Identification and clinical validation of metastasis-associated biomarkers based on large-scale samples in colon-adenocarcinoma

SIRT5-mediated desuccinylation of PPA2 enhances HIF-1alpha-dependent adaptation to hypoxic stress and colorectal cancer metastasis

Metastasis is the primary cause of death in patients with colorectal cancer (CRC). Hypoxia is a hallmark of solid tumors that promotes cellular metabolic adaptation and dissemination. However, the mechanisms linking hypoxia-regulated metabolic adaptation to CRC metastasis remain unclear. Here, we found that inorganic pyrophosphatase 2 (PPA2) suppresses metastatic progression of CRC via its phosphatase function. PPA2 expression levels are reduced in CRC specimen and correlate with enhanced response to hypoxia by promoting hypoxia-inducible factor-1 (HIF-1) signaling to promote CRC cell glycolysis and dissemination. Mechanistically, PPA2 decreases HIF-1alpha stability through non-canonical ubiquitin-mediated proteasomal degradation via recruitment of E3 ligase NEDD4. Furthermore, PPA2 directly dephosphorylates NEDD4 at threonine 758 residue, resulting in its activation. Under hypoxic stress, NAD-dependent protein deacetylase sirtuin-5 promotes the dissociation of PPA2 and NEDD4 by inducing PPA2 desuccinylation at lysine 176, contributing to the improved stability of HIF-1alpha under hypoxic conditions. Our findings reveal a tumor-suppressive role of PPA2 in HIF-1alpha-dependent colorectal cancer, providing a potential therapeutic target and prognostic strategy.

Heme-thiolate monooxygenase cytochrome P450 1B1, an old dog with many new tricks

Cytochrome P450 CYP1B1 is a heme-thiolate monooxygenase traditionally recognized for its xenobiotic functions and extrahepatic expressions. Recent studies have suggested that CYP1B1 is also expressed in hepatic stellate cells, immune cells, endothelial cells, and fibroblasts within the tumor microenvironment, as well as tumor cells themselves. CYP1B1 is responsible for the metabolism of a wide range of substrates, including xenobiotics such as drugs, environmental chemicals, and endobiotics such as steroids, retinol, and fatty acids. Consequently, CYP1B1 and its associated exogenous and endogenous metabolites have been critically implicated in the pathogenesis of many diseases. Understanding the mode of action of CYP1B1 in different pathophysiological conditions and developing pharmacological inhibitors that allow for systemic or cell type-specific modulation of CYP1B1 may pave the way for novel therapeutic opportunities. This review highlights the significant role of CYP1B1 in maintaining physiological homeostasis and provides a comprehensive discussion of recent advancements in our understanding of CYP1B1's involvement in the pathogenesis of diseases such as fibrosis, cancer, glaucoma, and metabolic disorders. Finally, the review emphasizes the therapeutic potential of targeting CYP1B1 for drug development, particularly in the treatment and prevention of cancers and liver fibrosis. SIGNIFICANCE STATEMENT: CYP1B1 plays a critical role in various physiological processes. Dysregulation or genetic mutations of the gene encoding this enzyme can lead to health complications and may increase the risk of diseases such as cancer and liver fibrosis. In this review, we summarize recent preclinical and clinical evidence that underscores the potential of CYP1B1 as a therapeutic target.

Identification of novel diagnostic biomarkers associated with liver metastasis in colon adenocarcinoma by machine learning

BACKGROUND

Liver metastasis is one of the primary causes of poor prognosis in colon adenocarcinoma (COAD) patients, but there are few studies on its biomarkers.

METHODS

The Cancer Genome Atlas (TCGA)-COAD, GSE41258, and GSE49355 datasets were acquired from the public database. Differentially expressed genes (DEGs) between liver metastasis and primary tumor samples in COAD were identified by limma, and functional enrichment analysis were performed. MuTect2 and maftools were used to measure somatic mutation rates, while ADTEx was used to measure copy number variations (CNVs). The intersection of three machine learning methods, support vector machine (SVM), Random Forest, and least absolute shrinkage and selection operator (LASSO), is utilized to screen biomarkers, and their diagnostic performance is subsequently validated. The correlation between biomarkers and immune cells infiltration was analyzed by Spearman method.

