Comprehensive Analysis of the Expression and Prognosis for MMPs in Human Colorectal Cancer

SH3GL2 and MMP17 as lung adenocarcinoma biomarkers: a machine-learning based approach

Objective

Using bioinformatics machine learning methods, our research aims to identify the potential key genes associated with Lung adenocarcinoma (LUAD).

Methods

We obtained two gene expression profiling microarrays (GSE68571 and GSE74706) from the public Gene Expression Omnibus (GEO) database at the National Centre for Biotechnology Information (NCBI). The purpose was to identify Differentially Expressed Genes (DEGs) between the lung adenocarcinoma group and the healthy control group. The limma R package in R was utilized for this analysis. For the differential gene diagnosis of lung adenocarcinoma, we employed the least absolute shrinkage and selection operator (LASSO) regression and SVM-RFE screening crossover. To evaluate the performance, ROC curves were plotted. We performed immuno-infiltration analysis using CIBERSORT. Finally, we validated the key genes through qRT-PCR and Western-blot verification, then downregulated MMP17 gene expression, upregulated SH3GL2 gene expression, and performed CCK8 experiments.

Results

A total of 32 Differentially Expressed Genes (DEGs) were identified. Two diagnostic marker genes, SH3GL2 and MMP17, were selected by employing LASSO and SVM-RFE machine learning methods. In Lung adenocarcinoma cells, the expression of MMP17 was observed to be elevated compared to normal lung epithelial cells in the control group (P < 0.05). In contrast, a down-regulation of SH3GL2 was found in Lung adenocarcinoma cells (P < 0.05). Finally, we downregulated MMP17 and upregulated SH3GL2 gene expression, then the CCK8 showed that the proliferation of both lung cancer cells was inhibited.

Conclusion

SH3GL2 and MMP17 are expected to be potential biomarkers for Lung adenocarcinoma.

The Downregulation of MMP23B Facilitates the Suppression of Vitality and Induction of Apoptosis in Endometrial Cancer Cells

Endometrial cancer is a malignant tumor that commonly occurs in the female reproductive system and its incidence is still increasing. The mechanism of the development of endometrial cancer has not yet been fully clarified, so we need to continuously study the relevant mechanisms of endometrial cancer and continue to explore its biomarkers in order to discover more precise and effective treatment methods for endometrial cancer. RT-qPCR (Real-Time quantitative Polymerase Chain Reaction) experiments were used to detect the expression level of MMP23B (Matrix Metalloproteinase 23B) in endometrial cancer cells; the clinical data of the TCGA (The Cancer Genome Atlas) database were downloaded, and gene expression profiles were analyzed to investigate the correlation between MMP23B (Matrix Metalloproteinase 23B) and the survival prognosis of endometrial cancer, and functional enrichment analysis was performed on MMP23B (Matrix Metalloproteinase 23B) related genes. After silencing MMP23B (Matrix Metalloproteinase 23B), CCK8 (Cell Counting Kit-8), RT-qPCR (Real-Time quantitative Polymerase Chain Reaction), scratch assay, and transwell assay were used to detect cell viability, levels of apoptotic factors, migration rate, and invasion number of endometrial cancer, respectively. MMP23B (Matrix Metalloproteinase 23B) was highly expressed in endometrial cancer, which is closely related to a poor survival prognosis for endometrial cancer, and may act on endometrial cancer through apoptosis-related functions. The downregulation of MMP23B (Matrix Metalloproteinase 23B) reduced the cell viability of endometrial cancer cells, upregulated the expression levels of CASP3 (Caspase-3), CASP8 (Caspase-8) and CASP9 (Caspase-9) in cells, and inhibited cell migration and invasion.

Cell Senescence-Related Genes as Biomarkers for Prognosis and Immunotherapeutic Response in Colon Cancer

