Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium

X-chromosome inactivation in human iPSCs provides insight into X-regulated gene expression in autosomes

BACKGROUND

Variation in X chromosome inactivation (XCI) in human-induced pluripotent stem cells (hiPSCs) can impact their ability to model biological sex biases. The gene-wise landscape of X chromosome gene dosage remains unresolved in female hiPSCs. To characterize patterns of de-repression and escape from inactivation, we performed a systematic survey of allele specific expression in 165 female hiPSC lines.

RESULTS

XCI erosion is non-random and primarily affects genes that escape XCI in human tissues. Individual genes and cell lines vary in the frequency and degree of de-repression. Bi-allelic expression increases gradually after modest decrease of XIST in cultures, whose loss is commonly used to mark lines with eroded XCI. We identify three clusters of female lines at different stages of XCI. Increased XCI erosion amplifies female-biased expression at hypomethylated sites and regions normally occupied by repressive histone marks, lowering male-biased differences in the X chromosome. In autosomes, erosion modifies sex differences in a dose-dependent way. Male-biased genes are enriched for hypermethylated regions, and de-repression of XIST-bound autosomal genes in female lines attenuates normal male-biased gene expression in eroded lines. XCI erosion can compensate for a dominant loss of function effect in several disease genes.

CONCLUSIONS

We present a comprehensive view of X chromosome gene dosage in hiPSCs and implicate a direct mechanism for XCI erosion in regulating autosomal gene expression in trans. The uncommon and variable reactivation of X chromosome genes in female hiPSCs can provide insight into X chromosome's role in regulating gene expression and sex differences in humans.

Sex-biased gene expression during neural differentiation of human embryonic stem cells

Sex differences in the developing human brain are primarily attributed to hormonal influence. Recently however, genetic differences and their impact on the developing nervous system have attracted increased attention. To understand genetically driven sexual dimorphisms in neurodevelopment, we investigated genome-wide gene expression in an in vitro differentiation model of male and female human embryonic stem cell lines (hESC), independent of the effects of human sex hormones. Four male and four female-derived hESC lines were differentiated into a population of mixed neurons over 37 days. Differential gene expression and gene set enrichment analyses were conducted on bulk RNA sequencing data. While similar differentiation tendencies in all cell lines demonstrated the robustness and reproducibility of our differentiation protocol, we found sex-biased gene expression already in undifferentiated ESCs at day 0, but most profoundly after 37 days of differentiation. Male and female cell lines exhibited sex-biased expression of genes involved in neurodevelopment, suggesting that sex influences the differentiation trajectory. Interestingly, the highest contribution to sex differences was found to arise from the male transcriptome, involving both Y chromosome and autosomal genes. We propose 13 sex-biased candidate genes (10 upregulated in male cell lines and 3 in female lines) that are likely to affect neuronal development. Additionally, we confirmed gene dosage compensation of X/Y homologs escaping X chromosome inactivation through their Y homologs and identified a significant overexpression of the Y-linked demethylase UTY and KDM5D in male hESC during neuron development, confirming previous results in neural stem cells. Our results suggest that genetic sex differences affect neuronal differentiation trajectories, which could ultimately contribute to sex biases during human brain development.

Evidence of a pan-tissue decline in stemness during human aging

Despite their biological importance, the role of stem cells in human aging remains to be elucidated. In this work, we applied a machine learning methodology to GTEx transcriptome data and assigned stemness scores to 17,382 healthy samples from 30 human tissues aged between 20 and 79 years. We found that ~60% of the studied tissues exhibit a significant negative correlation between the subject's age and stemness score. The only significant exception was the uterus, where we observed an increased stemness with age. Moreover, we observed that stemness is positively correlated with cell proliferation and negatively correlated with cellular senescence. Finally, we also observed a trend that hematopoietic stem cells derived from older individuals might have higher stemness scores. In conclusion, we assigned stemness scores to human samples and show evidence of a pan-tissue loss of stemness during human aging, which adds weight to the idea that stem cell deterioration may contribute to human aging.

Cell specification and functional interactions in the pig blastocyst inferred from single-cell transcriptomics and uterine fluids proteomics

The embryonic development of the pig comprises a long in utero pre- and peri-implantation development, which dramatically differs from mice and humans. During this peri-implantation period, a complex series of paracrine signals establishes an intimate dialogue between the embryo and the uterus. To better understand the biology of the pig blastocyst during this period, we generated a large dataset of single-cell RNAseq from early and hatched blastocysts, spheroid and ovoid conceptus and proteomic datasets from corresponding uterine fluids. Our results confirm the molecular specificity and functionality of the three main cell populations. We also discovered two previously unknown subpopulations of the trophectoderm, one characterised by the expression of LRP2, which could represent progenitor cells, and the other, expressing pro-apoptotic markers, which could correspond to the Rauber's layer. Our work provides new insights into the biology of these populations, their reciprocal functional interactions, and the molecular dialogue with the maternal uterine environment.

Proteogenomic characterization of primary colorectal cancer and metastatic progression identifies proteome-based subtypes and signatures

Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we performed multiomics analyses of primary CRC and liver metastases. Genomic alterations, such as structural variants or copy number alterations, were enriched in oncogenes and tumor suppressor genes and increased in metastases. Unsupervised mass spectrometry-based proteomics of 135 primary and 123 metastatic CRCs uncovered distinct proteomic subtypes, three each for primary and metastatic CRCs, respectively. Integrated analyses revealed that hypoxia, stemness, and immune signatures characterize these 6 subtypes. Hypoxic CRC harbors high epithelial-to-mesenchymal transition features and metabolic adaptation. CRC with a stemness signature shows high oncogenic pathway activation and alternative telomere lengthening (ALT) phenotype, especially in metastatic lesions. Tumor microenvironment analysis shows immune evasion via modulation of major histocompatibility complex (MHC) class I/II and antigen processing pathways. This study characterizes both primary and metastatic CRCs and provides a large proteogenomics dataset of metastatic progression.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Identification of Novel Stemness-based Subtypes and Construction of a Prognostic Risk Model for Patients with Lung Squamous Cell Carcinoma

BACKGROUND

Although cancer stem cells (CSCs) contribute to tumorigenesis, progression, and drug resistance, stemness-based classification and prognostic signatures of lung squamous cell carcinoma (LUSC) remain unclarified. This study attempted to identify stemness-based subtypes and develop a prognostic risk model for LUSC.

METHODS

Based on RNA-seq data from The Cancer Genome Atlas (TCGA), Gene-Expression Omnibus (GEO) and Progenitor Cell Biology Consortium (PCBC), mRNA expression-based stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR) algorithm. A weighted gene coexpression network (WGCNA) was employed to identify stemness subtypes. Differences in mutation, clinical characteristics, immune cell infiltration, and antitumor therapy responses were determined. We constructed a prognostic risk model, followed by validations in GEO cohort, pan-cancer and immunotherapy datasets.

RESULTS

LUSC patients with subtype C2 had a better prognosis, manifested by higher mRNAsi, higher tumor protein 53 (TP53) and Titin (TTN) mutation frequencies, lower immune scores and decreased immune checkpoints. Patients with subtype C2 were more sensitive to Imatinib, Pyrimethamine, and Paclitaxel therapy, whereas those with subtype C1 were more sensitive to Sunitinib, Saracatinib, and Dasatinib. Moreover, we constructed stemness-based signatures using seven genes (BMI1, CCDC51, CTNS, EIF1AX, FAM43A, THBD, and TRIM68) and found high-risk patients had a poorer prognosis in the TCGA cohort. Similar results were found in the GEO cohort. We verified the good performance of risk scores in prognosis prediction and therapy responses.

