Identification of genes with universally upregulated or downregulated expressions in colorectal cancer

RankCompV3: a differential expression analysis algorithm based on relative expression orderings and applications in single-cell RNA transcriptomics

BACKGROUND

Effective identification of differentially expressed genes (DEGs) has been challenging for single-cell RNA sequencing (scRNA-seq) profiles. Many existing algorithms have high false positive rates (FPRs) and often fail to identify weak biological signals.

RESULTS

We present a novel method for identifying DEGs in scRNA-seq data called RankCompV3. It is based on the comparison of relative expression orderings (REOs) of gene pairs which are determined by comparing the expression levels of a pair of genes in a set of single-cell profiles. The numbers of genes with consistently higher or lower expression levels than the gene of interest are counted in two groups in comparison, respectively, and the result is tabulated in a 3 × 3 contingency table which is tested by McCullagh's method to determine if the gene is dysregulated. In both simulated and real scRNA-seq data, RankCompV3 tightly controlled the FPR and demonstrated high accuracy, outperforming 11 other common single-cell DEG detection algorithms. Analysis with either regular single-cell or synthetic pseudo-bulk profiles produced highly concordant DEGs with the ground-truth. In addition, RankCompV3 demonstrates higher sensitivity to weak biological signals than other methods. The algorithm was implemented using Julia and can be called in R. The source code is available at https://github.com/pathint/RankCompV3.jl .

CONCLUSIONS

The REOs-based algorithm is a valuable tool for analyzing single-cell RNA profiles and identifying DEGs with high accuracy and sensitivity.

Personalized differential expression analysis in triple-negative breast cancer

Identification of individual-level differentially expressed genes (DEGs) is a pre-step for the analysis of disease-specific biological mechanisms and precision medicine. Previous algorithms cannot balance accuracy and sufficient statistical power. Herein, RankCompV2, designed for identifying population-level DEGs based on relative expression orderings, was adjusted to identify individual-level DEGs. Furthermore, an optimized version of individual-level RankCompV2, named as RankCompV2.1, was designed based on the assumption that the rank positions of genes and relative rank differences of gene pairs would influence the identification of individual-level DEGs. In comparison to other individualized analysis algorithms, RankCompV2.1 performed better on statistical power, computational efficiency, and acquired coequal accuracy in both simulation and real paired cancer-normal data from ten cancer types. Besides, single sample GSEA and Gene Set Variation Analysis analysis showed that pathways enriched with up-regulated and down-regulated genes presented higher and lower enrichment scores, respectively. Furthermore, we identified 16 genes that were universally deregulated in 966 triple-negative breast cancer (TNBC) samples and interacted with Food and Drug Administration (FDA)-approved drugs or antineoplastic agents, indicating notable therapeutic targets for TNBC. In addition, we also identified genes with highly variable deregulation status and used these genes to cluster TNBC samples into three subgroups with different prognoses. The subgroup with the poorest outcome was characterized by down-regulated immune-regulated pathways, signal transduction pathways, and apoptosis-related pathways. Protein-protein interaction network analysis revealed that OAS family genes may be promising drug targets to activate tumor immunity in this subgroup. In conclusion, RankCompV2.1 is capable of identifying individual-level DEGs with high accuracy and statistical power, analyzing mechanisms of carcinogenesis and exploring therapeutic strategy.

A novel anoikis-related risk model predicts prognosis in patients with colorectal cancer and responses to different immunotherapy strategies

PURPOSE

We aimed to study the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) using bioinformatics.

METHODS

GSE39582 and GSE39084, which collectively contain 363 CRC samples, were downloaded from the NCBI Gene Expression Omnibus (GEO) database as a test set. TCGA-COADREAD, with 376 CRC samples, was downloaded from the UCSC database as a validation set. Univariate Cox regression analysis was used to screen for ARGs that were significantly associated with prognosis. The top 10 ARGs were used to classify the samples into different subtypes based on unsupervised cluster analysis. The immune environments of the different subtypes were analyzed. ARGs that were significantly associated with CRC prognosis were used to construct a risk model. Univariate and multivariate Cox regression analyses were used to screen independent prognostic factors and construct a nomogram.

RESULTS

Four anoikis-related subtypes (ARSs) with differential prognoses and immune microenvironments were identified. KRAS and epithelial-mesenchymal transition pathways were enriched in subtype B, which had the worst prognosis. Three ARGs (DLG1, AKT3, and LPAR1) were used to construct the risk model. Both the test and validation sets showed worse outcomes for patients in the high-risk group than those in the low-risk group. Risk score was found to be an independent prognostic factor for CRC. Moreover, there was a difference in drug sensitivity between the high- and low-risk groups.

CONCLUSION

The identified ARGs and risk scores were associated with CRC prognosis and could predict the responses of patients with CRC to immunotherapy strategies.

