COLEC12 regulates apoptosis of osteosarcoma through Toll-like receptor 4-activated inflammation

Dysregulated AEBP1 and COLEC12 Genes in Late-Onset Alzheimer's Disease: Insights from Brain Cortex and Peripheral Blood Analysis

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive impairment, often accompanied by alterations in mood, confusion, and, ultimately, a state of acute mental disturbance. The cerebral cortex is considered a promising area for investigating the underlying causes of AD by analyzing transcriptional patterns, which could be complemented by investigating blood samples obtained from patients. We analyzed the RNA expression profiles of three distinct areas of the brain cortex, including the frontal cortex (FC), temporal cortex (TC), and entorhinal cortex (EC) in patients with AD. Functional enrichment analysis was performed on the differentially expressed genes (DEGs) across the three regions. The two genes with the most significant expression changes in the EC region were selected for assessing mRNA expression levels in the peripheral blood of late-onset AD patients using quantitative PCR (qPCR). We identified eight shared DEGs in these regions, including AEBP1 and COLEC12, which exhibited prominent changes in expression. Functional enrichment analysis uncovered a significant association of these DEGs with the transforming growth factor-β (TGF-β) signaling pathway and processes related to angiogenesis. Importantly, we established a robust connection between the up-regulation of AEBP1 and COLEC12 in both the brain and peripheral blood. Furthermore, we have demonstrated the potential of AEBP1 and COLEC12 genes as effective diagnostic tools for distinguishing between late-onset AD patients and healthy controls. This study unveils the intricate interplay between AEBP1 and COLEC12 in AD and underscores their potential as markers for disease detection and monitoring.

Identification of large yellow croakers (Larimichthys crocea) scavenger receptor genes: Involvement in immune response to Pseudomonas plecoglossicida infection and hypoxia-exposure experiments

Scavenger receptors (SRs) are pattern recognition receptors involved in the innate immune defense against pathogen infection in fish. However, there has not been much research done on teleosts. In this study, 18 members of the SR gene family were found in large yellow croaker. The identification of the SR gene family showed that the protein length of SR members in large yellow croaker were quite different, and most SR genes were distributed in nuclear and endoplasmic. The evolutionary relationship, exon/intron structure and motif analysis revealed that members of the SR gene family were highly conserved. The results of the expression profiles after Pseudomonas plecoglossicida infection and hypoxia-exposure demonstrated that SR members were involved in inflammatory reactions. Especially, COLEC12 and SCARF1 exhibited substantial changes in response to both P. plecoglossicida and hypoxia stress, indicating their possible immunological functions. The result of this study revealed that SR genes played a vital part in the innate immune response of large yellow croaker, and would give important details for a deeper comprehension of the SR gene family's regulation mechanism under various conditions in large yellow croaker.

Genome-wide identification and expression analysis of C-type lectins in discus fish (Symphysodon aequifasciatus) during parental care

Discus fish (Symphysodon aequifasciatus) exhibit a unique parental care behavior: adult discus produces secretion through their skin, on which the larvae live after birth. The immune components in the skin mucus of parental discus would change during different parental care. C-type lectins (CTLs) could identify and eliminate pathogenic microorganisms and play important roles in innate immunity. Studies on CTLs of discus fish especially during parental care, however, are scarce. Here, we identified 186 CTL genes that distributed in 27 linkage groups based on discus genome. Phylogenetic analysis showed that S. aequifasciatus CTL (SaCTL) members were grouped into 14 subfamilies. A total of 80 gene replication events occurred, of which 15 pairs were subjected to segmental duplication and 65 pairs underwent tandem duplication. Ka/Ks ranged from 0.11 (SaCTL25/SaCTL158) to 0.68 (SaCTL36/SaCTL69), all undergoing purifying selection. RNA-seq analysis revealed that SaCTL members, including duplicated genes, in the skin of parental discus show distinct expression patterns in different care stages and between male and female parents. The SaCTL11 was differentially expressed in most care stages and reached the maximum after eggs spawned, but the expression of its paired SaCTL14 was low in each stage. The SaCTL39 increased first and then decreased, reaching a peak in eggs spawned, while paired SaCTL48 first decreased and then increased, reaching a peak in hatched eggs. The SaCTL50 was differentially expressed only in female fish during care, but not in male fish. These results provide new insights into the evolution and potential functional differentiation of CTLs in discus fish during parental care.