Colon adenocarcinoma (COAD) stands out as the most prevalent malignancy diagnosed within the gastrointestinal tract, bearing substantial incidence and mortality rates. The processes of ageing and senescence intricately intertwine with tumorigenesis and immune regulation, concurrently exerting influence on the remodelling of the tumor microenvironment (TME). This phenomenon, in turn, significantly impacts the efficacy of immunotherapeutic interventions. Despite this awareness, the comprehensive understanding of the intricate interplay between cellular senescence and TME in the context of COAD remains elusive. Further inquiry is imperative to comprehensively gauge the relevance of cellular senescence-related genes (CSGs) in the realms of immune infiltration and the prognostication of COAD. Differentially expressed cell senescence-related genes (DE-CSGs) within COAD tumors and normal specimens were discerned through analysis of the TCGA-COAD dataset. Leveraging univariate, LASSO, and multivariate Cox regression analyses, we formulated a prognostic risk signature. Subsequent validation utilised two independent GEO datasets. Furthermore, a nomogram was devised to gauge the prognostic significance of this signature. Additionally, the immune landscape of the Cell Senescence-related Signature (CSS) was characterised using CIBERSORT and TIMER algorithms. The expression levels of CSGs were quantified through RT-PCR in COAD specimens. Drawing upon mRNA expression profiles of 191 DE-CSGs, we successfully established a 9-gene CSS, demonstrating its autonomy as a prognostic determinant for COAD patients. Those assigned high-risk scores exhibited an immunosuppressive phenotype, marked by elevated proportions of resting CD4+memory T cells and macrophages M0, correlating with diminished overall survival. Subsequent analyses uncovered that the amalgamation of CSS with the expression profiles of immune checkpoint key genes effectively predicted patient prognosis. Furthermore, patients with low-risk scores demonstrated a potential association with more favourable therapeutic outcomes in the context of immunotherapy. This study has culminated in the development of a prognostic risk signature grounded in cell senescence-related genes for COAD. We posit that the CSS plays a regulatory role in immune infiltration, emerging as a robust biomarker for prognosis and a predictive indicator for immunotherapeutic responsiveness within the COAD landscape.

Insights into the molecular mechanisms and signalling pathways of epithelial to mesenchymal transition (EMT) in colorectal cancer: A systematic review and bioinformatic analysis of gene expression

Colorectal cancer (CRC) is ranked as the second leading cause of mortality worldwide, mainly due to metastasis. Epithelial to mesenchymal transition (EMT) is a complex cellular process that drives CRC metastasis, regulated by changes in EMT-associated gene expression. However, while numerous genes have been identified as EMT regulators through various in vivo and in vitro studies, little is known about the genes that are differentially expressed in CRC tumour tissue and their signalling pathway in regulating EMT. Using an integration of systematic search and bioinformatic analysis, gene expression profiles of CRC tumour tissues were compared to non-tumour adjacent tissues to identify differentially expressed genes (DEGs), followed by performing systematic review on common identified DEGs. Fifty-eight common DEGs were identified from the analysis of 82 tumour tissue samples obtained from four gene expression datasets (NCBI GEO). These DEGS were then systematically searched for their roles in modulating EMT in CRC based on previously published studies. Following this, 10 common DEGs (CXCL1, CXCL8, MMP1, MMP3, MMP7, TACSTD2, VIP, HPGD, ABCG2, CLCA4) were included in this study and subsequently subjected to further bioinformatic analysis. Their roles and functions in modulating EMT in CRC were discussed in this review. This study enhances our understanding of the molecular mechanisms underlying EMT and uncovers potential candidate genes and pathways that could be targeted in CRC.

Prognostic value of oxidative stress-related genes in colorectal cancer and its correlation with tumor immunity

Oxidative stress (OS) plays an essential role in chronic diseases such as colorectal cancer (CRC). In this study, we aimed to explore the relation between oxidative stress-related genes and CRC prognosis and their involvement in the immune microenvironment. Totally 101 OS-related genes were selected from the MsigDB database. Then, univariate Cox regression was used to explore the prognostic value of the selected genes correlated with the CRC patient survival in the TCGA database. A total of 9 prognostic OS-related genes in CRC were identified. Based on consensus clustering, CRC patients were then categorized into two molecular subtypes. A prognostic risk model containing 8 genes was established using Lasso regression, and CRC patients were divided into high or low-risk groups based on the median risk scores. The predictive value of the 8 genes in CRC prognosis was validated using ROC curves, which indicate that CTNNB1, STK25, RNF112, SFPQ, MMP3, and NOL3 were promising prognostic biomarkers in CRC. Furthermore, the immune cell infiltration levels in different risk groups or CRC subtypes were analyzed. We found that the high-risk or C1 subtype had immunosuppressive microenvironment, which might explain the unfavorable prognosis in the two groups of CRC patients. Additionally, functional experiments were conducted to investigate the effects of OS-related genes on CRC cell proliferation, stemness, and apoptosis. We found that CTNNB1, HSPB1, MMP3, and NOL3 were upregulated in CRC tissues and cells. Knockdown of CTNNB1, HSPB1, MMP3, and NOL3 significantly suppressed CRC cell proliferation, stemness and facilitated CRC cell apoptosis. In conclusion, we established prognostic CRC subtypes and an eight-gene risk model, which may provide novel prognostic indicators and benefit the design of individualized therapeutic strategies for CRC patients.

Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation

Colorectal cancer (CRC) liver metastasis accounts for the majority of fatalities associated with CRC. Early detection of metastasis is crucial for improving patient outcomes but can be delayed due to a lack of symptoms. In this research, we aimed to investigate CRC metastasis-related biomarkers by employing a machine learning (ML) approach and experimental validation. The gene expression profile of CRC patients with liver metastasis was obtained using the GSE41568 dataset, and the differentially expressed genes between primary and metastatic samples were screened. Subsequently, we carried out feature selection to identify the most relevant DEGs using LASSO and Penalized-SVM methods. DEGs commonly selected by these methods were selected for further analysis. Finally, the experimental validation was done through qRT-PCR. 11 genes were commonly selected by LASSO and P-SVM algorithms, among which seven had prognostic value in colorectal cancer. It was found that the expression of the MMP3 gene decreases in stage IV of colorectal cancer compared to other stages (P value < 0.01). Also, the expression level of the WNT11 gene was observed to increase significantly in this stage (P value < 0.001). It was also found that the expression of WNT5a, TNFSF11, and MMP3 is significantly lower, and the expression level of WNT11 is significantly higher in liver metastasis samples compared to primary tumors. In summary, this study has identified a set of potential biomarkers for CRC metastasis using ML algorithms. The findings of this research may provide new insights into identifying biomarkers for CRC metastasis and may potentially lay the groundwork for innovative therapeutic strategies for treatment of this disease.

MMP12 serves as an immune cell-related marker of disease status and prognosis in lung squamous cell carcinoma

Background

Worldwide, lung squamous cell carcinoma (LUSC) has wreaked havoc on humanity. Matrix metallopeptidase 12 (MMP12) plays an essential role in a variety of cancers. This study aimed to reveal the expression, clinical significance, and potential molecular mechanisms of MMP12 in LUSC.

Methods

There were 2,738 messenger RNA (mRNA) samples from several multicenter databases used to detect MMP12 expression in LUSC, and 125 tissue samples were validated by immunohistochemistry (IHC) experiments. Receiver operator characteristic (ROC) curves, Kaplan-Meier curves, and univariate and multivariate Cox regression analyses were used to assess the clinical value of MMP12 in LUSC. The potential molecular mechanisms of MMP12 were explored by gene enrichment analysis and immune correlation analysis. Furthermore, single-cell sequencing was used to determine the distribution of MMP12 in multiple tumor microenvironment cells.

Results

MMP12 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 3.13, 95% CI [2.51-3.75]), which was verified at the protein level (p < 0.001) by internal IHC experiments. MMP12 expression could be used to differentiate LUSC samples from normal samples, and overexpression of MMP12 itself implied a worse clinical prognosis and higher levels of immune cell infiltration in LUSC patients. MMP12 was involved in cancer development and progression through two immune-related signaling pathways. The high expression of MMP12 in LUSC might act as an antigen-presenting cell-associated tumor neoantigen and activate the body's immune response.

Conclusions

MMP12 expression is upregulated in LUSC and high expression of MMP12 serves as a risk factor for LUSC patients. MMP12 may be involved in cancer development by participating in immune-related signaling pathways and elevating the level of immune cell infiltration.

Expression of Immune-Related and Inflammatory Markers and Their Prognostic Impact in Colorectal Cancer Patients