Generation and characterization of humanized affinity-matured EGFL6 antibodies for ovarian cancer therapy

OBJECTIVES

Epidermal growth factor EGF-like domain multiple-6 (EGFL6) is highly expressed in high grade serous ovarian cancer and promotes both endothelial cell proliferation/angiogenesis and cancer cell proliferation/metastasis. As such it has been implicated as a therapeutic target. As a secreted factor, EGFL6 is a candidate for antibody therapy. The objectives of this study were to create and validate humanized affinity-matured EGFL6 neutralizing antibodies for clinical development.

METHODS

A selected murine EGFL6 antibody was humanized using CDR grafting to create 26 variant humanized antibodies. These were screened and the lead candidate was affinity matured. Seven humanized affinity-matured EGFL6 antibodies were screened for their ability to block EGFL6 activity on cancer cells in vitro, two of which were selected and tested their therapeutic activity in vivo.

RESULTS

Humanized affinity matured antibodies demonstrated high affinity for EGFL6 (150 pM to 2.67 nM). We found that several humanized affinity-matured EGFL6 antibodies specifically bound to recombinant, and native human EGFL6. Two lead antibodies were able to inhibit EGFL6-mediated (i) cancer cell migration, (ii) proliferation, and (iii) increase in ERK phosphorylation in cancer cells in vitro. Both lead antibodies restricted growth of an EGFL6 expressing ovarian cancer patient derived xenograft. Analysis of treated human tumor xenografts indicated that anti-EGFL6 therapy suppressed angiogenesis, inhibited tumor cell proliferation, and promoted tumor cell apoptosis.

CONCLUSIONS

Our studies confirm the ability of these humanized affinity-matured antibodies to neutralize EGFL6 and acting as a therapeutic to restrict cancer growth. This work supports the development of these antibody for first-in-human clinical trials.

LIM protein Ajuba promotes liver cell proliferation through its involvement in DNA replication and DNA damage control

The LIM-domain protein Ajuba is associated with cell proliferation, a fundamental process of tissue regeneration and cancer. We report that in the liver, Ajuba expression is increased during regeneration and in tumor cells and tissues. Knockout of Ajuba using CRISPR/Cas9 is embryonic lethal in mice. shRNA targeting of Ajuba reduces cell proliferation, delays cell entry into S-phase, reduces cell survival and tumor growth in vivo, and increases expression of the DNA damage marker γH2AX. Ajuba binding partners include proteins involved in DNA replication and damage, such as SKP2, MCM2, MCM7 and RPA70. Taken together, our data support that Ajuba promotes liver cell proliferation associated with development, regeneration, and tumor growth and is involved in DNA replication and damage repair.

Epidermal growth factor-like domain protein 6 recombinant protein facilitates osteogenic differentiation in adipose stem cells via bone morphogenetic protein 2/recombinant mothers against decapentaplegic homolog 4 signaling pathway

Adipose-derived mesenchymal stem cells (ADSCs) are a class of pluripotent stem cells isolated from the adipose tissue; they can differentiate into osteoblasts after induction and play an important role in bone repair. EGFL6 protein is secreted by adipocytes and osteoblasts and can promote endothelial cell migration and angiogenesis. This study aimed to explore the effect of recombinant EGFL6 protein on the osteogenic differentiation of ADSCs. The cells were incubated with fluorescein isothiocyanate-conjugated antibodies and analyzed by flow cytometry. Alizarin red staining and alkaline phosphatase staining were used to detect the osteogenic differentiation ability. mRNA expression was analyzed by real-time quantitative polymerase chain reaction (RT-qPCR). Protein expression was determined using Western blotting. The osteogenic differentiation ability of ADSCs isolated from the adipose tissue was significantly weakened after EGFL6 knockdown; this ability was restored upon the addition of EGFL6 recombinant protein. BMP2 knockdown inhibited the effect of EGFL6 recombinant protein on osteogenic differentiation. EGFL6 recombinant protein promoted osteogenic differentiation of ADSCs through the BMP2/SMAD4 signaling pathway. This may provide a potential target for the osteogenic differentiation of ADSCs.

Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer

Integrative multiomics data analysis provides a unique opportunity for the mechanistic understanding of colorectal cancer (CRC) in addition to the identification of potential novel therapeutic targets. In this study, we used public omics data sets to investigate potential associations between microbiome, metabolome, bulk transcriptomics and single cell RNA sequencing datasets. We identified multiple potential interactions, for example 5-aminovalerate interacting with Adlercreutzia; cholesteryl ester interacting with bacterial genera Staphylococcus, Blautia and Roseburia. Using public single cell and bulk RNA sequencing, we identified 17 overlapping genes involved in epithelial cell pathways, with particular significance of the oxidative phosphorylation pathway and the ACAT1 gene that indirectly regulates the esterification of cholesterol. These findings demonstrate that the integration of multiomics data sets from diverse populations can help us in untangling the colorectal cancer pathogenesis as well as postulate the disease pathology mechanisms and therapeutic targets.