RESULTS

47 DEGs between liver metastasis and primary tumor samples in COAD were obtained, which were mainly enriched in the complement and coagulation, extracellular matrix (ECM), and peptidase regulator activity, etc. 38 out of 47 DEGs had mutations and exhibited a high frequency of CNV amplification or deletion. Furthermore, 3 biomarkers (MMP3, MAB21L2, and COLEC11) were screened, which showed good diagnostic performance. The proportion of multiple immune cells, such as B cells naive, T cells CD4 naive, Monocytes, and Dendritic cells resting, was higher in liver metastasis samples than that in primary tumor samples. Meanwhile, MMP3, MAB21L2, and COLEC11 exhibited an outstanding correlation with immune cells infiltration.

CONCLUSION

In short, 3 biomarkers with good diagnostic efficacy were identified, providing a new perspective of therapeutic targets for liver metastasis in COAD.

METTL3-mediated m6A modification of CDCA7 mRNA promotes COAD progression

BACKGROUND

Colon adenocarcinoma (COAD) represents a frequent malignant tumor of the digestive system with high mortality and poor prognosis. As a prevalent internal mRNA modification in eukaryotic cells, N6-methyladenosine (m6A) has been reported to participate in tumor malignancy. This study is designed to explore the role and mechanism of Methyltransferase-like 3 (METTL3) in the progression of COAD.

METHODS

In this research, the GEPIA database was applied to analyze the relationship between COAD and cell division cycle-associated protein 7 (CDCA7) or METTL3. Cell viability, cell cycle progression, apoptosis, migration, and invasion were detected by Cell Counting Kit-8 (CCK-8), flow cytometry, transwell assays. The glycolysis level was detected via specific kits. CDCA7, E-cadherin, N-cadherin, and METTL3 protein levels were determined by western blot assay. The biological role of CDCA7 on COAD tumor growth was examined by the xenograft tumor model in vivo. After RBPsuite analysis, the interaction between METTL3 and CDCA7 was verified by methylated RNA immunoprecipitation (MeRIP).

RESULTS

METTL3 and CDCA7 were highly expressed in COAD tissues and cells. Furthermore, the silencing of CDCA7 hindered COAD cell proliferation, migration, invasion, glycolysis, EMT, and promoted apoptosis in vitro, as well as retarded tumor growth in vivo. At the molecular level, METTL3 might enhance the stability of CDCA7 mRNA via m6A methylation.

CONCLUSION

METTL3 contributes to the malignant progression of COAD cells partly by regulating the stability of CDCA7 mRNA, providing a promising therapeutic target for COAD treatment.

SLC14A1 and TGF-β signaling: a feedback loop driving EMT and colorectal cancer metachronous liver metastasis

BACKGROUND

Colorectal cancer (CRC) metachronous liver metastasis is a significant clinical challenge, largely attributable to the late detection and the intricate molecular mechanisms that remain poorly understood. This study aims to elucidate the role of Solute Carrier Family 14 Member 1 (SLC14A1) in the pathogenesis and progression of CRC metachronous liver metastasis.

METHODS

We conducted a comprehensive analysis of CRC patient data from The Cancer Genome Atlas and GSE40967 databases, focusing on the differential expression of genes associated with non-metachronous liver metastasis and metachronous liver metastasis. Functional assays, both in vitro and in vivo, were performed to assess the biological impact of SLC14A1 modulation in CRC cells. Gene set enrichment analysis, molecular assays and immunohistochemical analyses on clinical specimens were employed to unravel the underlying mechanisms through which SLC14A1 exerts its effects.

RESULTS

SLC14A1 was identified as a differentially expressed gene, with its overexpression significantly correlating with poor relapse-free and overall survival. Mechanistically, elevated SLC14A1 levels enhanced CRC cell invasiveness and migratory abilities, corroborated by upregulated TGF-β/Smad signaling and Epithelial-Mesenchymal Transition. SLC14A1 interacted with TβRII and stabilized TβRII protein, impeding its Smurf1-mediated K48-linked ubiquitination and degradation, amplifying TGF-β/Smad signaling. Furthermore, TGF-β1 reciprocally elevated SLC14A1 mRNA expression, with Snail identified as a transcriptional regulator, binding downstream of SLC14A1's transcription start site, establishing a positive feedback loop. Clinically, SLC14A1, phosphorylated Smad2, and Snail were markedly upregulated in CRC patients with metachronous liver metastasis, underscoring their potential as prognostic markers.