The tumor microenvironment of colorectal cancer (CRC) is heterogenous; thus, it is likely that multiple immune-related and inflammatory markers are simultaneously expressed in the tumor. The aim of this study was to identify immune-related and inflammatory markers expressed in freshly frozen CRC tissues and to investigate whether they are related to the clinicopathological features and prognosis of CRC. Seventy patients with CRC who underwent curative surgical resection between December 2014 and January 2017 were included in this study. Tissue samples were obtained from tumor and non-tumor areas in the patients' colons. The concentrations of immune-related markers (APRIL/TNFSF13, BAFF, LAG-3, PD-1, PD-L1, and CTLA-4) and inflammatory markers (CHIT, MMP-3, osteocalcin, pentraxin-3, sTNF-R1, and sTNF-R2) in the samples were measured using the Bio-plex Multiplex Immunoassay system. The concentrations of APRIL/TNFSF13, BAFF, and MMP-3 in the samples were significantly high; thus, we conducted analyses based on the cut-off values for these three markers. The high-APRIL/TNFSH13-expression group showed a significantly higher rate of metastatic lesions than the low-expression group, whereas the high-MMP-3-expression group had higher CEA levels, more lymph node metastases, and more advanced disease stages than the low-expression group. The five-year disease-free survival of the high-MMP-3-expression group was significantly shorter than that of the low-expression group (65.1% vs. 90.2%, p = 0.033). This study provides evidence that the APRIL/TNFSF13, BAFF, and MMP-3 pathway is overexpressed in CRC tissues and is associated with unfavorable clinicopathological features and poor prognosis in CRC patients. These markers could serve as diagnostic or prognostic biomarkers for CRC.

Prognostic risk factors of serous ovarian carcinoma based on mesenchymal stem cell phenotype and guidance for therapeutic efficacy

BACKGROUND

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in which serous ovarian carcinoma (SOC) is the most common histological subtype. Although PARP inhibitors (PARPi) and antiangiogenics have been accepted as maintenance treatment in SOC, response to immunotherapy of SOC patients is limited.

METHODS

The source of transcriptomic data of SOC was from the Cancer Genome Atlas database and Gene Expression Omnibus. The abundance scores of mesenchymal stem cells (MSC scores) were estimated for each sample by xCell. Weighted correlation network analysis is correlated the significant genes with MSC scores. Based on prognostic risk model construction with Cox regression analysis, patients with SOC were divided into low- and high-risk groups. And distribution of immune cells, immunosuppressors and pro-angiogenic factors in different risk groups was achieved by single-sample gene set enrichment analysis. The risk model of MSC scores was further validated in datasets of immune checkpoint blockade and antiangiogenic therapy. In the experiment, the mRNA expression of prognostic genes related to MSC scores was detected by real-time polymerase chain reaction, while the protein level was evaluated by immunohistochemistry.

RESULTS

Three prognostic genes (PER1, AKAP12 and MMP17) were the constituents of risk model. Patients classified as high-risk exhibited worse prognosis, presented with an immunosuppressive phenotype, and demonstrated high micro-vessel density. Additionally, these patients were insensitive to immunotherapy and would achieve a longer overall survival with antiangiogenesis treatment. The validation experiments showed that the mRNA of PER1, AKAP12, and MMP17 was highly expressed in normal ovarian epithelial cells compared to SOC cell lines and there was a positive correlation between protein levels of PER1, AKAP12 and MMP17 and metastasis in human ovarian serous tumors.

CONCLUSION

This prognostic model established on MSC scores can predict prognosis of patients and provide the guidance for patients receiving immunotherapy and molecular targeted therapy. Because the number of prognostic genes was fewer than other signatures of SOC, it will be easily accessible on clinic.

MMP14 is a diagnostic gene of intrahepatic cholangiocarcinoma associated with immune cell infiltration

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is a malignant tumor of the hepatobiliary system with concealed onset, strong invasiveness and poor prognosis.

AIM

To explore the disease characteristic genes that may be helpful in the diagnosis of ICC and affect immune cell infiltration.

METHODS

We downloaded two ICC-related human gene expression profiles from GEO database as the training group (GSE26566 and GSE32958 datasets) for difference analysis, and performed enrichment analysis on differential genes. The least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF), three machine learning algorithms, were used to screen the characteristic genes. Double verification was carried out on GSE107943 and The Cancer Genome Atlas, two verification groups. Receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the diagnostic efficacy of genes for ICC. CIBERSORT and ssGSEA algorithms were used to evaluate the effect of characteristic genes on immune infiltration pattern. Human Protein Atlas (HPA) was used to analyze the protein expression level of the target gene.

