but also shed light on optimizing decision-making in immunotherapy and chemotherapy.

Implications of Stemness Features in 1059 Hepatocellular Carcinoma Patients from Five Cohorts: Prognosis, Treatment Response, and Identification of Potential Compounds

Simple Summary

Cancer stemness has been reported to drive hepatocellular carcinoma (HCC) tumorigenesis and treatment resistance. However, comprehensive interpretations of transcriptomic stemness features in HCC patients have not been conducted in multiple cohorts. Our aim was to interpret clinical and therapeutic implications of transcriptional stemness features and explore potential compounds for HCC treatment. We found that transcriptional stemness indexes (mRNAsi) were independently associated with worse HCC prognosis. The HCC stemness risk model (HSRM) developed in this study significantly predicted prognosis and treatment response in various HCC cohorts. Analysis of two stemness subtypes suggested several liver-specific metabolic pathways, and mutations of TP53 and RB1 were associated with HCC transcriptional stemness. Moreover, we also identified potential compounds that target HCC transcriptional stemness. Our findings comprehensively characterized transcriptional stemness as a risk factor in HCC progression and treatment.

Abstract

Cancer stemness has been reported to drive hepatocellular carcinoma (HCC) tumorigenesis and treatment resistance. In this study, five HCC cohorts with 1059 patients were collected to calculate transcriptional stemness indexes (mRNAsi) by the one-class logistic regression machine learning algorithm. In the TCGA-LIHC cohort, we found mRNAsi was an independent prognostic factor, and 626 mRNAsi-related genes were identified by Spearman correlation analysis. The HCC stemness risk model (HSRM) was trained in the TCGA-LIHC cohort and significantly discriminated overall survival in four independent cohorts. HSRM was also significantly associated with transarterial chemoembolization treatment response and rapid tumor growth in HCC patients. Consensus clustering was conducted based on mRNAsi-related genes to divide 1059 patients into two stemness subtypes. On gene set variation analysis, samples of subtype I were found enriched with pathways such as DNA replication and cell cycle, while several liver-specific metabolic pathways were inhibited in these samples. Somatic mutation analysis revealed more frequent mutations of TP53 and RB1 in the subtype I samples. In silico analysis suggested topoisomerase, cyclin-dependent kinase, and histone deacetylase as potential targets to inhibit HCC stemness. In vitro assay showed two predicted compounds, Aminopurvalanol-a and NCH-51, effectively suppressed oncosphere formation and impaired viability of HCC cell lines, which may shed new light on HCC treatment.

Classification of lung adenocarcinoma based on stemness scores in bulk and single cell transcriptomes

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This study explores tumor stemness based on both bulk tumor and single cell transcriptome datasets.

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High-stemness tumors are less responsive to immunotherapy and targeted therapy compared with low-stemness tumors.

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Many high-stemness cells are at the beginning of the cell evolution trajectory, while most low-stemness cells are in the terminal or later phase.

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The correlations of tumor stemness with intratumor heterogeneity and tumor immunity were in the opposite direction between bulk tumors and single cells.

Tumor stemness is associated with tumor progression and therapy resistance. The recent advances in sequencing, genomics, and computational technologies have facilitated investigation into the tumor stemness cell-like characteristics. We identified subtypes of lung adenocarcinoma (LUAD) in bulk tumors or single cells based on the enrichment scores of 12 stemness signatures by clustering analysis of their transcriptomic profiles. Three stemness subtypes of LUAD were identified: St-H, St-M, and St-L, having high, medium, and low stemness signatures, respectively, consistently in six different datasets. Among the three subtypes, St-H was the most enriched in epithelial-mesenchymal transition, invasion, and metastasis signaling, genomically instable, irresponsive to immunotherapies and targeted therapies, and hence had the worst prognosis. We observed that intratumor heterogeneity was significantly higher in high-stemness than in low-stemness bulk tumors, but significantly lower in high-stemness than in low-stemness single cancer cells. Moreover, tumor immunity was stronger in high-stemness than in low-stemness cancer cells, but weaker in high-stemness than in low-stemness bulk tumors. These differences between bulk tumors and single cancer cells could be attributed to the non-tumor cells in bulk tumors that confounded the results of correlation analysis. Furthermore, pseudotime analysis showed that many St-H cells were at the beginning of the cell evolution trajectory, compared to most St-L cells in the terminal or later phase, suggesting that many low-stemness cells are originated from high-stemness cells. The stemness-based classification of LUAD may provide novel insights into the tumor biology as well as precise clinical management of this disease.

Identification of stem cell-related subtypes and risk scoring for gastric cancer based on stem genomic profiling

Background

Although numerous studies demonstrate the role of cancer stem cells in occurrence, recurrence, and distant metastases in gastric cancer (GC), little is known about the evolving genetic and epigenetic changes in the stem and progenitor cells. The purpose of this study was to identify the stem cell subtypes in GC and examine their clinical relevance.

Methods

Two publicly available datasets were used to identify GC stem cell subtypes, and consensus clustering was performed by unsupervised machine learning methods. The cancer stem cell (CSC) typing-related risk scoring (RS) model was established through multivariate Cox regression analysis.

Results

Cross-platform dataset-based two stable GC stem cell subtypes, namely low stem cell enrichment (SCE_L) and high stem cell enrichment (SCE_H), were prudently identified. Gene set enrichment analysis revealed that the classical oncogenic pathways, immune-related pathways, and regulation of stem cell division were active in SCE_H; ferroptosis, NK cell activation, and post-mutation repair pathways were active in SCE_L. GC stem cell subtypes could accurately predict clinical outcomes in patients, tumor microenvironment cell-infiltration characteristics, somatic mutation landscape, and potential responses to immunotherapy, targeted therapy, and chemotherapy. Additionally, a CSC typing-related RS model was established; it was strongly independent and could accurately predict the patient’s overall survival.

