RNA sequencing of glioblastoma tissue slice cultures reveals the effects of treatment at the transcriptional level

AbstractBulk RNA sequencing of a tissue captures the gene expression profile from all cell types combined. Single-cell RNA sequencing identifies discrete cell-signatures based on transcriptomic identities. Six adult human corneas were processed for single-cell RNAseq and 16 cell clusters were bioinformatically identified. Based on their transcriptomic signatures and RNAscope results using representative cluster marker genes on human cornea cross-sections, these clusters were confirmed to be stromal keratocytes, endothelium, several subtypes of corneal epithelium, conjunctival epithelium, and supportive cells in the limbal stem cell niche. The complexity of the epithelial cell layer was captured by eight distinct corneal clusters and three conjunctival clusters. These were further characterized by enriched biological pathways and molecular characteristics which revealed novel groupings related to development, function, and location within the epithelial layer. Moreover, epithelial subtypes were found to reflect their initial generation in the limbal region, differentiation, and migration through to mature epithelial cells. The single-cell map of the human cornea deepens the knowledge of the cellular subsets of the cornea on a whole genome transcriptional level. This information can be applied to better understand normal corneal biology, serve as a reference to understand corneal disease pathology, and provide potential insights into therapeutic approaches.

Download Full-text

Circ-GALNT16 Restrains Colorectal Cancer Progression by Enhancing the SUMOylation of hnRNPK

10.21203/rs.3.rs-501100/v1 ◽

2021 ◽

Author(s):

Chaofan Peng ◽

Yuqian Tan ◽

Peng Yang ◽

Kangpeng Jin ◽

Chuan Zhang ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Binding ◽

Rna Sequencing ◽

Cancer Progression ◽

Molecular Mechanisms ◽

Transcriptional Level ◽

Multiple Cancer ◽

Binding Ability ◽

Colorectal Cancer Progression

Abstract BackgroundEmerging studies have investigated circRNAs as significant regulation factors in multiple cancer progression. Nevertheless, the biological functions and underlying mechanisms of circRNAs in colorectal cancer progression remain unclear.MethodsA novel circRNA (circ-GALNT16) was identified by microarray and qRT-PCR. A series of phenotype experiments in vitro and vivo were performed to investigate the role of circ-GALNT16 in CRC. FISH, RNA pulldown assay, RIP assay, RNA sequencing, coimmunoprecipitation, and ChIP were constructed to explore the molecular mechanisms of circ-GALNT16 in colorectal cancer.ResultsCirc-GALNT16 was downregulated in colorectal cancer and negatively correlated with poor prognosis. Circ-GALNT16 suppressed the proliferation and metastasis ability of colorectal cancer in vitro and vivo. Mechanistically, circ-GALNT16 could bind to the KH3 domain of heterogeneous nuclear ribonucleoprotein K (hnRNPK), which resulted in the SUMOylation of hnRNPK. Additionally, circ-GALNT16 could enhance the hnRNPK-p53 complex by facilitating the SUMOylation of hnRNPK. Furthermore, RNA sequencing assay identified serpin family E member 1 as the target gene of circ-GALNT16 at the transcriptional level. Rescue assays revealed that circ-GALNT16 regulated the expression of Serpine1 by inhibiting the deSUMOylation of hnRNPK mediated by SUMO specific peptidase 2 and then regulating the sequence-specific DNA binding ability of the hnRNPK-p53 transcriptional complex.ConclusionsCirc-GALNT16 suppressed CRC progression via inhibiting Serpine1 expression through adjusting the sequence-specific DNA binding ability of the SENP2-mediated hnRNPK-p53 transcriptional complex and might work as a biomarker and therapeutic target for CRC.

Download Full-text

RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens

Biomedicines ◽

10.3390/biomedicines8050114 ◽

2020 ◽

Vol 8 (5) ◽

pp. 114

Author(s):

Maxim Sorokin ◽

Kirill Ignatev ◽

Elena Poddubskaya ◽

Uliana Vladimirova ◽

Nurshat Gaifullin ◽

...