A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma

Background

Anoikis resistance is a prerequisite for the successful development of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes (ARGs) correlates with OS prognosis remains unclear. This study aimed to investigate the feasibility of using ARGs as prognostic tools for the risk stratification of OS.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided transcriptome information relevant to OS. The GeneCards database was used to identify ARGs. Differentially expressed ARGs (DEARGs) were identified by overlapping ARGs with common differentially expressed genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and GSE99671 datasets. Anoikis-related clusters of patients were obtained by consistent clustering, and gene set variation analysis (GSVA) of the different clusters was completed. Next, a risk model was created using Cox regression analyses. Risk scores and clinical features were assessed for independent prognostic values, and a nomogram model was constructed. Subsequently, a functional enrichment analysis of the high- and low-risk groups was performed. In addition, the immunological characteristics of OS samples were compared between the high- and low-risk groups, and their sensitivity to therapeutic agents was explored.

Results

Seven DEARGs between OS and normal samples were obtained by intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly differentially expressed between both clusters (P<0.05) and were identified as prognosis-related genes. The risk model showed that the risk score and tumor metastasis were independent prognostic factors of patients with OS. A nomogram combining risk score and tumor metastasis effectively predicted the prognosis. In addition, patients in the high-risk group had low immune scores and high tumor purity. The levels of immune cell infiltration, expression of human leukocyte antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower in the high-risk group than those in the low-risk group. The low-risk group was sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group exhibited lower inhibitory concentration values by 50% for 24 drugs, including AG.014699, AMG.706, and AZD6482.

Conclusion

The prognostic stratification framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead to more efficient clinical management.

COLEC12 Promotes Tumor Progression and Is Correlated With Poor Prognosis in Gastric Cancer

PURPOSE

Collectin subfamily member 12, a transmembrane scavenger receptor C-type lectin, is aberrantly expressed in various cancers. However, its physiological role in gastric cancer remains somewhat unclear. This study aimed to investigate the Collectin subfamily member 12 expression pattern in human gastric cancer and its role in gastric cancer progression.

METHODS

The Kaplan-Meier method was used for survival analysis. The univariate and multivariate Cox proportional hazards regression models were used to identify independent predictors for progression-free survival and overall survival. The effects of Collectin subfamily member 12 on gastric cancer cell proliferation, migration, invasion, and apoptosis were detected through the cell counting kit-8 assay, colony formation assay, wound healing assay, transwell assay, and flow cytometry analysis, respectively. Additionally, the correlation between Collectin subfamily member 12 expression and immune cell infiltration was analyzed through bioinformatics.

RESULTS

Collectin subfamily member 12 was highly expressed in advanced gastric cancer (T3-T4, pathologic stage III-IV). High Collectin subfamily member 12 expression was correlated with a worse progression-free survival and overall survival in the gastric cancer patients. In vitro, cell line studies revealed that Collectin subfamily member 12 promoted gastric cancer cell proliferation, migration, and invasion and inhibited gastric cancer cell apoptosis. The bioinformatics analysis further demonstrated that the Collectin subfamily member 12 expression level positively correlated with infiltration of several immune cells, such as M2 macrophages, dendritic cells, neutrophils, and regulatory T cells, suggesting that Collectin subfamily member 12 may also play a role in suppressing tumor immune response in gastric cancer.

CONCLUSIONS

Collectin subfamily member 12 was identified as a novel predictive marker and target for the clinical treatment of gastric cancer.

Cancer-Associated Fibroblast Risk Model for Prediction of Colorectal Carcinoma Prognosis and Therapeutic Responses