CONCLUSION

The stemness-based subtypes shed novel insights into the potential roles of LUSC-stemness in tumor heterogeneity, and our prognostic signatures offer a promising tool for prognosis prediction and guide therapeutic decisions in LUSC.

Machine learning-based identification of lower grade glioma stemness subtypes discriminates patient prognosis and drug response

Glioma stem cells (GSCs) remodel their tumor microenvironment to sustain a supportive niche. Identification and stratification of stemness related characteristics in patients with glioma might aid in the diagnosis and treatment of the disease. In this study, we calculated the mRNA stemness index in bulk and single-cell RNA-sequencing datasets using machine learning methods and investigated the correlation between stemness and clinicopathological characteristics. A glioma stemness-associated score (GSScore) was constructed using multivariate Cox regression analysis. We also generated a GSC cell line derived from a patient diagnosed with glioma and used glioma cell lines to validate the performance of the GSScore in predicting chemotherapeutic responses. Differentially expressed genes (DEGs) between GSCs with high and low GSScores were used to cluster lower-grade glioma (LGG) samples into three stemness subtypes. Differences in clinicopathological characteristics, including survival, copy number variations, mutations, tumor microenvironment, and immune and chemotherapeutic responses, among the three LGG stemness-associated subtypes were identified. Using machine learning methods, we further identified genes as subtype predictors and validated their performance using the CGGA datasets. In the current study, we identified a GSScore that correlated with LGG chemotherapeutic response. Through the score, we also identified a novel classification of the LGG subtype and associated subtype predictors, which might facilitate the development of precision therapy.

Spatially resolved transcriptomic profiles reveal unique defining molecular features of infiltrative 5ALA-metabolizing cells associated with glioblastoma recurrence

BACKGROUND

Spatiotemporal heterogeneity originating from genomic and transcriptional variation was found to contribute to subtype switching in isocitrate dehydrogenase-1 wild-type glioblastoma (GBM) prior to and upon recurrence. Fluorescence-guided neurosurgical resection utilizing 5-aminolevulinic acid (5ALA) enables intraoperative visualization of infiltrative tumors outside the magnetic resonance imaging contrast-enhanced regions. The cell population and functional status of tumor responsible for enhancing 5ALA-metabolism to fluorescence-active PpIX remain elusive. The close spatial proximity of 5ALA-metabolizing (5ALA +) cells to residual disease remaining post-surgery renders 5ALA + biology an early a priori proxy of GBM recurrence, which is poorly understood.

METHODS

We performed spatially resolved bulk RNA profiling (SPRP) analysis of unsorted Core, Rim, Invasive margin tissue, and FACS-isolated 5ALA + /5ALA - cells from the invasive margin across IDH-wt GBM patients (N = 10) coupled with histological, radiographic, and two-photon excitation fluorescence microscopic analyses. Deconvolution of SPRP followed by functional analyses was performed using CIBEROSRTx and UCell enrichment algorithms, respectively. We further investigated the spatial architecture of 5ALA + enriched regions by analyzing spatial transcriptomics from an independent IDH-wt GBM cohort (N = 16). Lastly, we performed survival analysis using Cox Proportinal-Hazards model on large GBM cohorts.

RESULTS

SPRP analysis integrated with single-cell and spatial transcriptomics uncovered that the GBM molecular subtype heterogeneity is likely to manifest regionally in a cell-type-specific manner. Infiltrative 5ALA + cell population(s) harboring transcriptionally concordant GBM and myeloid cells with mesenchymal subtype, -active wound response, and glycolytic metabolic signature, was shown to reside within the invasive margin spatially distinct from the tumor core. The spatial co-localization of the infiltrating MES GBM and myeloid cells within the 5ALA + region indicates PpIX fluorescence can effectively be utilized to resect the immune reactive zone beyond the tumor core. Finally, 5ALA + gene signatures were associated with poor survival and recurrence in GBM, signifying that the transition from primary to recurrent GBM is not discrete but rather a continuum whereby primary infiltrative 5ALA + remnant tumor cells more closely resemble the eventual recurrent GBM.

CONCLUSIONS

Elucidating the unique molecular and cellular features of the 5ALA + population within tumor invasive margin opens up unique possibilities to develop more effective treatments to delay or block GBM recurrence, and warrants commencement of such treatments as early as possible post-surgical resection of the primary neoplasm.

Identification of Pyroptosis-Relevant Signature in Tumor Immune Microenvironment and Prognosis in Skin Cutaneous Melanoma Using Network Analysis

Background

Pyroptosis is closely related to the programmed death of cancer cells as well as the tumor immune microenvironment (TIME) via the host-tumor crosstalk. However, the role of pyroptosis-related genes as prognosis and TIME-related biomarkers in skin cutaneous melanoma (SKCM) patients remains unknown.

Methods

We evaluated the expression profiles, copy number variations, and somatic mutations (CNVs) of 27 genes obtained from MSigDB database regulating pyroptosis among TCGA-SKCM patients. Thereafter, we conducted single-sample gene set enrichment analysis (ssGSEA) for evaluating pyroptosis-associated expression patterns among cases and for exploring the associations with clinicopathological factors and prognostic outcome. In addition, a prognostic pyroptosis-related signature (PPRS) model was constructed by performing Cox regression, weighted gene coexpression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis to score SKCM patients. On the other hand, we plotted the ROC and survival curves for model evaluation and verified the robustness of the model through external test sets (GSE22153, GSE54467, and GSE65904). Meanwhile, we examined the relations of clinical characteristics, oncogene mutations, biological processes (BPs), tumor stemness, immune infiltration degrees, immune checkpoints (ICs), and treatment response with PPRS via multiple methods, including immunophenoscore (IPS) analysis, gene set variation analysis (GSVA), ESTIMATE, and CIBERSORT. Finally, we constructed a nomogram incorporating PPRS and clinical characteristics to improve risk evaluation of SKCM.

Results

Many pyroptosis-regulated genes showed abnormal expression within SKCM. TP53, TP63, IL1B, IL18, IRF2, CASP5, CHMP4C, CHMP7, CASP1, and GSDME were detected with somatic mutations, among which, a majority displayed CNVs at high frequencies. Pyroptosis-associated profiles established based on pyroptosis-regulated genes showed markedly negative relation to low stage and superior prognostic outcome. Blue module was found to be highly positively correlated with pyroptosis. Later, this study established PPRS based on the expression of 8 PAGs (namely, GBP2, HPDL, FCGR2A, IFITM1, HAPLN3, CCL8, TRIM34, and GRIPAP1), which was highly associated with OS, oncogene mutations, tumor stemness, immune infiltration degrees, IC levels, treatment responses, and multiple biological processes (including cell cycle and immunoinflammatory response) in training and test set samples.

Conclusions

Based on our observations, analyzing modification patterns associated with pyroptosis among diverse cancer samples via PPRS is important, which can provide more insights into TIME infiltration features and facilitate immunotherapeutic development as well as prognosis prediction.