Keyword(s):

Breast Cancer ◽

Lung Cancer ◽

Rna Sequencing ◽

Expression Profiles ◽

Correlation Study ◽

Cancer Tissue ◽

Transcriptional Level ◽

Tissue Samples ◽

Protein Levels ◽

Formalin Fixed Paraffin Embedded

RNA sequencing is considered the gold standard for high-throughput profiling of gene expression at the transcriptional level. Its increasing importance in cancer research and molecular diagnostics is reflected in the growing number of its mentions in scientific literature and clinical trial reports. However, the use of different reagents and protocols for RNA sequencing often produces incompatible results. Recently, we published the Oncobox Atlas of RNA sequencing profiles for normal human tissues obtained from healthy donors killed in road accidents. This is a database of molecular profiles obtained using uniform protocol and reagents settings that can be broadly used in biomedicine for data normalization in pathology, including cancer. Here, we publish new original 39 breast cancer (BC) and 19 lung cancer (LC) RNA sequencing profiles obtained for formalin-fixed paraffin-embedded (FFPE) tissue samples, fully compatible with the Oncobox Atlas. We performed the first correlation study of RNA sequencing and immunohistochemistry-measured expression profiles for the clinically actionable biomarker genes in FFPE cancer tissue samples. We demonstrated high (Spearman’s rho 0.65–0.798) and statistically significant (p < 0.00004) correlations between the RNA sequencing (Oncobox protocol) and immunohistochemical measurements for HER2/ERBB2, ER/ESR1 and PGR genes in BC, and for PDL1 gene in LC; AUC: 0.963 for HER2, 0.921 for ESR1, 0.912 for PGR, and 0.922 for PDL1. To our knowledge, this is the first validation that total RNA sequencing of archived FFPE materials provides a reliable estimation of marker protein levels. These results show that in the future, RNA sequencing can complement immunohistochemistry for reliable measurements of the expression biomarkers in FFPE cancer samples.

Download Full-text

Pepsinogen C expression–related lncRNA/circRNA/mRNA profile and its co-mediated ceRNA network in gastric cancer

10.21203/rs.3.rs-529436/v1 ◽

2021 ◽

Author(s):

Li-rong Yan ◽

Han-xi Ding ◽

Shi-xuan Shen ◽

Xiao-dong Lu ◽

Yuan Yuan ◽

...

Keyword(s):

Gastric Cancer ◽

Rna Sequencing ◽

Expression Profiles ◽

Differentially Expressed ◽

Transcriptional Level ◽

Online Database ◽

Gastric Cancer Cells ◽

Pepsinogen C ◽

Ppi Networks

Abstract Background The expression of pepsinogen C (PGC) is considered an ideal negative biomarker of gastric cancer, but its pathological mechanisms remain unclear. This study aims to analyze competing endogenous RNA (ceRNA) networks related to PGC expression at a post-transcriptional level and build an experimental basis for studying the role of PGC in the progression of gastric cancer. Materials and methods RNA sequencing technology was used to detect the differential expression profiles of PGC-related long non-coding (lnc)RNAs, circular (circ)RNAs, and mRNAs. The online database, STRING, was used to construct protein–protein interaction (PPI) networks of differentially expressed (DE) mRNAs. A ggcorrplot R package and online database were used to construct DElncRNAs/DEcircRNAs co-mediated PGC expression–related ceRNA networks. In vivo and in vitro validations were performed using quantitative reverse transcription–PCR. Results RNA sequencing found 637 DEmRNAs, 698 DElncRNAs, and 38 DEcircRNAs. The PPI network of PGC expression–related mRNAs consisted of 503 nodes and 1179 edges. CFH, PPARG, and MUC6 directly interacted with PGC. Enrichment analysis suggested that DEmRNAs were mainly enriched in cancer-related pathways. Eleven DElncRNAs, 13 circRNAs, and 35 miRNA–mRNA pairs were used to construct ceRNA networks co-mediated by DElncRNAs and DEcircRNAs that were PGC expression–related. The network directly related to PGC was as follows: SNHG16/hsa_circ_0008197–hsa-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p–PGC. Quantitative reverse transcriptase PCR validation results showed that PGC, PPARG, SNHG16, and hsa_circ_0008197 were differentially expressed in gastric cancer cells and tissues: PGC positively correlated with PPARG (r = 0.276, P = 0.009), SNHG16 (r = 0.35, P = 0.002), and hsa_circ_0008197 (r = 0.346, P = 0.005). Conclusion PGC-related DElncRNAs and DEcircRNAs co-mediated complicated ceRNA networks to regulate PGC expression, thus affecting the occurrence and development of gastric cancer at a post-transcriptional level. Of these, the network directly associated with PGC expression was a SNHG16/hsa_circ_0008197–mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p – PGC axis. This study may form a foundation for the subsequent exploration of the possible regulatory mechanisms of PGC in gastric cancer.