Colorectal carcinoma (CRC) is a malignant tumor of the digestive system. Cancer-associated fibroblasts (CAFs) are important cellular elements in the tumor microenvironment of CRC, which contribute to CRC progression and immune escape. To predict the survival outcome and therapeutic responses of CRC patients, we identified genes connected with stromal CAF and generated a risk model. In this study, we used multiple algorithms to reveal CAF-related genes in the Gene Expression Omnibus and The Cancer Genome Atlas datasets and construct a risk model composed by prognostic CAF-associated genes. Then, we evaluated whether the risk score could predict CAF infiltrations and immunotherapy in CRC and confirmed the expression of the risk model in CAFs. Our results showed that CRC patients with high CAF infiltrations and stromal score had worse prognosis than those with low-CAF infiltrations and stromal score. We obtained 88 stromal CAF-associated hub-genes and generated a CAF risk model consisting of ZNF532 and COLEC12. Compared with low-risk group, the overall survival in high-risk group was shorter. The relationship between risk score, ZNF532 and COLEC12, and stromal CAF infiltrations and CAF markers was positive. In addition, the effect of immunotherapy in the high-risk group was not as good as that in the low-risk group. Patients with the high-risk group were enriched in chemokine signaling pathway, cytokine-cytokine receptor interaction, and focal adhesion. Finally, we confirmed that the expressions of ZNF532 and COLEC12 in risk model were widely distributed in fibroblasts of CRC, and the expression levels were higher in fibroblasts than CRC cells. In conclusion, the prognostic CAF signature of ZNF532 and COLEC12 can be applied not only to predict the prognosis of CRC patients but also to evaluate the immunotherapy response in CRC patients, and these findings provide the possibility for further development of individualized treatment for CRC.

Whole genome analysis reveals the genomic complexity in metastatic cutaneous squamous cell carcinoma

Metastatic cutaneous squamous cell carcinoma (CSCC) is a highly morbid disease requiring radical surgery and adjuvant therapy, which is associated with a poor prognosis. Yet, compared to other advanced malignancies, relatively little is known of the genomic landscape of metastatic CSCC. We have previously reported the mutational signatures and mutational patterns of CCCTC-binding factor (CTCF) regions in metastatic CSCC. However, many other genomic components (indel signatures, non-coding drivers, and structural variants) of metastatic CSCC have not been reported. To this end, we performed whole genome sequencing on lymph node metastases and blood DNA from 25 CSCC patients with regional metastases of the head and neck. We designed a multifaceted computational analysis at the whole genome level to provide a more comprehensive perspective of the genomic landscape of metastatic CSCC. In the non-coding genome, 3′ untranslated region (3′UTR) regions of EVC (48% of specimens), PPP1R1A (48% of specimens), and ABCA4 (20% of specimens) along with the tumor-suppressing long non-coding RNA (lncRNA) LINC01003 (64% of specimens) were significantly functionally altered (Q-value < 0.05) and represent potential non-coding biomarkers of CSCC. Recurrent copy number loss in the tumor suppressor gene PTPRD was observed. Gene amplification was much less frequent, and few genes were recurrently amplified. Single nucleotide variants driver analyses from three tools confirmed TP53 and CDKN2A as recurrently mutated genes but also identified C9 as a potential novel driver in this disease. Furthermore, indel signature analysis highlighted the dominance of ID signature 13 (ID13) followed by ID8 and ID9. ID9 has previously been shown to have no association with skin melanoma, unlike ID13 and ID8, suggesting a novel pattern of indel variation in metastatic CSCC. The enrichment analysis of various genetically altered candidates shows enrichment of “TGF-beta regulation of extracellular matrix” and “cell cycle G1 to S check points.” These enriched terms are associated with genetic instability, cell proliferation, and migration as mechanisms of genomic drivers of metastatic CSCC.

CircPVT1 promotes the tumorigenesis and metastasis of osteosarcoma via mediation of miR-26b-5p/CCNB1 axis

INTRODUCTION

Osteosarcoma (OS) is the most aggressive malignancy among the bone tumors in the world. Circular RNAs (circRNAs) have been reported to be participated in multiple cancers, including OS. Meanwhile, circPVT1 has been proved to be upregulated in OS. However, the mechanism by which circPVT1 mediates the tumorigenesis of OS remains to be further explored.

MATERIALS AND METHODS

Protein and gene expressions in OS cells were measured by western blot and RT-qPCR, respectively. Cell growth was assessed by flow cytometry and colony formation, respectively. In addition, cell migration was assessed by wound healing, and invasion was evaluated by Transwell assay. Meanwhile, the correlation among circPVT1, miR-26b-5p and CCNB1 was explored by RNA pull-down and dual luciferase assay. Finally, in vivo model was established to explore the role of circPVT1 in OS in vivo.