Distinct dosage compensations of ploidy-sensitive and -insensitive X chromosome genes during development and in diseases

The active X chromosome in mammals is upregulated to balance its dosage to autosomes during evolution. However, it is elusive why the known dosage compensation machinery showed uneven and small influence on X genes. Here, based on >20,000 transcriptomes, we identified two X gene groups (ploidy-sensitive [PSX] and ploidy-insensitive [PIX]), showing distinct but evolutionarily conserved dosage compensations (termed XAR). We demonstrated that XAR-PIX was downregulated whereas XAR-PSX upregulated at both RNA and protein levels across cancer types, in contrast with their trends during stem cell differentiation. XAR-PIX, but not XAR-PSX, was lower and correlated with autoantibodies and inflammation in patients of lupus, suggesting that insufficient dosage of PIX genes contribute to lupus pathogenesis. We further identified and experimentally validated two XAR regulators, TP53 and ATRX. Collectively, we provided insights into X dosage compensation in mammals and demonstrated different regulation of PSX and PIX and their pathophysiological roles in human diseases.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

A novel ganglioside-related risk signature can reveal the distinct immune landscape of neuroblastoma and predict the immunotherapeutic response

Introduction

Gangliosides play an essential role in cancer development and progression. However, the involvement of gangliosides in the prognosis and tumor microenvironment (TME) of neuroblastoma is not entirely understood.

Methods

Consensus clustering analysis was performed to identify ganglioside-mediated molecular subtypes. LASSO-Cox analysis was conducted to identify independent prognostic genes, and a novel risk signature was constructed. The risk signature was validated internally and externally. We further explored the independent prognosis value, immune landscape, drug susceptibility, and tumor dedifferentiation of the risk signature. The role of the signature gene B3GALT4 in neuroblastoma was explored in vitro.

Results

Seventeen ganglioside-related genes were differentially expressed between INSS stage 4 and other stages, and two ganglioside-related clusters with distinct prognoses were identified. A novel risk signature integrating ten ganglioside-related prognostic genes was established. Across the train set and external validation sets, the risk signature presented high predictive accuracy and discrimination. The risk signature was an independent prognostic factor and constructed a nomogram combining multiple clinical characteristics. In the high-score group, the deficiency in antigen processing and presenting machinery, lack of immune cell infiltration, and escaping NK cells contributed substantially to immune escape. The low-score group was more responsive to immune checkpoint blockade therapy, while the high-score group showed substantial sensitivity to multiple chemotherapeutic drugs. Besides, the risk score was significantly positively correlated with the stemness index and reduced considerably in all-trans retinoic acid-treated neuroblastoma cell lines, indicating high dedifferentiation in the high-score group. Additionally, neuroblastoma cells with downregulation of B3GALT4 present with increased proliferation, invasion, and metastasis abilities in vitro.

Conclusion

The novel ganglioside-related risk signature highlights the role of ganglioside in neuroblastoma prognosis and immune landscape and helps optimize chemotherapy and immunotherapy for neuroblastoma.

De-erosion of X chromosome dosage compensation by the editing of XIST regulatory regions restores the differentiation potential in hPSCs

Human pluripotent stem cells (hPSCs) regularly and irreversibly show the erosion of X chromosome inactivation (XCI) by long non-coding RNA (lncRNA) XIST silencing, causing challenges in various applications of female hPSCs. Here, we report reliable methods to reactivate XIST with monoallelic expression in female hPSCs. Surprisingly, we find that the editing of XIST regulatory regions by Cas9-mediated non-homologous end joining is sufficient for the reactivation of XIST by endogenous systems. Proliferated hPSCs with XIST reactivation show XCI from an eroded X chromosome, suggesting that hPSCs with normal dosage compensation might lead to a growth advantage. Furthermore, the use of targeting vectors, including the XIST regulatory region sequences and selection cassette, enables XIST reactivation in hPSCs with high efficiency. XIST-reactivated hPSCs can show the restoration of differentiation potential. Thus, our findings demonstrate that XIST re-expression is a beneficial method to maximize the use of female hPSCs in various applications, such as proper disease modeling.

Epigenetic biomarkers to track differentiation of pluripotent stem cells

Quality control of induced pluripotent stem cells remains a challenge. For validation of the pluripotent state, it is crucial to determine trilineage differentiation potential toward endoderm, mesoderm, and ectoderm. Here, we report GermLayerTracker, a combination of site-specific DNA methylation (DNAm) assays that serve as biomarker for early germ layer specification. CG dinucleotides (CpGs) were identified with characteristic DNAm at pluripotent state and after differentiation into endoderm, mesoderm, and ectoderm. Based on this, a pluripotency score was derived that tracks reprogramming and may indicate differentiation capacity, as well as lineage-specific scores to monitor either directed differentiation or self-organized multilineage differentiation in embryoid bodies. Furthermore, we established pyrosequencing assays for fast and cost-effective analysis. In the future, the GermLayerTracker could be used for quality control of pluripotent cells and to estimate lineage-specific commitment during initial differentiation events.

Methylation-based reclassification and risk stratification of skull-base chordomas

BACKGROUND

Skull-base chordomas are rare malignant bone cancers originating from the remnant of the notochord. Survival is variable, and clinical or molecular factors cannot reliably predict their outcomes. This study therefore identified epigenetic subtypes that defined new chordoma epigenetic profiles and their corresponding characteristics.

METHODS

Methylation profiles of 46 chordoma-resected neoplasms between 2008 and 2014, along with clinical information, were collected. K-means consensus clustering and principal component analysis were used to identify and validate the clusters. Single-sample gene set enrichment analysis, methylCIBERSORT algorithm, and copy number analysis were used to identify the characteristics of the clusters.

RESULTS

Unsupervised clustering analysis confirmed two clusters with a progression-free survival difference. Gene set enrichment analysis indicated that the early and late estrogen response pathways and the hypoxia pathway were activated whereas the inflammatory and interferon gamma responses were suppressed. Forty-six potential therapeutic targets corresponding to differentially methylated sites were identified from chordoma patients. Subgroups with a worse outcome were characterized by low immune cell infiltration, higher tumor purity, and higher stemness indices. Moreover, copy number amplifications mostly occurred in cluster 1 tumors and the high-risk group. Additionally, the presence of a CCNE1 deletion was exclusively found in the group of chordoma patients with better outcome, whereas RB1 and CDKN2A/2B deletions were mainly found in the group of chordoma patients with worse outcome.

CONCLUSIONS

Chordoma prognostic epigenetic subtypes were identified, and their corresponding characteristics were found to be variable.