Conclusions

This study demonstrated the complex oncogenic mechanisms underlying GC. The findings provide a basis and reference for the diagnosis and treatment of GC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-021-02633-x.

Efficient induction and sustenance of pluripotent stem cells from bovine somatic cells

Although derivation of naïve bovine embryonic stem cells is unachieved, the possibility for generation of bovine induced pluripotent stem cells (biPSCs) has been generally reported. However, attempts to sustain biPSCs by promoting self-renewal have not been successful. Methods established for maintaining murine and human induced pluripotent stem cells (iPSCs) do not support self-renewal of iPSCs for any bovid species. In this study, we examined methods to enhance complete reprogramming and concurrently investigated signaling relevant to pluripotency of the bovine blastocyst inner cell mass (ICM). First, we identified that forced expression of SV40 large T antigen together with the reprogramming genes (OCT4, SOX2, KLF4 and MYC) substantially enhanced the reprogramming efficacy of bovine fibroblasts to biPSCs. Second, we uncovered that TGFβ signaling is actively perturbed in the ICM. Inhibition of ALK4/5/7 to block TGFβ/activin/nodal signaling together with GSK3β and MEK1/2 supported robust in vitro self-renewal of naïve biPSCs with unvarying colony morphology, steady expansion, expected pluripotency gene expression and committed differentiation plasticity. Core similarities between biPSCs and stem cells of the 16-cell-stage bovine embryo indicated a stable ground state of pluripotency; this allowed us to reliably gain predictive understanding of signaling in bovine pluripotency using systems biology approaches. Beyond defining a high-fidelity platform for advancing biPSC-based biotechnologies that have not been previously practicable, these findings also represent a significant step towards understanding corollaries and divergent aspects of bovine pluripotency.

This article has an associated First Person interview with the joint first authors of the paper.

Summary: Pluripotency reprogramming by overcoming the stable epigenome of bovine cells, and uncovering precise early embryo self-renewal mechanisms enables sustenance and expansion of authentic induced pluripotent stem cells in vitro.

Integrative Analysis to Identify Genes Associated with Stemness and Immune Infiltration in Glioblastoma

It is imperative to identify the mechanisms that confer stemness to the cancer cells for more effective targeting. Moreover, there are not many studies on the link between stemness characteristics and the immune response in tumours. Therefore, in the current study involving GBM, we started with the study of BIRC5 (one of the rare genes differentially expressed in normal and cancer cells) and CXCR4 (gene involved in the survival and proliferation of CSCs). Together, these genes have not been systematically explored. We used a set of 27 promoter methylated regions in GBM. Our analysis showed that four genes corresponding to these regions, namely EOMES, BDNF, HLA-A, and PECAM1, were involved with BIRC5 and CXCR4. Interestingly, we found EOMES to be very significantly involved in stemness and immunology and it was positively correlated to CXCR4. Additionally, BDNF, which was significant in methylation, was negatively correlated to BIRC5.

Quantification of Age-Related Decline in Transcriptional Homeostasis

Age-dependent dysregulation of transcription regulatory machinery triggers modulations in the gene expression levels leading to the decline in cellular fitness. Tracking of these transcripts along the temporal axis in multiple species revealed a spectrum of evolutionarily conserved pathways, such as electron transport chain, translation regulation, DNA repair, etc. Recent shreds of evidence suggest that aging deteriorates the transcription machinery itself, indicating the hidden complexity of the aging transcriptomes. This reinforces the need for devising novel computational methods to view aging through the lens of transcriptomics. Here, we present Homeostatic Divergence Score (HDS) to quantify the extent of messenger RNA (mRNA) homeostasis by assessing the balance between spliced and unspliced mRNA repertoire in single cells. We validated its utility in two independent aging datasets, and identified sets of genes undergoing age-related breakdown of transcriptional homeostasis. Moreover, testing of our method on a subpopulation of human embryonic stem cells revealed a set of differentially processed transcripts segregating these subpopulations. Our preliminary analyses in this direction suggest that mRNA processing level information offered by single-cell RNA sequencing (scRNA-seq) data is a superior determinant of chronological age as compared to transcriptional noise.

Disruption of RING and PHD Domains of TRIM28 Evokes Differentiation in Human iPSCs

TRIM28, a multi-domain protein, is crucial in the development of mouse embryos and the maintenance of embryonic stem cells’ (ESC) self-renewal potential. As the epigenetic factor modulating chromatin structure, TRIM28 regulates the expression of numerous genes and is associated with progression and poor prognosis in many types of cancer. Because of many similarities between highly dedifferentiated cancer cells and normal pluripotent stem cells, we applied human induced pluripotent stem cells (hiPSC) as a model for stemness studies. For the first time in hiPSC, we analyzed the function of individual TRIM28 domains. Here we demonstrate the essential role of a really interesting new gene (RING) domain and plant homeodomain (PHD) in regulating pluripotency maintenance and self-renewal capacity of hiPSC. Our data indicate that mutation within the RING or PHD domain leads to the loss of stem cell phenotypes and downregulation of the FGF signaling. Moreover, impairment of RING or PHD domain results in decreased proliferation and impedes embryoid body formation. In opposition to previous data indicating the impact of phosphorylation on TRIM28 function, our data suggest that TRIM28 phosphorylation does not significantly affect the pluripotency and self-renewal maintenance of hiPSC. Of note, iPSC with disrupted RING and PHD functions display downregulation of genes associated with tumor metastasis, which are considered important targets in cancer treatment. Our data suggest the potential use of RING and PHD domains of TRIM28 as targets in cancer therapy.