CONCLUSIONS

Our findings unveil SLC14A1 as a critical regulator in CRC metachronous liver metastasis, providing novel insights into the molecular crosstalk between SLC14A1 and TGF-β/Smad signaling. These discoveries not only enhance our understanding of CRC metachronous liver metastasis pathogenesis, but also highlight SLC14A1 as a promising target for therapeutic intervention and predictive marker.

Predicting potential therapeutic targets and small molecule drugs for early-stage lung adenocarcinoma

Lung cancer is a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) constituting the majority, and its main subtype being lung adenocarcinoma (LUAD). Despite substantial advances in LUAD diagnosis and treatment, early diagnostic biomarkers inadequately fulfill clinical requirements. Thus, we conducted bioinformatics analysis to identify potential biomarkers and corresponding therapeutic drugs for early-stage LUAD patients. Here we identified a total of 10 differentially expressed genes (DEGs) with survival significance through the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Subsequently, we identified a promising small molecule drug, Aminopurvalanol A, based on the 10 key genes using the L1000FWD application, which was validated by molecular docking followed by in vivo and in vitro experiments. The results highlighted TOP2A, CDH3, ASPM, CENPF, SLC2A1, and PRC1 as potential detection biomarkers for early LUAD. We confirmed the efficacy and safety of Aminopurvalanol A, providing valuable insights for the clinical management of LUAD.

Modification patterns and metabolic characteristics of m6A regulators in digestive tract tumors

M6A is essential for tumor occurrence and progression. The expression patterns of m6A regulators differ in various kinds of tumors. Transcriptomic expression statistics together with clinical data from a database were analyzed to distinguish patients with digestive tract tumors. Based on the expression patterns of diverse m6A regulators, patients were divided into several clusters. Survival analysis suggested significant differences in patient prognosis among the m6A clusters. The results showed overlapping of m6A expression patterns with energy metabolism and nucleotide metabolism. Functional analyses imply that m6A modifications in tumor cells probably drive metabolic reprogramming to sustain rapid proliferation of cancer cells. Our analysis highlights the m6A risk characterizes various kinds of metabolic features and predicts chemotherapy sensitivity in digestive tract tumors, providing evidence for m6A regulators as markers to predict patient outcomes.

Enhancing the invasive traits of breast cancers by CYP1B1 via regulation of p53 to promote uPAR expression

Human cytochrome P450 1B1 (CYP1B1) catalyzes estrogen metabolism to produce metabolites that promote the progression of breast cancer. Since the invasive properties of cancer cells cause cancer relapse, which dramatically reduces patient survival, we investigated the new pro-invasive mechanism involving CYP1B1 in breast cancer. Exploring clinical data from invasive breast cancer patients revealed that CYP1B1 exhibits a potential correlation with urokinase-type plasminogen activator receptor (uPAR). Interestingly, uPAR mRNA expression was elevated in invasive breast cancer patients carrying TP53 genes with driver mutations, and our results showed that CYP1B1 activates the uPAR pathway following regulation of p53 according to its mutant status. CYP1B1 suppressed wild-type (WT) p53 whereas it induced the oncogenic gain-of-function mutant p53R280K, not only via transcriptional regulation but also the protein stabilization and activation following phosphorylation on Ser15 residue of p53R280K. Intriguingly, results from CYP1B1 polymorphic gene study and 4-hydroxyestradiol (4-OHE2) treatment showed that CYP1B1 regulates p53s and uPAR through its enzymatic activity. Furthermore, effects of DMBA and TMS on uPAR expression disappeared in HCT116p53-/- cells, indicating that p53 is critical for uPAR induction by CYP1B1. Collectively, our results demonstrate that CYP1B1 may reduce the relapse-free survival rate of breast cancer patients by inducing invasive traits in cancer cells via p53 regulation based on the mutation status of TP53 genes and further activation of the uPAR pathway. The elucidation of the previously unknown molecular mechanism of CYP1B1 may provide evidence for the development of effective anti-cancer therapeutic strategies that target the progression of cancer invasion.