Characterizing the Crosstalk of NCAPG with Tumor Microenvironment and Tumor Stemness in Stomach Adenocarcinoma

Background. Nonstructural maintenance of non-SMC condensin I complex subunit G (NCAPG) exerts critical effects on cancer progression. However, its biological roles in tumorigenesis and metastasis remain unclear. Thus, we aimed to assess the prognostic utility of NCAPG in stomach adenocarcinoma (STAD) and its potential as a tumor biomarker. Methods. Pan-cancer expression profile dataset from public databases and corresponding clinical information were extracted. Single-sample gene set enrichment analysis (ssGSEA) was performed for the evaluation of immune correlations pan-cancer. Subsequently, we focused on STAD and evaluated the methylation profiles, copy number variants (CNVs), and single nucleotide variants (SNVs). Immune features were analyzed between high and low NCAPG expression groups. Differential analysis was performed between high and low expression groups to identify differentially expressed genes (DEGs). Prognostic DEGs were screened by univariate analysis, and an NCAPG-based risk model was constructed based on the prognostic DEGs and LASSO analysis. Results. NCAPG expression in STAD was significantly and positively correlated with four immune checkpoints, namely, CTLA4, PDCD1, LAG3, and CD276, but was negatively correlated with the infiltration of most immune cells. High and low NCAPG expression groups had differential overall survival, tumor mutation burden, and differential enrichment of therapeutic-related pathways. An immune risk scoring model related to NCAPG expression and immune score was constructed which showed a favorable performance in predicting STAD prognosis as well as predicting the response to immunotherapy. In addition, we found a higher mRNA stemness index (mRNAsi) in the high-risk group and a positive correlation between NCAPG expression and mRNAsi. Conclusion. NCAPG was suggested to be involved in the regulation of tumor microenvironment in STAD. High NCAPG expression was related to high tumor stemness and good prognosis. The immune risk model had a potential to predict STAD prognosis and help directing therapeutic treatment.

Identification of Prognostic Markers and Potential Therapeutic Targets in Gastric Adenocarcinoma by Machine Learning Based on mRNAsi Index

Background

Cancer stem cells (CSCs), characterized by self-renewal and therapeutic resistance, play important roles in stomach adenocarcinoma (STAD). However, the molecular mechanism of STAD stem cells is still unclear. In this study, our purpose is to explore the expression of stem cell-related genes in STAD.

Methods

The stemness index based on mRNA expression (mRNAsi) was used to analyze STAD cases in The Cancer Genome Atlas (TCGA). Firstly, mRNAsi was used and analyzed by differential expression, survival analysis, clinical stage, and gender in STAD. Then, weighted gene coexpression network analysis (WGCNA) was used to discover the fascinating modules and key genes. Enrichment analysis was carried out to annotate the functions and pathways of key genes. The gene expression comprehensive database (GEO) in STAD was used to verify the expression levels of key genes in all cancers. Protein-protein interaction networks is used to determine the relationships between key genes.

Results

The mRNAsi was obviously upregulated in tumor cases. With the increase of tumor stage and T stage, the mRNAsi score decreased, and the overall survival rate of high score group patients was better. According to the degree of association with mRNAsi, different modules and key genes were screened out. A total of 6,740 differential genes were found, of which 1,147 genes were downregulated and 5,593 genes were upregulated. 19 key genes (BUB1, BUB1B, KIF14, NCAPH, RACGAP, KIF15, CENPF, TPX2, RAD54L, KIF18B, KIF4A, TTK, SGO2, PLK4, ARHGAP11A, XRCC2, Clorf112, NCAPG, and ORC6) were screened due to significant upregulation in STAD. And they had been proven that enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Among them, 9 genes have been extensively associated to OS, and 3 genes had been associated to receive chemotherapy resistance. PPI protein network suggests that there is a sturdy correlation between these key genes.

Conclusion

A total of 19 key genes were found to play an essential position in retaining the traits of STAD stem cells. These genes can be used to evaluate the prognosis of STAD patients or become specific therapeutic targets.

Stemness Analysis Uncovers That The Peroxisome Proliferator-Activated Receptor Signaling Pathway Can Mediate Fatty Acid Homeostasis In Sorafenib-Resistant Hepatocellular Carcinoma Cells

Hepatocellular carcinoma (HCC) stem cells are regarded as an important part of individualized HCC treatment and sorafenib resistance. However, there is lacking systematic assessment of stem-like indices and associations with a response of sorafenib in HCC. Our study thus aimed to evaluate the status of tumor dedifferentiation for HCC and further identify the regulatory mechanisms under the condition of resistance to sorafenib. Datasets of HCC, including messenger RNAs (mRNAs) expression, somatic mutation, and clinical information were collected. The mRNA expression-based stemness index (mRNAsi), which can represent degrees of dedifferentiation of HCC samples, was calculated to predict drug response of sorafenib therapy and prognosis. Next, unsupervised cluster analysis was conducted to distinguish mRNAsi-based subgroups, and gene/geneset functional enrichment analysis was employed to identify key sorafenib resistance-related pathways. In addition, we analyzed and confirmed the regulation of key genes discovered in this study by combining other omics data. Finally, Luciferase reporter assays were performed to validate their regulation. Our study demonstrated that the stemness index obtained from transcriptomic is a promising biomarker to predict the response of sorafenib therapy and the prognosis in HCC. We revealed the peroxisome proliferator-activated receptor signaling pathway (the PPAR signaling pathway), related to fatty acid biosynthesis, that was a potential sorafenib resistance pathway that had not been reported before. By analyzing the core regulatory genes of the PPAR signaling pathway, we identified four candidate target genes, retinoid X receptor beta (RXRB), nuclear receptor subfamily 1 group H member 3 (NR1H3), cytochrome P450 family 8 subfamily B member 1 (CYP8B1) and stearoyl-CoA desaturase (SCD), as a signature to distinguish the response of sorafenib. We proposed and validated that the RXRB and NR1H3 could directly regulate NR1H3 and SCD, respectively. Our results suggest that the combined use of SCD inhibitors and sorafenib may be a promising therapeutic approach.

Stemness Correlates Inversely with MHC Class I Expression in Pediatric Small Round Blue Cell Tumors

Recently, immunotherapeutic approaches have become a feasible option for a subset of pediatric cancer patients. Low MHC class I expression hampers the use of immunotherapies relying on antigen presentation. A well-established stemness score (mRNAsi) was determined using the bulk transcriptomes of 1134 pediatric small round blue cell tumors. Interestingly, MHC class I gene expression (HLA-A/-B/-C) was correlated negatively with mRNAsi throughout all diagnostic entities: neuroblastomas (NB) (n = 88, r = −0.41, p < 0.001), the Ewing’s sarcoma family of tumors (ESFT) (n = 117, r = −0.46, p < 0.001), rhabdomyosarcomas (RMS) (n = 158, r = −0.5, p < 0.001), Wilms tumors (WT) (n = 224, r = −0.39, p < 0.001), and central nervous system-primitive neuroectodermal tumors CNS-PNET (r = −0.49, p < 0.001), with the exception of medulloblastoma (MB) (n = 76, r = −0.24, p = 0.06). The negative correlation of MHC class I and mRNAsi was independent of clinical features in NB, RMS, and WT. In NB and WT, increased MHC class I was correlated negatively with tumor stage. RMS patients with a high expression of MHC class I and abundant CD8 T cells showed a prolonged overall survival (n = 148, p = 0.004). Possibly, low MHC class I expression and stemness in pediatric tumors are remnants of prenatal tumorigenesis from multipotent precursor cells. Further studies are needed to assess the usefulness of stemness and MHC class I as predictive markers.

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.

KRAB-ZFPs and cancer stem cells identity

Studies on carcinogenesis continue to provide new information about different disease-related processes. Among others, much research has focused on the involvement of cancer stem cells (CSCs) in tumor initiation and progression. Studying the similarities and differences between CSCs and physiological stem cells (SCs) allows for a better understanding of cancer biology. Recently, it was shown that stem cell identity is partially governed by the Krϋppel-associated box domain zinc finger proteins (KRAB-ZFPs), the biggest family of transcription regulators. Several KRAB-ZFP factors exert a known effect in tumor cells, acting as tumor suppressor genes (TSGs) or oncogenes, yet their role in CSCs is still poorly characterized. Here, we review recent studies regarding the influence of KRAB-ZFPs and their cofactor protein TRIM28 on CSCs phenotype, stemness features, migration and invasion potential, metastasis, and expression of parental markers.