Download Full-text

Clinical significance of ERBB2 exon 16 skipping: analysis of a real-world retrospective observational cohort study

ESMO Open ◽

10.1136/esmoopen-2020-000985 ◽

2020 ◽

Vol 5 (6) ◽

pp. e000985

Author(s):

Lei Shi ◽

Caihua Xu ◽

Yutong Ma ◽

Qiuxiang Ou ◽

Xue Wu ◽

...

Keyword(s):

Lung Cancer ◽

Rna Sequencing ◽

Kinase Inhibitor ◽

Growth Factor Receptor ◽

Chinese Patients ◽

Transcriptional Level ◽

Driver Genes ◽

Large Patient ◽

Tki Resistance ◽

Oncogenic Driver

BackgroundERBB2 exon 16 skipping is an alternatively spliced isoform of ERBB2, which was reported to lead to oncogenic activation of ERBB2 and could potentially cause tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC) in case studies. In this study, we aimed to evaluate the frequency of ERBB2 exon 16 skipping in a large patient cohort and its function in cancer development.MethodsA total of 38 680 Chinese patients with cancer whose tumour specimens and/or circulating cell-free DNA underwent targeted nextgeneration sequencing of cancer-related genes were retrospectively reviewed. Clinicopathological features and treatment history of patients harbouring ERBB2 exon 16 skipping were evaluated. RNA-sequencing was performed to validate the presence of exon 16 skipping in ERBB2 at the transcriptional level.ResultsERBB2 exon 16 skipping is rare and was identified in a total of 18 patients (0.046% of total patients), including 12 lung cancers, which were caused by large fragment deletion spanning the whole or partial region of exon 16 (13/18, 72.2%) and/or splice site variants (6/18, 33.3%). The majority of these variants have not been previously reported and three of them were confirmed by RNA-sequencing. Among the 12 patients with lung cancer, 9 had coexisting activating EGFR mutations (exon 19 deletions or L858R) and received prior-treatment with epidermal growth factor receptor TKIs. Further analysis of matched pre-treatment and post-treatment samples in three EGFR-mutated NSCLC patients confirmed that ERBB2 exon 16 skipping was newly acquired on resistance to TKI therapies. In 6 out of 18 patients, including colorectal, gastric and ovarian cancers, there were no mutations in known cancer driver genes detected, indicating that ERBB2 exon 16 skipping might be the oncogenic driver in these patients.ConclusionsOur data suggest that ERBB2 exon 16 skipping is another mechanism of TKI resistance in EGFR-mutated patients with lung cancer, in addition to its role of being an oncogenic driver in other solid malignancies.

Download Full-text

Single-cell RNA-seq of human induced pluripotent stem cells reveals cellular heterogeneity and cell state transitions between subpopulations

10.1101/119255 ◽

2017 ◽

Cited By ~ 3

Author(s):

Quan H. Nguyen ◽

Samuel W. Lukowski ◽

Han Sheng Chiu ◽

Anne Senabouth ◽

Timothy J. C. Bruxner ◽

...

Keyword(s):

Stem Cells ◽

Induced Pluripotent Stem Cells ◽

Single Cell ◽

Rna Sequencing ◽

Pluripotent Stem Cells ◽

Single Cells ◽

State Transitions ◽

Transcriptional Level ◽

Single Cell Rna Sequencing ◽

Induced Pluripotent

AbstractHeterogeneity of cell states represented in pluripotent cultures have not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing can be used to identify how individual pluripotent cells function. Here, we present results from the analysis of single-cell RNA sequencing data from 18,787 individual WTC CRISPRi human induced pluripotent stem cells. We developed an unsupervised clustering method, and through this identified four subpopulations distinguishable on the basis of their pluripotent state including: a core pluripotent population (48.3%), proliferative (47.8%), early-primed for differentiation (2.8%) and late-primed for differentiation (1.1%). For each subpopulation we were able to identify the genes and pathways that define differences in pluripotent cell states. Our method identified four transcriptionally distinct predictor gene sets comprised of 165 unique genes that denote the specific pluripotency states; and using these sets, we developed a multigenic machine learning prediction method to accurately classify single cells into each of the subpopulations. Compared against a set of established pluripotency markers, our method increases prediction accuracy by 10%, specificity by 20%, and explains a substantially larger proportion of deviance (up to 3-fold) from the prediction model. Finally, we developed an innovative method to predict cells transitioning between subpopulations, and support our conclusions with results from two orthogonal pseudotime trajectory methods.