Smoking induces WEE1 expression to promote docetaxel resistance in esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) patients have poor clinical outcomes, with an overall 5-year survival rate of 20%. Smoking is a significant risk factor for EAC. The role of WEE1, a nuclear kinase that negatively regulates the cell cycle in normal conditions, in EAC tumorigenesis and drug resistance is not fully understood. Immunohistochemistry staining shows significant WEE1 overexpression in human EAC tissues. Nicotine, nicotine-derived nitrosamine ketone, or 2% cigarette smoke extract treatment induces WEE1 protein expression in EAC, detected by western blot and immunofluorescence staining. qRT-PCR and reporter assay indicates that smoking induces WEE1 expression through miR-195-5p downregulation in EAC. ATP-Glo cell viability and clonogenic assay confirmed that WEE1 inhibition sensitizes EAC cells to docetaxel treatment in vitro. A TE-10 smoking machine with EAC patient-derived xenograft mouse model demonstrated that smoking induces WEE1 protein expression and resistance to docetaxel in vivo. MK-1775 and docetaxel combined treatment improves EAC patient-derived xenograft mouse survival in vivo. Our findings demonstrate, for the first time, that smoking-induced WEE1 overexpression through miRNA dysregulation in EAC plays an essential role in EAC drug resistance. WEE1 inhibition is a promising therapeutic method to overcome drug resistance and target treatment refractory cancer cells.

Correlation analysis of PBX family with immune invasion and drug sensitivity in colon adenocarcinoma

Objedtive

Pre-B cell leukemia (PBX) has been found to be associated with cancer, but poorly studied with colon adenocarcinoma (COAD). In this study, the correlation between PBX family and COAD pathogenesis and immune cytokine infiltration was further explored by analyzing online tumor databases, in order to find new biomarkers for the diagnosis of COAD.

Methods

The online database was used to analyze gene differential expression, methylation level, gene mutation rate, immune infiltration difference, drug sensitivity, and so on.

Results

PBX1 and PBX3 decreased in COAD. PBX2 and PBX4 increased. The expression of PBX1 and PBX2 in different clinical stages was different. PBX4 was valuable for the prognosis of COAD. PBX family has correlation between COAD and immune infiltration. PBX2 was correlated with different pathological stages. PBX3 had the highest gene mutation rate, followed by PBX1, PBX2 and PBX4. PBX1, PBX2 and PBX4 were correlated with the sensitivity of multiple drugs.

Conclusion

The PBX family is differentially expressed in COAD and has a genetic mutation, and its protein network is closely related to the HOX family and is associated with immune infiltration of COAD.

A novel prognostic gene set for colon adenocarcinoma relative to the tumor microenvironment, chemotherapy, and immune therapy

Background: Colon adenocarcinoma (COAD) is a common aggressive malignant tumor. Heterogeneity in tumorigenesis and therapy response leads to an unsatisfactory overall survival of colon adenocarcinoma patients. Our study aimed to identify tools for a better prediction of colon adenocarcinoma prognosis, bolstering the development of a better personalized treatment and management. Method: We used the least absolute shrinkage and selection operator (LASSO) Cox model to analyze the prognosis-related gene datasets from the Gene Expression Omnibus (GEO) database and verified them using The Cancer Genome Atlas (TCGA) database. The area under the curve (AUC) was calculated using the receiver operating characteristic (ROC) curve to evaluate the predictive ability of the risk score model. Gene Set Enrichment Analysis (GSEA) was used to identify the significantly enriched and depleted biological processes. The tumor immune dysfunction and exclusion (TIDE) algorithm was taken to explore the relationship between the risk score and immunotherapy. The observations collectively helped us construct a nomogram to predict prognosis. Finally, the correlation between drug sensitivity and prognostic gene sets was conducted based on the Cancer Therapeutics Response Portal (CTRP) analyses. Results: We constructed a scoring model to assess the significance of the prognosis risk-related gene signatures, which was relative to common tumor characteristics and tumor mutational burdens. Patients with a high-risk score had higher tumor stage and poor prognosis (p< 0.05). Moreover, the expressions of these genes were in correlation with changes in the tumor microenvironment (TME). The risk score is an independent prognostic factor for COAD (p< 0.05). The accuracy of the novel nomogram model with a risk score and TNM-stage prediction prognosis in the predicting prognosis was higher than that of the TNM stage. Further analysis showed that a high-risk score was associated with tumor immune rejection. Patients with a low-risk score have a better prognosis with chemotherapy than those with a high-risk score. Compared to patients in the high-risk group, patients in the low-risk group had a significant survival advantage after receiving chemotherapy. In addition, the prognostic gene sets aid the assessment of drug sensitivity. Conclusion: This study establishes a new prognostic model to better predict the clinical outcome and TME characteristics of colon adenocarcinoma. We believe, our model also serves as a useful clinical tool to strengthen the functioning of chemotherapy, immunotherapy, and targeted drugs.