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients

Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance of HCC. This study aimed to propose a novel CSCs-related cluster of HCC to predict patients' response to immunotherapy. Based on RNA-seq datasets from The Cancer Genome Atlas (TCGA) and Progenitor Cell Biology Consortium (PCBC), one-class logistic regression (OCLR) algorithm was applied to compute the stemness index (mRNAsi) of HCC patients. Unsupervised consensus clustering was performed to categorize HCC patients into two stemness subtypes which further proved to be a predictor of tumor immune microenvironment (TIME) status, immunogenomic expressions and sensitivity to neoadjuvant therapies. Finally, four machine learning algorithms (LASSO, RF, SVM-RFE and XGboost) were applied to distinguish different stemness subtypes. Thus, a five-hub-gene based classifier was constructed in TCGA and ICGC HCC datasets to predict patients' stemness subtype in a more convenient and applicable way, and this novel stemness-based classification system could facilitate the prognostic prediction and guide clinical strategies of immunotherapy and targeted therapy in HCC.

Analysis of Stemness and Prognosis of Subtypes in Breast Cancer Using the Transcriptome Sequencing Data

The stem characteristics of tumor cells have been proposed in theory very early, and we can use the signature of gene expression to speculate the stemness of tumor cells. However, systematic studies on the stemness of breast cancer as well as breast cancer subtypes, and the relationship between stemness and metastasis and prognosis, are still lacking. In the present research, using the transcriptome data of patients with breast cancer in the TCGA database, a stemness prediction model was utilized to derive the stemness of the patients’ tumors. We compared the stemness values among different subtypes and the differences with metastasis. COX regression was employed to evaluate the correlation between stemness value as well as prognosis. Using the Lasso-penalized Cox regression machine learning model, we obtained the gene signature of the basal subtype that is related to stemness and can also predict the prognosis of the patient. Patients can be stratified into two groups of high and low stemness, corresponding to good and poor prognosis. Based on further prediction of tumor infiltration by CIBERSORT and prediction of drug response by a connectivity map, we found that the difference in stemness between these two groups is associated with the activation of tumor-killing immune cells and drug response. Our findings can promote the understanding and research of subtypes of basal breast cancer and provide corresponding molecular markers for clinical detection and therapy.

Inherent genomic properties underlie the epigenomic heterogeneity of human induced pluripotent stem cells

Human induced pluripotent stem cells (hiPSCs) show variable differentiation potential due to their epigenomic heterogeneity, whose extent/attributes remain unclear, except for well-studied elements/chromosomes such as imprints and the X chromosomes. Here, we show that seven hiPSC lines with variable germline potential exhibit substantial epigenomic heterogeneity, despite their uniform transcriptomes. Nearly a quarter of autosomal regions bear potentially differential chromatin modifications, with promoters/CpG islands for H3K27me3/H2AK119ub1 and evolutionarily young retrotransposons for H3K4me3. We identify 145 large autosomal blocks (≥100 kb) with differential H3K9me3 enrichment, many of which are lamina-associated domains (LADs) in somatic but not in embryonic stem cells. A majority of these epigenomic heterogeneities are independent of genetic variations. We identify an X chromosome state with chromosome-wide H3K9me3 that stably prevents X chromosome erosion. Importantly, the germline potential of female hiPSCs correlates with X chromosome inactivation. We propose that inherent genomic properties, including CpG density, transposons, and LADs, engender epigenomic heterogeneity in hiPSCs.

Longitudinal Analysis of Human Pancreatic Adenocarcinoma Development Reveals Transient Gene Expression Signatures

Previous transcriptome studies of human pancreatic ductal adenocarcinoma (PDAC) compare non-cancerous pancreatic intraepithelial neoplasias (PanIN) with late-stage PDAC obtained from different patients, thus have limited ability to discern network dynamics that contribute to the disease progression. We demonstrated previously that the 10-22 cell line, an induced pluripotent stem cell-like line reprogrammed from late-stage human PDAC cells, recapitulated the progression from PanINs to PDAC upon transplantation into NOD/LtSz-scid/IL2R-gamma^null mice. Herein, we investigated the transition from precursor to PDAC using the isogenic model. We analyzed transcriptomes of genetically tagged 10-22 cells progressing from PanINs to PDAC in mice and validated the results using The Cancer Genome Atlas PDAC dataset, human clinical PanIN and PDAC tissues, and a well-established murine PDAC model. We functionally studied candidate proteins using human normal (H6C7) and cancerous (Miapaca2, Aspc1) pancreatic ductal epithelial cell lines. 10-22 cell-derived PDAC displayed the molecular signature of clinical human PDAC. Expression changes of many genes were transient during PDAC progression. Pathways for extracellular vesicle transport and neuronal cell differentiation were derepressed in the progression of PanINs to PDAC. HMG-box transcription factor 1 (HBP1) and BTB domain and CNC homolog 1 (BACH1) were implicated in regulating dynamically expressed genes during PDAC progression, and their expressions inversely correlated with PDAC patients' prognosis. Ectopic expression of HBP1 increased proliferation and migration of normal and cancerous pancreatic cells, indicating that HBP1 may confer the cell dissemination capacity in early PDAC progression. This unique longitudinal analysis provides insights into networks underlying human PDAC progression and pathogenesis. IMPLICATIONS: Manipulation of HBP1, BACH1, and RUN3 networks during PDAC progression can be harnessed to develop new targets for treating PDAC.

De novo DNA methyltransferases DNMT3A and DNMT3B are essential for XIST silencing for erosion of dosage compensation in pluripotent stem cells

Human pluripotent stem cells (hPSCs) have proven to be valuable tools for both drug discovery and the development of cell-based therapies. However, the long non-coding RNA XIST, which is essential for the establishment and maintenance of X chromosome inactivation, is repressed during culture, thereby causing erosion of dosage compensation in female hPSCs. Here, we report that the de novo DNA methyltransferases DNMT3A/3B are necessary for XIST repression in female hPSCs. We found that the deletion of both genes, but not the individual genes, inhibited XIST silencing, maintained the heterochromatin mark of H3K27me3, and did not cause global overdosage in X-linked genes. Meanwhile, DNMT3A/3B deletion after XIST repression failed to restore X chromosome inactivation. Our findings revealed that de novo DNA methyltransferases are primary factors responsible for initiating erosion of dosage compensation in female hPSCs, and XIST silencing is stably maintained in a de novo DNA-methylation-independent manner.

Systematic assessment of variability in the proteome of iPSC derivatives

The use of induced pluripotent stem cells (iPSC) to model human complex diseases is gaining popularity as it allows investigation of human cells that are otherwise sparsely available. However, due to its laborious and cost intensive nature, iPSC research is often plagued by limited sample size and putative large variability between clones, decreasing statistical power for detecting experimental effects. Here, we investigate the source and magnitude of variability in the proteome of parallel differentiated astrocytes using mass spectrometry. We compare three possible sources of variability: inter-donor variability, inter- and intra-clonal variability, at different stages of maturation. We show that the interclonal variability is significantly smaller than the inter-donor variability, and that including more donors has a much larger influence on statistical power than adding more clones per donor. Our results provide insight into the sources of variability at protein level between iPSC samples derived in parallel and will aid in optimizing iPSC studies.