RESULTS

A total of 1091 differential genes were obtained in the training group. Enrichment analysis showed that the above genes were mainly enriched in small molecular catabolism, complement and coagulation cascade, bile secretion and other functions and pathways. Twenty-five characteristic genes were screened by LASSO regression, 19 by SVM-RFE algorithm, and 30 by RF algorithm. Three algorithms were used in combination to determine the characteristic gene of ICC: MMP14. The verification group confirmed that the genes had a high diagnostic accuracy (AUC values of the training group and the verification group were 0.960, 0.999, and 0.977, respectively). Comprehensive analysis of immune infiltration showed that MMP14 could affect the infiltration of monocytes, activated memory CD4 T cells, resting memory CD4 T cells, and other immune cells, and was closely related to the expression of CD200, cytotoxic T-lymphocyte-associated antigen 4, CD14, CD44, and other immune checkpoints. The results of immunohistochemistry in HPA database showed was indeed overexpressed in ICC.

CONCLUSION

MMP14 can be used as a disease characteristic gene of ICC, and may regulate the distribution of immune-infiltrating cells in the ICC tumor microenvironment, which provides a new method for the determination of ICC diagnostic markers and screening of therapeutic targets.

CXCL1 promotes colon cancer progression through activation of NF-κB/P300 signaling pathway

BACKGROUND

The upregulated expression of CXCL1 has been validated in colorectal cancer patients. As a potential biotherapeutic target for colorectal cancer, the mechanism by which CXCL1 affects the development of colorectal cancer is not clear.

METHODS

Expression data of CXCL1 in colorectal cancer were obtained from the GEO database and verified using the GEPIA database and the TIMER 2.0 database. Knockout and overexpression of CXCL1 in colorectal cancer cells by CRISPR/Cas and "Sleeping Beauty" transposon-mediated gene editing techniques. Cell biological function was demonstrated by CCK-8, transwell chamber and Colony formation assay. RT-qPCR and Western Blot assays measured RNA and protein expression. Protein localization and expression were measured by immunohistochemistry and immunofluorescence.

RESULTS

Bioinformatics analysis showed significant overexpression of CXCL1 in the colorectal cancer tissues compared to normal human tissues, and identified CXCL1 as a potential therapeutic target for colorectal cancer. We demonstrate that CXCL1 promotes the proliferation and migration of colon cancer cells and has a facilitative effect on tumor angiogenesis. Furthermore, CXCL1 elevation promoted the migration of M2-tumor associated macrophages (TAMs) while disrupting the aggregation of CD4+ and CD8+ T cells at tumor sites. Mechanistic studies suggested that CXCL1 activates the NF-κB pathway. In the in vivo colon cancer transplantation tumor model, treatment with the P300 inhibitor C646 significantly inhibited the growth of CXCL1-overexpressing colon cancer.

CONCLUSION

CXCL1 promotes colon cancer development through activation of NF-κB/P300, and that CXCL1-based therapy is a potential novel strategy to prevent colon cancer development.

Transcriptome profile of spleen tissues from locally-adapted Kenyan pigs (Sus scrofa) experimentally infected with three varying doses of a highly virulent African swine fever virus genotype IX isolate: Ken12/busia.1 (ken-1033)

Background

African swine fever (ASF) is a lethal hemorrhagic disease affecting domestic pigs resulting in up to 100% mortality rates caused by the ASF virus (ASFV). The locally-adapted pigs in South-western Kenya have been reported to be resilient to disease and harsh climatic conditions and tolerate ASF; however, the mechanisms by which this tolerance is sustained remain largely unknown. We evaluated the gene expression patterns in spleen tissues of these locally-adapted pigs in response to varying infective doses of ASFV to elucidate the virus-host interaction dynamics.

Methods

Locally adapted pigs (n = 14) were experimentally infected with a high dose (1x10⁶HAD₅₀), medium dose (1x10⁴HAD₅₀), and low dose (1x10²HAD₅₀) of the highly virulent genotype IX ASFV Ken12/busia.1 (Ken-1033) isolate diluted in PBS and followed through the course of infection for 29 days. The in vivo pig host and ASFV pathogen gene expression in spleen tissues from 10 pigs (including three from each infective group and one uninfected control) were analyzed in a dual-RNASeq fashion. We compared gene expression between three varying doses in the host and pathogen by contrasting experiment groups against the naïve control.