Download Full-text

Lack of MECP2 gene transcription on the duplicated alleles of two MECP2 duplication females with opposite skewed X chromosome inactivation

10.22541/au.161762393.39262851/v1 ◽

2021 ◽

Author(s):

Yixi Sun ◽

Yali Yang ◽

Yuqin Luo ◽

Min Chen ◽

Liya Wang ◽

...

Keyword(s):

Rna Sequencing ◽

X Chromosome ◽

Neurodevelopmental Disorder ◽

X Chromosome Inactivation ◽

Chromosome Inactivation ◽

Inhibition Mechanism ◽

Transcriptional Level ◽

X Chromosomes ◽

Xq28 Duplication ◽

Skewed X Chromosome Inactivation

Xq28 (involving MECP2) duplication syndrome is a severe neurodevelopmental disorder in males, most females are asymptomatic carriers, but there are phenotypic heterogeneities in the females. Skewed X-chromosome inactivation (XCI) seems to prevent duplicated region activation in asymptomatic females, but it remains controversial. Herein we reported two asymptomatic females (daughter and mother) with interstitial Xq28 duplication. HUMARA and RP2 assays showed that both had complete skewed XCI, the Xq28 duplicated chromosome was inactivated in the daughter, but surprisingly, it was activated in her mother. Interestingly, by combining RNA sequencing and whole-exome sequencing, we confirmed that XIST only expressed in the Xq28 duplication chromosomes of the two females, indicating that the Xq28 duplication chromosomes were inactive. Meanwhile, MECP2 and most XCI genes in the duplicated X-chromosomes were not transcriptionally expressed or upregulated, precluding major clinical phenotypes in the two females, especially the mother. We showed that XCI status detected by RNA sequencing was more relevant for establishing the clinical phenotype of MECP2 duplication females. It suggested there were other factors maintaining the XCI status in addition to DNA methylation, a possible additional inhibition mechanism occured at the transcriptional level in the unmethylated X-chromosome, counter balancing the MECP2 duplication’s detrimental phenotype effects

Download Full-text

Circ-GALNT16 restrains colorectal cancer progression by enhancing the SUMOylation of hnRNPK

Journal of Experimental & Clinical Cancer Research ◽

10.1186/s13046-021-02074-7 ◽

2021 ◽

Vol 40 (1) ◽

Author(s):

Chaofan Peng ◽

Yuqian Tan ◽

Peng Yang ◽

Kangpeng Jin ◽

Chuan Zhang ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Binding ◽

Rna Sequencing ◽

Cancer Progression ◽

Transcriptional Level ◽

Binding Ability ◽

Transcriptional Complex

Abstract Background Recent studies have investigated the role of circular RNAs (circRNAs) as significant regulatory factors in multiple cancer progression. Nevertheless, the biological functions of circRNAs and the underlying mechanisms by which they regulate colorectal cancer (CRC) progression remain unclear. Methods A novel circRNA (circ-GALNT16) was identified by microarray and qRT-PCR. A series of in vitro and in vivo phenotype experiments were performed to investigate the role of circ-GALNT16 in CRC. The FISH, RNA pulldown assay, RIP assay, RNA sequencing, coimmunoprecipitation, and ChIP were performed to investigate the molecular mechanisms of circ-GALNT16 in CRC progression. Results Circ-GALNT16 was downregulated in CRC and was negatively correlated with poor prognosis. Circ-GALNT16 suppressed the proliferation and metastatic ability of CRC cells in vitro and in vivo. Mechanistically, circ-GALNT16 could bind to the KH3 domain of heterogeneous nuclear ribonucleoprotein K (hnRNPK), which promoted the SUMOylation of hnRNPK. Additionally, circ-GALNT16 could enhance the formation of the hnRNPK-p53 complex by facilitating the SUMOylation of hnRNPK. RNA sequencing assay identified serpin family E member 1 as the target gene of circ-GALNT16 at the transcriptional level. Rescue assays revealed that circ-GALNT16 regulated the expression of Serpine1 by inhibiting the deSUMOylation of hnRNPK mediated by SUMO-specific peptidase 2 and then regulating the sequence-specific DNA binding ability of the hnRNPK-p53 transcriptional complex. Conclusions Circ-GALNT16 suppressed CRC progression by inhibiting Serpine1 expression through regulating the sequence-specific DNA binding ability of the SENP2-mediated hnRNPK-p53 transcriptional complex and might function as a biomarker and therapeutic target for CRC.