Alternative splicing associated with cancer stemness in kidney renal clear cell carcinoma

Backgroud

Cancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options.

Methods

The corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alternative splicing event between high- and low- stemness groups. Univariate Cox and multivariable logistic regression analysisw as carried out to detect the prognosis-related SASEs respectively. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of our model.

Results

Here, we constructed a KIRC-specific stemness prediction model with an AUC of 0.968,and to provide a user-friendly interface of our model for KIRC stemness analysis, we have developed KIRC Stemness Calculator and Visualization (KSCV), hosted on the Shiny server, can most easily be accessed via web browser and the url https://jiang-lab.shinyapps.io/kscv/. When applied to 605 KIRC patients, our stemness indices had a higher correlation with the gender, smoking history and metastasis of the patients than the previous stemness indices, and revealed intratumor heterogeneity at the stemness level. We identified 77 novel SASEs by dividing patients into high- and low- stemness groups with significantly different outcome and they had significant correlations with expression of 17 experimentally validated splicing factors. Both univariate and multivariate survival analysis demonstrated that SASEs closely correlated with the overall survival of patients.

Conclusions

Basing on the stemness indices, we found that not only immune infiltration but also alternative splicing events showed significant different at the stemness level. More importantly, we highlight the critical role of these differential alternative splicing events in poor prognosis, and we believe in the potential for their further translation into targets for immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08470-8.

The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma

Objectives

This study aimed to identify genes regulating cancer stemness of head and neck squamous cell carcinoma (HNSCC) and evaluate the ability of these genes to predict clinical outcomes.

Materials and Methods

The stemness index (mRNAsi) was obtained using a one-class logistic regression machine learning algorithm based on sequencing data of HNSCC patients. Stemness-related genes were identified by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis (LASSO). The coefficient of LASSO was applied to construct a diagnostic risk score model. The Cancer Genome Atlas database, the Gene Expression Omnibus database, Oncomine database and the Human Protein Atlas database were used to validate the expression of key genes. Interaction network analysis was performed using String database and DisNor database. The Connectivity Map database was used to screen potential compounds. The expressions of stemness-related genes were validated using quantitative real‐time polymerase chain reaction (qRT‐PCR).

Results

TTK, KIF14, KIF18A and DLGAP5 were identified. Stemness-related genes were upregulated in HNSCC samples. The risk score model had a significant predictive ability. CDK inhibitor was the top hit of potential compounds.

Conclusion

Stemness-related gene expression profiles may be a potential biomarker for HNSCC.

iPSC Preparation and Epigenetic Memory: Does the Tissue Origin Matter?

The production of induced pluripotent stem cells (iPSCs) represent a breakthrough in regenerative medicine, providing new opportunities for understanding basic molecular mechanisms of human development and molecular aspects of degenerative diseases. In contrast to human embryonic stem cells (ESCs), iPSCs do not raise any ethical concerns regarding the onset of human personhood. Still, they present some technical issues related to immune rejection after transplantation and potential tumorigenicity, indicating that more steps forward must be completed to use iPSCs as a viable tool for in vivo tissue regeneration. On the other hand, cell source origin may be pivotal to iPSC generation since residual epigenetic memory could influence the iPSC phenotype and transplantation outcome. In this paper, we first review the impact of reprogramming methods and the choice of the tissue of origin on the epigenetic memory of the iPSCs or their differentiated cells. Next, we describe the importance of induction methods to determine the reprogramming efficiency and avoid integration in the host genome that could alter gene expression. Finally, we compare the significance of the tissue of origin and the inter-individual genetic variation modification that has been lightly evaluated so far, but which significantly impacts reprogramming.

Contiguous erosion of the inactive X in human pluripotency concludes with global DNA hypomethylation

Female human pluripotent stem cells (hPSCs) routinely undergo inactive X (Xi) erosion. This progressive loss of key repressive features follows the loss of XIST expression, the long non-coding RNA driving X inactivation, and causes reactivation of silenced genes across the eroding X (Xe). To date, the sporadic and progressive nature of erosion has obscured its scale, dynamics, and key transition events. To address this problem, we perform an integrated analysis of DNA methylation (DNAme), chromatin accessibility, and gene expression across hundreds of hPSC samples. Differential DNAme orders female hPSCs across a trajectory from initiation to terminal Xi erosion. Our results identify a cis-regulatory element crucial for XIST expression, trace contiguously growing reactivated domains to a few euchromatic origins, and indicate that the late-stage Xe impairs DNAme genome-wide. Surprisingly, from this altered regulatory landscape emerge select features of naive pluripotency, suggesting that its link to X dosage may be partially conserved in human embryonic development.

Reactivation of the silenced X in human female iPSC/ESCs compromises their utility. Bansal et al. perform an integrated genomics analysis to reveal a prevalent X erosion trajectory that they validate in long-term culture. Starting with XIST loss, this trajectory indicates that reactivation may spread contiguously from escapees to silenced genes.

Running the full human developmental clock in interspecies chimeras using alternative human stem cells with expanded embryonic potential

Human pluripotent stem cells (hPSCs) can generate specialized cell lineages that have great potential for regenerative therapies and disease modeling. However, the developmental stage of the lineages generated from conventional hPSC cultures in vitro are embryonic in phenotype, and may not possess the cellular maturity necessary for corrective regenerative function in vivo in adult recipients. Here, we present the scientific evidence for how adult human tissues could generate human–animal interspecific chimeras to solve this problem. First, we review the phenotypes of the embryonic lineages differentiated from conventional hPSC in vitro and through organoid technologies and compare their functional relevance to the tissues generated during normal human in utero fetal and adult development. We hypothesize that the developmental incongruence of embryo-stage hPSC-differentiated cells transplanted into a recipient adult host niche is an important mechanism ultimately limiting their utility in cell therapies and adult disease modeling. We propose that this developmental obstacle can be overcome with optimized interspecies chimeras that permit the generation of adult-staged, patient-specific whole organs within animal hosts with human-compatible gestational time-frames. We suggest that achieving this goal may ultimately have to await the derivation of alternative, primitive totipotent-like stem cells with improved embryonic chimera capacities. We review the scientific challenges of deriving alternative human stem cell states with expanded embryonic potential, outline a path forward for conducting this emerging research with appropriate ethical and regulatory oversight, and defend the case of why current federal funding restrictions on this important category of biomedical research should be liberalized.

Sustained intrinsic WNT and BMP4 activation impairs hESC differentiation to definitive endoderm and drives the cells towards extra-embryonic mesoderm

We identified a human embryonic stem cell subline that fails to respond to the differentiation cues needed to obtain endoderm derivatives, differentiating instead into extra-embryonic mesoderm. RNA-sequencing analysis showed that the subline has hyperactivation of the WNT and BMP4 signalling. Modulation of these pathways with small molecules confirmed them as the cause of the differentiation impairment. While activation of WNT and BMP4 in control cells resulted in a loss of endoderm differentiation and induction of extra-embryonic mesoderm markers, inhibition of these pathways in the subline restored its ability to differentiate. Karyotyping and exome sequencing analysis did not identify any changes in the genome that could account for the pathway deregulation. These findings add to the increasing evidence that different responses of stem cell lines to differentiation protocols are based on genetic and epigenetic factors, inherent to the line or acquired during cell culture.