RESULTS

CircPVT1 and CCNB1 were significantly upregulated in OS cells, while miR-26b-5p was downregulated. Knockdown of circPVT1 notably inhibited proliferation and induced apoptosis of OS cells. CircPVT1 shRNA significantly suppressed the OS cell invasion and migration. Meanwhile, circPVT1 sponged miR-26b-5p and CCNB1 was found to be the direct target of miR-26b-5p. Furthermore, silencing of circPVT1 inhibited the growth and metastasis of OS in vivo.

CONCLUSION

Silencing of circPVT1 notably suppressed the tumorigenesis and metastasis of OS via miR-26b-5p/CCNB1 axis. Therefore, circPVT1 might be used as a target for OS treatment.

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.

The potential role of methyltransferase-like 5 in deficient mismatch repair of uterine corpus endometrial carcinoma

To explore the potential function of methyltransferase-like 5 (METTL5) in uterine corpus endometrial carcinoma (UCEC) and verify the relationship between deficient DNA mismatch repair (MMR) and METTL5. We used bioinformatics to predict the possible role of METTL5 and molecular biology methods to analyze METTL5 expression. We observed UCEC proliferation, development, and apoptosis using a METTL5 knockdown lentivirus and, coupled with METTL5 bioinformatics and Western blot analysis, detected microsatellite instability (MSI) and MMR. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Finally, some METTL5-associated gene mutations in UCECs were detected. Results show that METTL5 expression in UCEC tumor tissue was increased, and UCEC patients with high METTL5 expression had worse prognostic outcomes. We also observed the highest METTL5 expression level in KLE cells. Furthermore, knocking down METTL5 weakened the proliferation, reduced tumor volume and biomarkers, and increased apoptosis. Moreover, METTL5 knockdown induced the MSH2, MSH6 and PMS2 expression in MMR. METTL5 was negatively correlated with gene silencing, mRNA binding, olfactory receptor activity, antigen processing and presentation, cytosolic DNA sensing, olfactory transduction, and RIG-1-like and Toll-like receptor signaling pathways. METTL5 may regulate MMR protein levels in UCECs, thus enhancing UCEC proliferation, development, and prognosis.

Transmembrane p24 trafficking protein 2 regulates inflammation through the TLR4/NF-κB signaling pathway in lung adenocarcinoma

Background

To investigate the role of transmembrane p24 trafficking protein 2 (TMED2) in lung adenocarcinoma (LUAD) and determine whether TMED2 knockdown could inhibit LUAD in vitro and in vivo.

Methods

TIMER2.0, Kaplan-Meier plotter, gene set enrichment analysis (GSEA), Target Gene, and pan-cancer systems were used to predict the potential function of TMED2. Western blotting and immunohistochemistry were performed to analyze TMED2 expression in different tissues or cell lines. The proliferation, development, and apoptosis of LUAD were observed using a lentivirus-mediated TMED2 knockdown. Bioinformatics and western blot analysis of TMED2 against inflammation via the TLR4/NF-κB signaling pathway were conducted.

Results

TMED2 expression in LUAD tumor tissues was higher than that in normal tissues and positively correlated with poor survival in lung cancer and negatively correlated with apoptosis in LUAD. The expression of TMED2 was higher in tumors or HCC827 cells. TMED2 knockdown inhibited LUAD development in vitro and in vivo and increased the levels of inflammatory factors via the TLR4/NF-κB signaling pathway. TMED2 was correlated with TME, immune score, TME-associated immune cells, their target markers, and some mechanisms and pathways, as determined using the TIMER2.0, GO, and KEGG assays.

Conclusions

TMED2 may regulate inflammation in LUAD through the TLR4/NF-κB signaling pathway and enhance the proliferation, development, and prognosis of LUAD by regulating inflammation, which provide a new strategy for treating LUAD by regulating inflammation.