Results

A total of 4954 differentially expressed genes (DEGs) were detected after ASFV Ken12/1 infection, including 3055, 1771, and 128 DEGs in the high, medium, and low doses, respectively. Gene ontology and KEGG pathway analysis showed that the DEGs were enriched for genes involved in the innate immune response, inflammatory response, autophagy, and apoptosis in lethal dose groups. The surviving low dose group suppressed genes in pathways of physiopathological importance. We found a strong association between severe ASF pathogenesis in the high and medium dose groups with upregulation of proinflammatory cytokines and immunomodulation of cytokine expression possibly induced by overproduction of prostaglandin E synthase (4-fold; p < 0.05) or through downregulation of expression of M1-activating receptors, signal transductors, and transcription factors. The host-pathogen interaction resulted in induction of expression of immune-suppressive cytokines (IL-27), inactivation of autophagy and apoptosis through up-regulation of NUPR1 [5.7-fold (high dose) and 5.1-fold (medium dose) [p < 0.05] and IL7R expression. We detected repression of genes involved in MHC class II antigen processing and presentation, such as cathepsins, SLA-DQB1, SLA-DOB, SLA-DMB, SLA-DRA, and SLA-DQA in the medium and high dose groups. Additionally, the host-pathogen interaction activated the CD8⁺ cytotoxicity and neutrophil machinery by increasing the expression of neutrophils/CD8⁺ T effector cell-recruiting chemokines (CCL2, CXCL2, CXCL10, CCL23, CCL4, CXCL8, and CXCL13) in the lethal high and medium dose groups. The recovered pigs infected with ASFV at a low dose significantly repressed the expression of CXCL10, averting induction of T lymphocyte apoptosis and FUNDC1 that suppressed neutrophilia.

Conclusions

We provide the first in vivo gene expression profile data from locally-adapted pigs from south-western Kenya following experimental infection with a highly virulent ASFV genotype IX isolate at varying doses that mimic acute and mild disease. Our study showed that the locally-adapted pigs induced the expression of genes associated with tolerance to infection and repression of genes involved in inflammation at varying levels depending upon the ASFV dose administered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08754-8.

Pan-Cancer Analysis Identified Homologous Recombination Factor With OB-Fold (HROB) as a Potential Biomarker for Various Tumor Types

Background: By recruiting the MCM8–MCM9 helicase to DNA damage site, the Homologous Recombination Factor With OB-Fold (HROB) is involved in the repair of inter-strand crosslink and homologous recombination. Previous studies have shown that HROB may play an oncogenic role by promoting cell proliferation and chemoresistance in several tumor types. However, the potential diagnostic and prognostic values of HROB have not been systemically explored in pan-cancer.

Methods: We analyzed the expression pattern of HROB among tumor tissues and normal tissues in several public databases, including Human Protein Atlas and the Cancer Genome Atlas (TCGA) and investigated the association between the HROB expression and pathological stage and patient prognosis. We also analyzed the association between HROB expression and cancer stemness and immune infiltration of cancer-associated fibroblasts (CAFs) and CD8⁺ T cells in pan-cancer. Finally, we explored the potential biological function of HROB through pathway enrichment analysis.

Results: In most tumor types, HROB is overexpressed in tumor tissues compared with non-tumor tissues. High HROB expression was correlated with poor prognosis and advanced pathological stages. HROB expression was robustly correlated with cancer stemness. Moreover, significant correlations between CAFs, CD8⁺ T-cell infiltration, and HROB expression were observed in several tumor types. Pathway enrichment analysis revealed that cell cycle and mitotic-regulated pathways were strongly enriched in HROB co-expressed genes.

Conclusion: HROB may be a potential diagnostic and prognostic biomarker in pan-cancer, which may play a role in tumorigenesis and disease progression by affecting the cancer stemness of tumor tissues and immune cell infiltration.

Integrated Whole-Transcriptome Profiling and Bioinformatics Analysis of the Polypharmacological Effects of Ganoderic Acid Me in Colorectal Cancer Treatment