Proteogenomic and metabolomic characterization of human glioblastoma

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Epigenetic Age Acceleration of Stomach Adenocarcinoma Associated With Tumor Stemness Features, Immunoactivation, and Favorable Prognosis

Background: Abnormal DNA methylation (DNAm) age has been assumed to be an indicator for canceration and all-cause mortality. However, associations between DNAm age and molecular features of stomach adenocarcinoma (STAD), and its prognosis have not been systematically studied.

Method: We calculated the DNAm age of 591 STAD samples and 115 normal stomach samples from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) database using the Horvath’s clock model. Meanwhile, we utilized survival analysis to evaluate the prognostic value of DNAm age and epigenetic age acceleration shift. In addition, we performed weighted gene co-expression network analysis (WGCNA) to identify DNAm age-associated gene modules and pathways. Finally, the association between DNAm age and molecular features was performed by correlation analysis.

Results: DNA methylation age was significantly correlated with chronological age in normal gastric tissues (r = 0.85, p < 0.0001), but it was not associated with chronological age in STAD samples (r = 0.060, p = 0.2369). Compared with tumor adjacent normal tissue, the DNAm age of STAD tissues was significantly decreased. Meanwhile, chronological age in STAD samples was higher than its DNAm age. Both DNAm age and epigenetic acceleration shift were associated with the prognosis of STAD patients. By using correlation analysis, we also found that DNAm age was associated with immunoactivation and stemness in STAD samples.

Conclusion: In summary, epigenetic age acceleration of STAD was associated with tumor stemness, immunoactivation, and favorable prognosis.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells

BACKGROUND

The discovery that somatic cells can be reprogrammed to induced pluripotent stem cells (iPSCs) has provided a foundation for in vitro human disease modelling, drug development and population genetics studies. Gene expression plays a critical role in complex disease risk and therapeutic response. However, while the genetic background of reprogrammed cell lines has been shown to strongly influence gene expression, the effect has not been evaluated at the level of individual cells which would provide significant resolution. By integrating single cell RNA-sequencing (scRNA-seq) and population genetics, we apply a framework in which to evaluate cell type-specific effects of genetic variation on gene expression.

RESULTS

Here, we perform scRNA-seq on 64,018 fibroblasts from 79 donors and map expression quantitative trait loci (eQTLs) at the level of individual cell types. We demonstrate that the majority of eQTLs detected in fibroblasts are specific to an individual cell subtype. To address if the allelic effects on gene expression are maintained following cell reprogramming, we generate scRNA-seq data in 19,967 iPSCs from 31 reprogramed donor lines. We again identify highly cell type-specific eQTLs in iPSCs and show that the eQTLs in fibroblasts almost entirely disappear during reprogramming.

CONCLUSIONS

This work provides an atlas of how genetic variation influences gene expression across cell subtypes and provides evidence for patterns of genetic architecture that lead to cell type-specific eQTL effects.

Prognostic Gene Expression, Stemness and Immune Microenvironment in Pediatric Tumors

Simple Summary

Tumors in children and young adults are rare and diagnostically distinct from those occurring in older patients. They frequently arise from developing cells, resembling stem cells, which may explain some of the clinical and biologic differences observed. The aim of this retrospective transcriptome study was to investigate the prognostic landscape, immune tumor microenvironment (TME) and stemness in a cohort of 4068 transcriptomes of such tumors. We find that patients’ prognosis correlates with distinct gene expression patterns similar to adult tumor types. Stemness defined by a computational stemness score (mRNAsi) correlates with clinical and molecular parameters that is distinct for each tumor type. In Wilms tumors that recapitulate normal kidney development microscopically, stemness correlates with distinct patterns of immune cell infiltration by transcriptome analysis and by cell localization in tumor tissue.

Abstract

Pediatric tumors frequently arise from embryonal cells, often displaying a stem cell-like (“small round blue”) morphology in tissue sections. Because recently “stemness” has been associated with a poor immune response in tumors, we investigated the association of prognostic gene expression, stemness and the immune microenvironment systematically using transcriptomes of 4068 tumors occurring mostly at the pediatric and young adult age. While the prognostic landscape of gene expression (PRECOG) and infiltrating immune cell types (CIBERSORT) is similar to that of tumor entities occurring mainly in adults, the patterns are distinct for each diagnostic entity. A high stemness score (mRNAsi) correlates with clinical and morphologic subtype in Wilms tumors, neuroblastomas, synovial sarcomas, atypical teratoid rhabdoid tumors and germ cell tumors. In neuroblastomas, a high mRNAsi is associated with shortened overall survival. In Wilms tumors a high mRNAsi correlates with blastemal morphology, whereas tumors with predominant epithelial or stromal differentiation have a low mRNAsi and a high percentage of M2 type macrophages. This could be validated in Wilms tumor tissue (n = 78). Here, blastemal areas are low in M2 macrophage infiltrates, while nearby stromal differentiated areas contain abundant M2 macrophages, suggesting local microanatomic regulation of the immune response.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy

The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this "proteogenomics" approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy.

Functional in vivo and in vitro effects of 20q11.21 genetic aberrations on hPSC differentiation

Human pluripotent stem cells (hPSCs) have promising therapeutic applications due to their infinite capacity for self-renewal and pluripotency. Genomic stability is imperative for the clinical use of hPSCs; however, copy number variation (CNV), especially recurrent CNV at 20q11.21, may contribute genomic instability of hPSCs. Furthermore, the effects of CNVs in hPSCs at the whole-transcriptome scale are poorly understood. This study aimed to examine the functional in vivo and in vitro effects of frequently detected CNVs at 20q11.21 during early-stage differentiation of hPSCs. Comprehensive transcriptome profiling of abnormal hPSCs revealed that the differential gene expression patterns had a negative effect on differentiation potential. Transcriptional heterogeneity identified by single-cell RNA sequencing (scRNA-seq) of embryoid bodies from two different isogenic lines of hPSCs revealed alterations in differentiated cell distributions compared with that of normal cells. RNA-seq analysis of 22 teratomas identified several differentially expressed lineage-specific markers in hPSCs with CNVs, consistent with the histological results of the altered ecto/meso/endodermal ratio due to CNVs. Our results suggest that CNV amplification contributes to cell proliferation, apoptosis, and cell fate specification. This work shows the functional consequences of recurrent genetic abnormalities and thereby provides evidence to support the development of cell-based applications.

Copy number variant hotspots in Han Taiwanese population induced pluripotent stem cell lines - lessons from establishing the Taiwan human disease iPSC Consortium Bank

Background

The Taiwan Human Disease iPSC Service Consortium was established to accelerate Taiwan’s growing stem cell research initiatives and provide a platform for researchers interested in utilizing induced pluripotent stem cell (iPSC) technology. The consortium has generated and characterized 83 iPSC lines: 11 normal and 72 disease iPSC lines covering 21 different diseases, several of which are of high incidence in Taiwan. Whether there are any reprogramming-induced recurrent copy number variant (CNV) hotspots in iPSCs is still largely unknown.