Integrated bioinformatics analyses of key genes involved in hepatocellular carcinoma immunosuppression

Hepatocellular carcinoma (HCC) is a typical inflammation-driven cancer. Chronically unresolved inflammation may remodel the immunosuppressive tumor microenvironment, which is rich in innate immune cells. The mechanisms via which HCC progresses through the evasion of the innate immune surveillance remain unclear. The present study thus aimed to identify key genes involved in HCC immunosuppression and to establish an innate immune risk signature, with the ultimate goal of obtaining new insight into effective immunotherapies. HCC and normal liver tissue mRNA expression and clinicopathological data were obtained from the Cancer Genome Atlas database. The immunosuppressive innate immune-related genes (IIRGs) in HCC were screened using integrated bioinformatics analyses. Gene expression was then validated using the Gene Expression Omnibus database and the Human Protein Atlas database, and tissues were obtained from patients with HCC who underwent surgery. In total, 3,676 genes were identified as differentially expressed mRNAs after comparing the HCC tissues with the normal liver tissues in TCGA. Gene Set Enrichment Analyses revealed 21 highly expressed IIRGs in HCC tissues. A survival analysis and Cox regression model were used to construct an innate immune risk signature, including three IIRGs: Collectin-12 (COLEC12), matrix metalloproteinase-12 (MMP12) and mucin-12 (MUC12) genes. Univariate and multivariate Cox analyses revealed that the signature of the three IIRGs was a robust independent risk factor in relation to the overall survival (OS) of patients with HCC. The expression of the three aforementioned IIRGs was confirmed through external validation. Moreover, COLEC12 and MMP12 expression significantly correlated with that of immune checkpoint molecules or immunosuppressive cytokines. The tumor immune dysfunction and exclusion tool predicted that the increased expression of the three IIRGs in patients with HCC was significantly associated with the efficacy of relatively poor immune checkpoint blockade therapy. Conclusively, a novel innate immune-related risk signature for patients with HCC was constructed and validated. This signature may be involved in immunosuppression, and may be used to predict a poor prognosis, functioning as a potential immunotherapeutic target for patients with HCC.

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear. The current study aimed to discover reliable biomarkers for anticipating the future prognosis of HCC patients based on the relationship between TDTRGs and IRGs.

Methods

Tumor doubling time-related genes (TDTRGs) were acquired from GSE54236 by using Pearson correlation test and immune-related genes (IRGs) were available from ImmPort. Prognostic TDTRGs and IRGs in TCGA-LIHC dataset were determined to create a prognostic model by the LASSO-Cox regression and stepwise Cox regression analysis. International Cancer Genome Consortium (ICGC) and another cohort of individual clinical samples acted as external validations. Additionally, significant impacts of the signature on HCC immune microenvironment and reaction to immune checkpoint inhibitors were observed.

Results

Among the 68 overlapping genes identified as TDTRG and IRG, a total of 29 genes had significant prognostic relevance and were further selected by performing a LASSO-Cox regression model based on the minimum value of λ. Subsequently, a prognostic three-gene signature including HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), C-type lectin domain family 1 member B (CLEC1B), and Collectin sub-family member 12 (COLEC12) was finally identified by stepwise Cox proportional modeling. The signature exhibited superior accuracy in forecasting the survival outcomes of HCC patients in TCGA, ICGC and the independent clinical cohorts. Patients in high-risk subgroup had significantly increased levels of immune checkpoint molecules including PD-L1, CD276, CTLA4, CXCR4, IL1A, PD-L2, TGFB1, OX40 and CD137, and are therefore more sensitive to immune checkpoint inhibitors (ICIs) treatment. Finally, we first found that overexpression of CLEC1B inhibited the proliferation and migration ability of HuH7 cells.

Conclusions

In summary, the prognostic signature based on TDTRGs and IRGs could effectively help clinicians classify HCC patients for prognosis prediction and individualized immunotherapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02227-w.

The choice of negative control antisense oligonucleotides dramatically impacts downstream analysis depending on the cellular background

Background

The lymphatic and the blood vasculature are closely related systems that collaborate to ensure the organism’s physiological function. Despite their common developmental origin, they present distinct functional fates in adulthood that rely on robust lineage-specific regulatory programs. The recent technological boost in sequencing approaches unveiled long noncoding RNAs (lncRNAs) as prominent regulatory players of various gene expression levels in a cell-type-specific manner.