Lipid metabolism characterization in gastric cancer identifies signatures to predict prognostic and therapeutic responses

Purpose: Increasing evidence has elucidated the significance of lipid metabolism in predicting therapeutic efficacy. Obviously, a systematic analysis of lipid metabolism characterizations of gastric cancer (GC) needs to be reported. Experimental design: Based on two proposed computational algorithms (TCGA-STAD and GSE84437), the lipid metabolism characterization of 367 GC patients and its systematic relationship with genomic characteristics, clinicopathologic features, and clinical outcomes of GC were analyzed in our study. Differentially expressed genes (DEGs) were identified based on the lipid metabolism cluster. At the same time, we applied single-factor Cox regression and random forest to screen signature genes to construct a prognostic model, namely, the lipid metabolism score (LMscore). Next, we deeply explored the predictive value of the LMscore for GC. To verify the specific changes in lipid metabolism, a total of 90 serum, 30 tumor, and non-tumor adjacent tissues from GC patients, were included for pseudotargeted metabolomics analysis via SCIEX triple quad 5500 LC-MS/MS system. Results: Five lipid metabolism signature genes were identified from a total of 3,104 DEGs. The LMscore could be a prognosticator for survival in different clinicopathological GC cohorts. As well, the LMscore was identified as a predictive biomarker for responses to immunotherapy and chemotherapeutic drugs. Additionally, significant changes in sphingolipid metabolism and sphingolipid molecules were discovered in cancer tissue from GC patients by pseudotargeted metabolomics. Conclusion: In conclusion, multivariate analysis revealed that the LMscore was an independent prognostic biomarker of patient survival and therapeutic responses in GC. Depicting a comprehensive landscape of the characteristics of lipid metabolism may help to provide insights into the pathogenesis of GC, interpret the responses of gastric tumors to therapies, and achieve a better outcome in the treatment of GC. In addition, significant alterations of sphingolipid metabolism and increased levels of sphingolipids, in particular, sphingosine (d16:1) and ceramide, were discovered in GC tissue by lipidome pseudotargeted metabolomics, and most of the sphingolipid molecules have the potential to be diagnostic biomarkers for GC.

Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.

Lipid Nanoparticle Delivery of Fas Plasmid Restores Fas Expression to Suppress Melanoma Growth In Vivo

Fas ligand (FasL), expressed on the surface of activated cytotoxic T lymphocytes (CTLs), is the physiological ligand for the cell surface death receptor, Fas. The Fas-FasL engagement initiates diverse signaling pathways, including the extrinsic cell death signaling pathway, which is one of the effector mechanisms that CTLs use to kill tumor cells. Emerging clinical and experimental data indicate that Fas is essential for the efficacy of CAR-T cell immunotherapy. Furthermore, loss of Fas expression is a hallmark of human melanoma. We hypothesize that restoring Fas expression in tumor cells reverses human melanoma resistance to T cell cytotoxicity. DNA hypermethylation, at the FAS promoter, down-regulates FAS expression and confers melanoma cell resistance to FasL-induced cell death. Forced expression of Fas in tumor cells overcomes melanoma resistance to FasL-induced cell death in vitro. Lipid nanoparticle-encapsulated mouse Fas-encoding plasmid therapy eliminates Fas⁺ tumor cells and suppresses established melanoma growth in immune-competent syngeneic mice. Similarly, lipid nanoparticle-encapsulated human FAS-encoding plasmid (hCOFAS01) therapy significantly increases Fas protein levels on tumor cells of human melanoma patient-derived xenograft (PDX) and suppresses the established human melanoma PDX growth in humanized NSG mice. In human melanoma patients, FasL is expressed in activated and exhausted T cells, Fas mRNA level positively correlates with melanoma patient survival, and nivolumab immunotherapy increases FAS expression in tumor cells. Our data demonstrate that hCOFAS01 is an effective immunotherapeutic agent for human melanoma therapy with dual efficacy in increasing tumor cell FAS expression and in enhancing CTL tumor infiltration.