Methods

We performed genome-wide copy number variant screening of 83 Han Taiwanese iPSC lines and compared them with 1093 control subjects using an Affymetrix genome-wide human SNP array.

Results

In the iPSCs, we identified ten specific CNV loci and seven “polymorphic” CNV regions that are associated with the reprogramming process. Additionally, we established several differentiation protocols for our iPSC lines. We demonstrated that our iPSC-derived cardiomyocytes respond to pharmacological agents and were successfully engrafted into the mouse myocardium demonstrating their potential application in cell therapy.

Conclusions

The CNV hotspots induced by cell reprogramming have successfully been identified in the current study. This finding may be used as a reference index for evaluating iPSC quality for future clinical applications. Our aim was to establish a national iPSC resource center generating iPSCs, made available to researchers, to benefit the stem cell community in Taiwan and throughout the world.

Population-scale proteome variation in human induced pluripotent stem cells

Human disease phenotypes are driven primarily by alterations in protein expression and/or function. To date, relatively little is known about the variability of the human proteome in populations and how this relates to variability in mRNA expression and to disease loci. Here, we present the first comprehensive proteomic analysis of human induced pluripotent stem cells (iPSC), a key cell type for disease modelling, analysing 202 iPSC lines derived from 151 donors, with integrated transcriptome and genomic sequence data from the same lines. We characterised the major genetic and non-genetic determinants of proteome variation across iPSC lines and assessed key regulatory mechanisms affecting variation in protein abundance. We identified 654 protein quantitative trait loci (pQTLs) in iPSCs, including disease-linked variants in protein-coding sequences and variants with trans regulatory effects. These include pQTL linked to GWAS variants that cannot be detected at the mRNA level, highlighting the utility of dissecting pQTL at peptide level resolution.

Direct Comparison of Four Hematopoietic Differentiation Methods from Human Induced Pluripotent Stem Cells

Induced pluripotent stem cells (iPSCs) are an invaluable resource for the study of human disease. However, there are no standardized methods for differentiation into hematopoietic cells, and there is a lack of robust, direct comparisons of different methodologies. In the current study we improved a feeder-free, serum-free method for generation of hematopoietic cells from iPSCs, and directly compared this with three other commonly used strategies with respect to efficiency, repeatability, hands-on time, and cost. We also investigated their capability and sensitivity to model genetic hematopoietic disorders in cells derived from Down syndrome and β-thalassemia patients. Of these methods, a multistep monolayer-based method incorporating aryl hydrocarbon receptor hyperactivation (“2D-multistep”) was the most efficient, generating significantly higher numbers of CD34⁺ progenitor cells and functional hematopoietic progenitors, while being the most time- and cost-effective and most accurately recapitulating phenotypes of Down syndrome and β-thalassemia.

•

Direct comparison of 4 serum & feeder-free iPSC hematopoietic differentiation methods

•

Comparison: cost-benefit efficiency, sensitivity to model genetic blood diseases

•

Presents an improved iPSC hematopoietic differentiation: 7× efficiency at 50% cost

•

Improved method = most live cells, CD34⁺, CFU; lowest cost; greatest sensitivity

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Uncovering the potential differentially expressed miRNAs as diagnostic biomarkers for hepatocellular carcinoma based on machine learning in The Cancer Genome Atlas database

The present study aimed to identify novel diagnostic differentially expressed microRNAs (miRNAs/miRs) in order to understand the molecular mechanisms underlying hepatocellular carcinoma. The expression data of miRNA and mRNA were downloaded for differential expression analysis. Optimal diagnostic differentially expressed miRNA biomarkers were identified via a random forest algorithm. Classification models were established to distinguish patients with hepatocellular carcinoma and normal individuals. A regulatory network between optimal diagnostic differentially expressed miRNA and differentially expressed mRNAs was then constructed. The GSE63046 dataset and in vitro experiments were used to validate the expression of the optimal diagnostic differentially expressed miRNAs identified. In addition, diagnostic and prognostic analyses of optimal diagnostic differentially expressed miRNAs were performed. In total, 14 differentially expressed miRNAs (all upregulated) and 2,982 differentially expressed mRNAs (1,989 upregulated and 993 downregulated) were identified. hsa-miR-10b-5p, hsa-miR-10b-3p, hsa-miR-224-5p, hsa-miR-183-5p and hsa-miR-182-5p were considered as the optimal diagnostic biomarkers for hepatocellular carcinoma. The mRNAs targeted by these five miRNAs included secreted frizzled related protein 1 (SFRP1), endothelin receptor type B (EDNRB), nuclear receptor subfamily 4 group A member 3 (NR4A3), four and a half LIM domains 2 (FHL2), NK3 homeobox 1 (NKX3-1), interleukin 6 signal transducer (IL6ST) and forkhead box O1 (FOXO1). ‘Bile acid biosynthesis and cholesterol’ was the most enriched signaling pathways of these target mRNAs. The expression validation of the five miRNAs was consistent with the present bioinformatics analysis. Notably, hsa-miR-10b-5p and hsa-miR-10b-3p had a significant prognosis value for patients with hepatocellular carcinoma. In conclusion, the five differentially expressed miRNAs may be considered as diagnostic biomarkers for patients with hepatocellular carcinoma. In addition, the differential expression levels of the targets of these five mRNAs, including SFRP1, EDNRB, NR4A3, FHL2, NKX3−1, IL6ST and FOXO1, may be involved in hepatocellular carcinoma tumorigenesis.

Deleterious mtDNA mutations are common in mature oocytes

Heritable mitochondrial DNA (mtDNA) mutations are common, yet only a few recurring pathogenic mtDNA variants account for the majority of known familial cases in humans. Purifying selection in the female germline is thought to be responsible for the elimination of most harmful mtDNA mutations during oogenesis. Here we show that deleterious mtDNA mutations are abundant in ovulated mature mouse oocytes and preimplantation embryos recovered from PolG mutator females but not in their live offspring. This implies that purifying selection acts not in the maternal germline per se, but during post-implantation development. We further show that oocyte mtDNA mutations can be captured and stably maintained in embryonic stem cells and then reintroduced into chimeras, thereby allowing examination of the effects of specific mutations on fetal and postnatal development.

Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Human induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across 9 time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells. We identify widespread changes in the expression of both individual features and global patterns of transcription. We next demonstrate that co-culturing human NPCs with rodent astrocytes results in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without cell sorting. We lastly adapt a previously generated RNA deconvolution approach to single-cell expression data to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue. Using many public datasets, we demonstrate neuronal cultures are maturationally heterogeneous but contain subsets of neurons more mature than previously observed.

Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility

Induced pluripotent stem cell (iPSC) technologies have provided in vitro models of inaccessible human cell types, yielding new insights into disease mechanisms especially for neurological disorders. However, without due consideration, the thousands of new human iPSC lines generated in the past decade will inevitably affect the reproducibility of iPSC-based experiments. Differences between donor individuals, genetic stability and experimental variability contribute to iPSC model variation by impacting differentiation potency, cellular heterogeneity, morphology, and transcript and protein abundance. Such effects will confound reproducible disease modelling in the absence of appropriate strategies. In this Review, we explore the causes and effects of iPSC heterogeneity, and propose approaches to detect and account for experimental variation between studies, or even exploit it for deeper biological insight.