Download Full-text

Study of cellular heterogeneity and differential dynamics of autophagy in human embryonic kidney development by single-cell RNA sequencing

Cancer Cell International ◽

10.1186/s12935-021-02154-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Chen Wen-jin ◽

Pan Xiu-wu ◽

Chu Jian ◽

Xu Da ◽

Chen Jia-xin ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Intercellular Communication ◽

Wilms Tumor ◽

R Package ◽

Cellular Heterogeneity ◽

Transcriptional Level ◽

Renal Cells ◽

Cell Clusters ◽

Single Cell Rna Sequencing

Abstract Background Autophagy is believed to participate in embryonic development, but whether the expression of autophagy-associated genes undergoes changes during the development of human embryonic kidneys remains unknown. Methods In this work, we identified 36,151 human renal cells from embryonic kidneys of 9–18 gestational weeks in 16 major clusters by single-cell RNA sequencing (scRNA-seq), and detected 1350 autophagy-related genes in all fetal renal cells. The abundance of each cell cluster in Wilms tumor samples from scRNA-seq and GDC TARGET WT datasets was detected by CIBERSORTx. R package Monocle 3 was used to determine differentiation trajectories. Cyclone tool of R package scran was applied to calculate the cell cycle scores. R package SCENIC was used to investigate the transcriptional regulons. The FindMarkers tool from Seurat was used to calculate DEGs. GSVA was used to perform gene set enrichment analyses. CellphoneDB was utilized to analyze intercellular communication. Results It was found that cells in the 13th gestational week showed the lowest transcriptional level in each cluster in all stages. Nephron progenitors could be divided into four subgroups with diverse levels of autophagy corresponding to different SIX2 expressions. SSBpod (podocyte precursors) could differentiate into four types of podocytes (Pod), and autophagy-related regulation was involved in this process. Pseudotime analysis showed that interstitial progenitor cells (IPCs) potentially possessed two primitive directions of differentiation to interstitial cells with different expressions of autophagy. It was found that NPCs, pretubular aggregates and interstitial cell clusters had high abundance in Wilms tumor as compared with para-tumor samples with active intercellular communication. Conclusions All these findings suggest that autophagy may be involved in the development and cellular heterogeneity of early human fetal kidneys. In addition, part of Wilms tumor cancer cells possess the characteristics of some fetal renal cell clusters. Graphical abstract

Download Full-text

Defining the adult hippocampal neural stem cell secretome: in vivo versus in vitro transcriptomic differences and their correlation to secreted protein levels

10.1101/760215 ◽

2019 ◽

Author(s):

JK. Denninger ◽

X. Chen ◽

AM. Turkoglu ◽

P. Sarchet ◽

AR. Volk ◽

...

Keyword(s):

Gene Expression ◽

Stem Cell ◽

Rna Sequencing ◽

Antibody Array ◽

Transcriptional Level ◽

Isolated Cells ◽

Secretome Profiling

AbstractRecent evidence shows that adult hippocampal neural stem and progenitor cells (NSPCs) secrete a variety of proteins that affect tissue function. Though several individual NSPC-derived proteins have been shown to impact cellular processes like neuronal maturation and stem cell maintenance, a broad characterization of NSPC-secreted factors is lacking. Secretome profiling of low abundance stem cell populations is typically achieved via proteomic characterization of in vitro, isolated cells. Here, we analyzed the in vitro NSPC secretome using conditioned media from cultured adult mouse hippocampal NSPCs and detected over 200 different bioactive proteins with an antibody array. We next assessed the NSPC secretome on a transcriptional level with RNA sequencing (RNAseq) of cultured NSPCs. This comparison revealed that quantification of gene expression did not accurately predict relative protein abundance for several factors. Furthermore, comparing our transcriptional data with previously published single cell RNA sequencing datasets of freshly isolated hippocampal NSPCs, we found key differences in gene expression of secreted proteins between cultured and acutely isolated NSPCs. Understanding the components and functions of the NSPC secretome is essential to understanding how these cells may modulate the hippocampal neurogenic niche, as well as how they can be applied therapeutically. Cumulatively, our data emphasize the importance of using proteomic analysis in conjunction with transcriptomic studies and highlights the need for better methods of global unbiased secretome profiling.

Download Full-text