Amino acid metabolism genes associated with immunotherapy responses and clinical prognosis of colorectal cancer

Based on amino acid metabolism-related genes (AAMRGs), this study aimed at screening out key prognosis-related genes and finding the underlying correlation between the amino acid metabolism and tumor immune microenvironment of colorectal cancer. A total of 448 amino acid metabolism-related genes were obtained from MsigDB. The risk signature was built based on differential expression genes, univariate Cox, and LASSO analyses with 403 patients’ data downloaded from the TCGA database. Survival analysis and independence tests were performed to confirm the validity of the risk signature. Single-sample gene set enrichment analysis (ssGSEA), tumor mutation burden (TMB), the score of tumor immune dysfunction and exclusion (TIDE), the immunophenoscore obtained from The Cancer Immunome Atlas database, and the IC50 of drugs were used to find the relationship among the risk signature, immune status, immunotherapy response, and drug sensitivity of colorectal cancer. We identified five amino acid metabolism-related genes for the construction of the risk signature, including ENOPH1, ACAT1, ALDH4A1, FAS, and ASPG. The low-risk group was significantly associated with a better prognosis (p &lt; 0.0001). In the entire set, the area under the curve (AUC) for 1, 3, and 5 years was 0.717, 0.734, and 0.764, respectively. We also discovered that the low-risk subgroup was related to more activity of immune cells, had higher expression of some immune checkpoints, and was more likely to benefit from immunotherapy. ssGSEA revealed that except the processes of glutamine histidine, lysine, tyrosine, and L-phenylalanine metabolism, the other amino acid metabolism pathways were more active in the samples with the low risk scores, whereas the activities of synthesis and transportation of most amino acids were similar. Hedgehog signaling, WNT/β-catenin signaling, mitotic, notch signaling, and TGF-β signaling were the top five pathways positively associated with the risk score. To sum up, AAMRGs were associated with the immune microenvironment of CRC patients and could be applied as biomarkers to predict the prognosis and immunotherapy response of patients.

A Prognostic Model for Colon Adenocarcinoma Patients Based on Ten Amino Acid Metabolism Related Genes

Background

Amino acid metabolism plays a vital role in cancer biology. However, the application of amino acid metabolism in the prognosis of colon adenocarcinoma (COAD) has not yet been explored. Here, we construct an amino acid metabolism-related risk model to predict the survival outcome of COAD and improve clinical decision making.

Methods

The RNA-sequencing-based transcriptome for 524 patients with COAD from The Cancer Genome Atlas (TCGA) was selected as a training set. The integrated Gene Expression Omnibus (GEO) dataset with 1,430 colon cancer samples was used for validation. Differential expression of amino acid metabolism-related genes (AAMRGs) was identified for prognostic gene selection. Univariate cox regression analysis, LASSO-penalized Cox regression analysis, and multivariate Cox regression analysis were applied to construct a prognostic risk model. Moreover, the correlation between risk score and microsatellite instability, immunotherapy response, and drug sensitivity were analyzed.

Results

A prognostic signature was constructed based on 10 AAMRGs, including ASPG, DUOX1, GAMT, GSR, MAT1A, MTAP, PSMD12, RIMKLB, RPL3L, and RPS17. Patients with COAD were divided into high-risk and low-risk group based on the medianrisk score. Univariate and multivariate Cox regression analysis revealed that AAMRG-related signature was an independent risk factor for COAD. Moreover, COAD patients in the low-risk group were more sensitive to immunotherapy targeting PD-1 and CTLA-4.