Results

To investigate the potential roles of lncRNAs in vascular biology, we performed antisense oligonucleotide (ASO) knockdowns of lncRNA candidates specifically expressed either in human lymphatic or blood vascular endothelial cells (LECs or BECs) followed by Cap Analysis of Gene Expression (CAGE-Seq). Here, we describe the quality control steps adopted in our analysis pipeline before determining the knockdown effects of three ASOs per lncRNA target on the LEC or BEC transcriptomes. In this regard, we especially observed that the choice of negative control ASOs can dramatically impact the conclusions drawn from the analysis depending on the cellular background.

Conclusion

In conclusion, the comparison of negative control ASO effects on the targeted cell type transcriptomes highlights the essential need to select a proper control set of multiple negative control ASO based on the investigated cell types.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00992-1.

RNA-binding protein with serine-rich domain 1 regulates microsatellite instability of uterine corpus endometrial adenocarcinoma

OBJECTIVE

To determine the role of RNA-binding protein with serine-rich domain 1 (RNPS1) in uterine corpus endometrial carcinoma (UCEC), the role of RNPS1 knockdown in UCEC development in vitro and in vivo, and the relationship between RNPS1 and mismatch repair (MMR) in UCEC.

METHODS

We predicted the potential function of RNPS1 using bioinformatics systems. The expression of RNPS1 in tissues and cell lines was analyzed by western blotting and immunohistochemistry. The expression of RNPS1 in MMR was assessed using bioinformatics and western blotting. The proliferation and apoptosis of UCEC cells were assessed under RNPS1 knockdown conditions, and RNPS1 regulation in MMR was detected by suppressing Notch signaling. Associations between RNPS1 and gene mutations in UCEC and prognosis were analyzed.

RESULTS

The RNPS1 level was higher in UCEC tumors than in normal tissues and tumors or RL952 cells. Prognostic outcomes were worse when UCEC showed abundant RNPS1 expression. Lentiviral RNPS1 knockdown weakened tumor cell proliferation and suppressed biomarker expression, reduced the tumor volume, promoted apoptosis in vitro and in vivo, and inhibited UCEC development. Increased MutS homolog 2 (MSH2) and MutS homolog 6 (MSH6) levels in MMR after RNPS1 knockdown were reversed by inhibiting Notch signaling. Furthermore, RNPS1 was associated with mutations in NAA11, C2orf57, NUPR1, and other genes involved in UCEC prognosis.

CONCLUSION

RNPS1 may regulate the expression levels of MSH2 and MSH6 in MMR, enhancing the proliferation, development, and prognosis of UCEC through a Notch signaling pathway in UCEC. Our study offers a new method and strategy for delaying UCEC development through modulating MMR.

COLEC12 regulates apoptosis of osteosarcoma through Toll-like receptor 4-activated inflammation

OBJECTIVE

To investigate the role of COLEC12 in osteosarcoma and observe the relationship between COLEC12 knockdown and the inflammation of osteosarcoma. Then, further explore whether the process is regulated by TLR4.

METHOD

GEPIA and TCGA systems were used to predict the potential function of COLEC12. Western blot and RT-PCR were used to analyze the protein expression, or mRNA level, of COLEC12 in different tissue or cell lines. The occurrence and development of osteosarcoma were observed by using COLEC12 knockdown lentivirus. The inflammation indexes of osteosarcoma, in vitro and in vivo, were explored. TLR4 knockdown lentivirus was applied to the relationship between COLEC12 and TLR4.

RESULTS

COLEC12 expression in SARC tumor tissue was higher than in normal, and a high expression of COLEC12 in SARC patients had a worse prognostic outcome. Pairwise gene correlation analysis revealed a potential relationship between COLEC12 and TLR4. The COLEC12 expression and mRNA level in the tumor or Saos-2 cells were increased. COLEC12 knockdown lentivirus could inhibit osteosarcoma development, in vivo and vitro, through reducing tumor volume and weight, weakening tumor proliferation, migration, and invasion, and enhancing apoptosis. Furthermore, COLEC12 knockdown could increase inflammation of osteosarcoma, in vivo and in vitro, through inducing myeloperoxidase (MPO), TLR4, NF-κB, and C3, and expression of related inflammatory factors. Finally, TLR4 knockdown lentivirus inhibits the progress of inflammation after COLEC12 regulation, in vivo and vitro.

CONCLUSION

COLEC12 may be able to regulate apoptosis and inflammation of osteosarcoma, and TLR4 may be the downstream target factor of COLEC12 in inflammation.