Ganoderic acid Me (GA-Me) is a natural bioactive compound derived from Ganoderma lucidum. Our present results suggested that GA-Me inhibited proliferation, induced DNA fragmentation and significantly activated caspase-9 and caspase-3 in HCT116 cells. As shown in our previous studies, GA-Me targets several genes to prevent cancer, including colorectal cancer (CRC). Thus, we hypothesized that GA-Me might be a multitarget ligand against cancer. However, its exact mechanism in CRC remains unclear. Here, whole-transcriptome sequencing was employed to assess the long noncoding RNA (lncRNA), circular RNA (circRNA), microRNA (miRNA), and messenger RNA (mRNA) profiles of GA-Me-treated HCT116 cells. In total, 1572 differentially expressed (DE) lncRNAs, 123 DEcircRNAs, 87 DEmiRNAs, and 1508 DEmRNAs were identified. DCBLD2 and RAPGEF5 were validated as two core mRNAs in the DElncRNA, DEcircRNA, and DEmiRNA networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed the biological functions and potential mechanisms of TCONS-00008997, XR-925056.2, circRNA-07908, hsa-miR-100-3p, hsa-miR-1257, hsa-miR-3182, NAV3, ADAM20, and STARD4, which were altered after GA-Me treatment. The regulatory relationships of the XR-925056.2-hsa-miR-3182-NAV3/ADAM20/STARD4, circRNA-07908|Chr22:38986298-39025349-hsa-miR-3182-NAV3/ADAM20, ENST00000414039/ENST00000419190-novel874_mature-MMP9 and circRNA-00314|Chr1:35470863-35479212/circRNA-05460|Chr17:72592203-72649268-novel874_mature-MMP9 immune-regulatory networks involved both noncoding RNAs (ncRNAs) and mRNAs. Molecular docking studies showed that Zn²⁺ and the His201, His205, His211, Glu202, and Ala165 residues of MMP2 contributed to its high affinity for GA-Me. Zn²⁺ and the Glu402 and Gly186 residues of MMP9 are important for its interaction with GA-Me. Our results suggested and confirmed that GA-Me is a potential multitarget lead compound for CRC treatment with unique polypharmacological advantages.

Mass-Encoded Suspension Array for Multiplex Detection of Matrix Metalloproteinase Activities

This work designed a mass spectrometric biosensing strategy for the multiplex detection of matrix metalloproteinases (MMPs) with a mass-encoded suspension array. This array was fabricated as multiplex sensing probes by functionalizing magnetic beads with MMP-specific peptide-isobaric tags for relative and absolute quantification (iTRAQ) conjugates, which contained a hexahistidine tag for surface binding, a substrate region for MMP cleavage, and a coding region for the specific MMP. The integration of the multiplex coding ability of iTRAQ with ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and the proteolysis method for peptide digestion endowed the biosensing method with high throughput and ultrahigh sensitivity. This strategy could be conveniently performed by mixing the sample and the suspension array for enzymatic reactions and then digesting the uncleaved peptides with trypsin to release the coding regions for UPLC-MS/MS analysis. With MMP-2 and MMP-7 as analytes, the relative changes of peak area ratios of coding regions showed good linear responses in the ranges of 0.2-100 and 0.5-400 ng mL^-1, with detection limits of 0.064 and 0.17 ng mL^-1, respectively. The analysis of MMP activity in serum samples and its change responding to inhibitors demonstrated the specificity, practicability, and expansibility of the proposed strategy. This work paves a new avenue for the activity assays of multiplex enzymes and promotes the development of mass spectrometric biosensing.

Colorectal Cancer Cell Differentiation Trajectory Predicts Patient Immunotherapy Response and Prognosis

Objectives

This study aimed to investigate the differentiation state and clinical significance of colorectal cancer cells, as well as to predict the immune response and prognosis of patients based on differentiation-related genes of colorectal cancer.

Introduction

Colorectal cancer cells exhibit different differentiation states under the influence of the tumor microenvironment, which determines the cell fates.

Methods

We combined single-cell sequencing (scRNA-seq) data from The Cancer Genome Atlas source with extensive transcriptome data from the Gene Expression Omnibus database. We obtained colorectal cancer differentiation-related genes using cell trajectory analysis and developed a colorectal cancer differentiation-related gene based molecular typing and prognostic model to predict the immune response and prognosis of patients with colorectal cancer.

Results

We identified 5 distinct cell differentiation subsets and 620 colorectal cancer differentiation-related genes. Colorectal cancer differentiation-related genes were significantly associated with metabolism, angiogenesis, and immunity. We separated patients into 3 subtypes based on colorectal cancer differentiation-related gene expression in the tumor and found differences among the different subtypes in immune infiltration status, immune checkpoint gene expression, clinicopathological features, and overall survival. Immunotherapeutic interventions involving a highly expressed immune checkpoint blockade may be selectively effective in the corresponding cancer subtypes. We built a risk score prediction model (5-year AUC: .729) consisting of the 4 most important predictors of survival (TIMP1, MMP1, LGALS4, and ITLN1). Finally, we generated and validated a nomogram consisting of the risk score and clinicopathological variables.

Conclusion

This study highlights the significance of genes involved in cell differentiation for clinical prognosis and immunotherapy in patients and provides prospective therapeutic targets for colorectal cancer.