Conclusion

Our study constructed a prognostic signature based on 10 AAMRGs, which could be used to build a novel prognosis model and identify potential drug candidates for the treatment of COAD.

Identification and validation of a cigarette smoke-related five-gene signature as a prognostic biomarker in kidney renal clear cell carcinoma

Cigarette smoking greatly promotes the progression of kidney renal clear cell carcinoma (KIRC), however, the underlying molecular events has not been fully established. In this study, RCC cells were exposed to the tobacco specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK, nicotine-derived nitrosamine) for 120 days (40 passages), and then the soft agar colony formation, wound healing and transwell assays were used to explore characteristics of RCC cells. RNA-seq was used to explore differentially expressed genes. We found that NNK promoted RCC cell growth and migration in a dose-dependent manner, and RNA-seq explored 14 differentially expressed genes. In TCGA-KIRC cohort, Lasso regression and multivariate COX regression models screened and constructed a five-gene signature containing ANKRD1, CYB5A, ECHDC3, MT1E, and AKT1S1. This novel gene signature significantly associated with TNM stage, invasion depth, metastasis, and tumor grade. Moreover, when compared with individual genes, the gene signature contained a higher hazard ratio and therefore had a more powerful value for the prognosis of KIRC. A nomogram was also developed based on clinical features and the gene signature, which showed good application. Finally, AKT1S1, the most crucial component of the gene signature, was significantly induced after NNK exposure and its related AKT/mTOR signaling pathway was dramatically activated. Our findings supported that NNK exposure would promote the KIRC progression, and the novel cigarette smoke-related five-gene signature might serve as a highly efficient biomarker to identify progression of KIRC patients, AKT1S1 might play an important role in cigarette smoke exposure-induced KIRC progression.

Use of Omics Technologies for the Detection of Colorectal Cancer Biomarkers

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers with high mortality rates, especially when detected at later stages. Early detection of CRC can substantially raise the 5-year survival rate of patients, and different efforts are being put into developing enhanced CRC screening programs. Currently, the faecal immunochemical test with a follow-up colonoscopy is being implemented for CRC screening. However, there is still a medical need to describe biomarkers that help with CRC detection and monitor CRC patients. The use of omics techniques holds promise to detect new biomarkers for CRC. In this review, we discuss the use of omics in different types of samples, including breath, urine, stool, blood, bowel lavage fluid, or tumour tissue, and highlight some of the biomarkers that have been recently described with omics data. Finally, we also review the use of extracellular vesicles as an improved and promising instrument for biomarker detection.

Restoring FAS Expression via Lipid-Encapsulated FAS DNA Nanoparticle Delivery Is Sufficient to Suppress Colon Tumor Growth In Vivo

Simple Summary

A key feature of human colorectal tumor is loss of FAS expression. FAS is the death receptor for FASL of activated T cells. Loss of FAS expression therefore may promote tumor cell immune escape. We aimed at determining whether restoring FAS expression is sufficient to suppress colorectal tumor growth. Mouse and human FAS cDNA was synthesized and encapsulated into cationic lipid nanoparticle DOTAP-Cholesterol to formulate DOTAP-Chol-mFAS and DOTAP-Chol-hFAS, respectively. Restoring FAS expression in metastatic mouse colon-tumor cells enabled FASL-induced elimination of FAS⁺ tumor cells in vitro and suppressed colon-tumor growth and progression in tumor-bearing mice in vivo. Restoring FAS expression induced FAS receptor auto-oligomerization and tumor cell auto-apoptosis in metastatic human colon-tumor cells in vitro. DOTAP-Chol-hFAS therapy is also sufficient to suppress metastatic human colon tumor xenograft growth in athymic mice. Tumor-selective delivery of FAS DNA nanoparticle is potentially an effective therapy for human colorectal cancer.