EGFL6 promotes colorectal cancer cell growth and mobility and the anti-cancer property of anti-EGFL6 antibody

BACKGROUND

The availability of a reliable tumor target for advanced colorectal cancer (CRC) therapeutic approaches is critical since current treatments are limited. Epidermal growth factor-like domain 6 (EGFL6) has been reported to be associated with cancer development. Here, we focused on the role of EGFL6 in CRC progression and its clinical relevance. In addition, an anti-EGFL6 antibody was generated by phage display technology to investigate its potential therapeutic efficacy in CRC.

RESULTS

EGFL6 expression significantly increased in the colon tissues from CRC patients and mice showing spontaneous tumorigenesis, but not in normal tissue. Under hypoxic condition, EGFL6 expression was enhanced at both protein and transcript levels. Moreover, EGFL6 could promote cancer cell migration invasion, and proliferation of CRC cells via up-regulation of the ERK/ AKT pathway. EGFL6 also regulated cell migration, invasion, proliferation, and self-renewal through EGFR/αvβ3 integrin receptors. Treatment with the anti-EGFL6 antibody EGFL6-E5-IgG showed tumor-inhibition and anti-metastasis abilities in the xenograft and syngeneic mouse models, respectively. Moreover, EGFL6-E5-IgG treatment had no adverse effect on angiogenesis and wound healing CONCLUSIONS: We demonstrated that EGFL6 plays a role in CRC tumorigenesis and tumor progression, indicating that EGFL6 is a potential therapeutic target worth further investigation.

Hsa_circ_0128846 promotes tumorigenesis of colorectal cancer by sponging hsa-miR-1184 and releasing AJUBA and inactivating Hippo/YAP signalling

Hsa_circ_0128846 was found to be the most significantly up-regulated circRNA in our bioinformatics analysis. However, the role of hsa_circ_0128846 in colorectal cancer has not been explored. We thus aim to explore the influence and mechanism of hsa_circ_0128846 in colorectal cancer by sponging its downstream miRNA target miR-1184. We collected 40 colorectal cancer patients' tumour tissues to analyse the expression of hsa_circ_0128846, miR-1184 and AJUBA using qRT-PCR and Western blot where needed. Then, we constructed stably transfected SW480 and HCT116 cells to study the influence of hsa_circ_0128846, miR-1184 and AJUBA on colorectal cancer cell phenotypes. To obtain reliable results, a plethora of experiments including RNA immunoprecipitation assay, flow cytometry, EdU incorporation assay, wound healing migration assay, transwell invasion assay and live imaging of nude mice xenograft assay were performed. The binding relationship between hsa_circ_0128846, miR-1184 and AJUBA mRNA in colorectal cancer was validated by reported gene assay. In colorectal cancer tissues, circ_0128846 and AJUBA were both significantly up-regulated, while miR-1184 was significantly down-regulated compared with healthy tissues. Meanwhile, hsa_circ_0128846 can absorb miR-1184 to promote the progression of CRC in vivo and SW480 and HCT116 cell phenotypes in vitro. The knockdown of AJUBA, a downstream target of miR-1184, reversed the effect of miR-1184 in CRC cells via enhancing the phosphorylation of the Hippo/YAP signalling pathway proteins MST1, LATS1 and YAP. This study revealed that hsa_circ_0128846 contributed to the development of CRC by decreasing the expression of miR-1184, thereby increasing AJUBA expression and inactivating Hippo/YAP signalling.

The LIM Protein Ajuba Augments Tumor Metastasis in Colon Cancer

Colorectal cancer, along with its high potential for recurrence and metastasis, is a major health burden. Uncovering proteins and pathways required for tumor cell growth is necessary for the development of novel targeted therapies. Ajuba is a member of the LIM domain family of proteins whose expression is positively associated with numerous cancers. Our data shows that Ajuba is highly expressed in human colon cancer tissue and cell lines. Publicly available data from The Cancer Genome Atlas shows a negative correlation between survival and Ajuba expression in patients with colon cancer. To investigate its function, we transduced SW480 human colon cancer cells, with lentiviral constructs to knockdown or overexpress Ajuba protein. The transcriptome of the modified cell lines was analyzed by RNA sequencing. Among the pathways enriched in the differentially expressed genes, were cell proliferation, migration and differentiation. We confirmed our sequencing data with biological assays; cells depleted of Ajuba were less proliferative, more sensitive to irradiation, migrated less and were less efficient in colony formation. In addition, loss of Ajuba expression decreased the tumor burden in a murine model of colorectal metastasis to the liver. Taken together, our data supports that Ajuba promotes colon cancer growth, migration and metastasis and therefore is a potential candidate for targeted therapy.