Abstract

A hallmark of human colorectal cancer is lost expression of FAS, the death receptor for FASL of cytotoxic T lymphocytes (CTLs). However, it is unknown whether restoring FAS expression alone is sufficient to suppress csolorectal-cancer development. The FAS promoter is hypermethylated and inversely correlated with FAS mRNA level in human colorectal carcinomas. Analysis of single-cell RNA-Seq datasets revealed that FAS is highly expressed in epithelial cells and immune cells but down-regulated in colon-tumor cells in human colorectal-cancer patients. Codon usage-optimized mouse and human FAS cDNA was designed, synthesized, and encapsulated into cationic lipid to formulate nanoparticle DOTAP-Chol-mFAS and DOTAP-Chol-hFAS, respectively. Overexpression of codon usage-optimized FAS in metastatic mouse colon-tumor cells enabled FASL-induced elimination of FAS⁺ tumor cells in vitro, suppressed colon tumor growth, and increased the survival of tumor-bearing mice in vivo. Overexpression of codon-optimized FAS-induced FAS receptor auto-oligomerization and tumor cell auto-apoptosis in metastatic human colon-tumor cells. DOTAP-Chol-hFAS therapy is also sufficient to suppress metastatic human colon tumor xenograft growth in athymic mice. DOTAP-Chol-mFAS therapy exhibited no significant liver toxicity. Our data determined that tumor-selective delivery of FAS DNA nanoparticles is sufficient for suppression of human colon tumor growth in vivo.

Re-Clustering and Profiling of Digestive System Tumors According to Microenvironment Components

Background

Immunotherapy has become the most promising therapy in digestive system tumors besides conventional chemotherapy and radiotherapy. But only a few patients can benefit from different types of immunotherapies, such as immune checkpoint blockade (ICB). To identify these ICB-susceptible patients, methods are urgently needed to screen and profile subgroups of patients with different responsiveness to ICB.

Methods

This study carried out analysis on patients with digestive system tumors that were obtained from Cancer Genome Atlas (TCGA) cohorts. The analyses were mainly performed using GraphPad Prism 7 and R language.

Results

We have quantified the microenvironmental components of eight digestive system tumor patients in TCGA cohorts and evaluated their clinical value. We re-clustered patients based on their microenvironment composition and divided these patients into six clusters. The differences between these six clusters were profiled, including survival conditions, enriched biological processes, genomic mutations, and microenvironment traits. Cluster 3 was the most immune-related cluster, exhibiting a high infiltration of non-tumor components and poor survival status, along with an inhibitory immune status, and we found that patients with high stromal score indicated a poor response in ICB cohort.

Conclusions

Our research provides a new strategy based on the microenvironment components for the reclassification of digestive system tumors, which could provide guidance for prognosis judgment and treatment response prediction like ICB.

Weighted gene co-expression network analysis and drug-gene interaction bioinformatics uncover key genes associated with various presentations of malaria infection in African children and major drug candidates

Malaria is a fatal parasitic disease with unelucidated pathogenetic mechanism. Herein, we aimed to uncover genes associated with different clinical aspects of malaria based on the GSE1124 dataset that is publicly accessible by using WGCNA. We obtained 16 co-expression modules and their correlations with clinical features. Using the MCODE tool, we identified THEM4, STYX, VPS36, LCOR, KIAA1143, EEA1, RAPGEF6, LOC439994, ZBTB33, PTPN22, ESCO1, and KLF3 as hub genes positively associated with Plasmodium falciparum infection (ASPF). These hub genes were involved in the biological processes of endosomal transport, regulation of natural killer cell proliferation, and KEGG pathways of endocytosis and fatty acid elongation. For the purple module negatively correlated with ASPF, we identified 19 hub genes that were involved in the biological processes of positive regulation of cellular protein catabolic process and KEGG pathways of other glycan degradation. For the salmon module positively correlated with severe malaria anemia (SMA), we identified 17 hub genes that were among those driving the biological processes of positive regulation of erythrocyte differentiation. For the brown module positively correlated with cerebral malaria (CM), we identified eight hub genes and these genes participated in phagolysosome assembly and positive regulation of exosomal secretion, and animal mitophagy pathway. For the tan module negatively correlated with CM, we identified four hub genes that were involved in CD8-positive, alpha-beta T cell differentiation and notching signaling pathway. These findings may provide new insights into the pathogenesis of malaria and help define new diagnostic and therapeutic approaches for malaria patients.