Ajuba: An emerging signal transducer in oncogenesis

The LIM protein Ajuba contains an unstructured proline/glycine-rich preLIM region in the N terminus and conserved tandem LIM motifs in the C terminus. Additionally, Ajuba contains both nuclear export sequences (NES) and nuclear localization sequences (NLS), which enable Ajuba shuttle between the cytoplasm and the nucleus. Thus, Ajuba can act as a versatile scaffold participating in assembly of variety of protein complexes to execute multiple cellular functions including cell adhesion, motility, mitosis, survival, gene expression, microRNA processing and mechanical force sensing. Numerous studies have demonstrated that Ajuba plays important roles in oncogenesis and progression by regulating major signalling pathways such as Wnt, RAS/ERK, JAK/STAT and Hippo, and by acting as a co-regulator of key transcription factors such as Snail, Sp1 and nuclear hormone receptors. Clinically, Ajuba is highly expressed in various types of tumors and can be a marker for prognosis and diagnosis. In this review, we aim to summarize the up-to-date literatures on the signaling pathways mediated by Ajuba and its associated protein complexes in oncogenesis, and to discuss Ajuba as a potential target for new therapeutics to treat cancers.

Paxillin regulated genomic networks in prostate cancer

Paxillin is extensively involved in focal adhesion signaling and kinase signaling throughout the plasma membrane and cytoplasm. However, recent studies in prostate cancer suggest that paxillin also plays a critical role in regulating gene expression within the nucleus, serving as a liaison between cytoplasmic and nuclear MAPK and Androgen Receptor (AR) signaling. Here we used RNA-seq to examine the paxillin-regulated transcriptome in several human prostate cancer cell lines. First, we examined paxillin effects on androgen-mediated transcription in control or paxillin-depleted AR-positive LNCaP and C4-2 human prostate cancer cells. In androgen-dependent LNCaP cells, we found over 1000 paxillin-dependent androgen-responsive genes, some of which are involved in endocrine therapy resistance. Most paxillin-dependent AR-mediated genes in LNCaP cells were no longer paxillin-dependent in androgen-sensitive, castration-resistant C4-2 cells, suggesting that castration-resistance may markedly alter paxillin effects on genomic AR signaling. To examine the paxillin-regulated transcriptome in the absence of androgen signaling, we performed RNA-seq in AR-negative PC3 human prostate cancer cells. Paxillin enhanced several pro-proliferative pathways, including the CyclinD/Rb/E2F and DNA replication/repair pathways. Additionally, paxillin suppressed pro-apoptotic genes, including CASP1 and TNFSF10. Quantitative PCR confirmed that these pathways are similarly regulated by paxillin in LNCaP and C4-2 cells. Functional studies showed that, while paxillin stimulated cell proliferation, it had minimum effect on apoptosis. Thus, paxillin appears to be an important transcriptional regulator in prostate cancer, and analysis of its transcriptome might lead to novel approaches toward the diagnosis and treatment of this important disease.

Identification of potential key genes associated with osteosarcoma based on integrated bioinformatics analyses

Due to high rates of metastasis and poor clinical outcomes for patients, it is important to study the pathomechanisms of osteosarcoma. However, due to the fact that osteosarcoma shows significant interindividual variation and high heterogeneity, the identification of differentially expressed genes (DEGs) at the population level cannot answer many important questions related to osteosarcoma tumorigenesis. Therefore, a new strategy to identify dysregulated genes in osteosarcoma samples is required. The aim of this study was to improve our understanding of osteosarcoma pathogenesis by identifying genes with universal aberrant expression in osteosarcoma samples. Because the relative expression ordering of genes is stable in normal bone tissues but is disrupted in osteosarcoma tissues, we used the RankComp algorithm to identify DEGs in normal and osteosarcoma tissue samples. We then calculated the dysregulation frequency for each gene. Genes with deregulation frequencies above 80% were deemed to be universal DEGs. Next, coexpression, pathway enrichment, and protein-protein interaction network analyses were performed to characterize the functions of these genes. From 188 samples of osteosarcoma obtained from four datasets measured on different platforms, 51 universal DEGs were identified, including 4 universally upregulated genes and 47 universally downregulated genes. Genes that were differentially coexpressed with these universal DEGs were found to be enriched in 46 cancer-related pathways. In addition, functional and network analyses showed that genes with high dysregulation frequencies were involved in cancer-related functions. Thus, the commonly aberrant genes identified in osteosarcoma tissues may be important targets for osteosarcoma diagnosis and therapy.