TKI resistant-based prognostic immune related gene signature in LUAD, in which FSCN1 contributes to tumor progression

Identification of a DNA-methylome-based signature for prognosis prediction in driver gene-negative lung adenocarcinoma

"Driver gene-negative" lung adenocarcinoma (LUAD) was of rare treatment options and a poor prognosis. Presently, for them, few biomarkers are available for stratification analysis to make appropriate treatment strategy. This study aimed to develop a DNA-methylome-based signature to realize the precise risk-stratifying. Here, an Illumina MethylationEPIC Beadchip was applied to obtain differentially methylated CpG sites (DMCs). A four-CpG-based signature, named as TLA, was successfully established, whose prognosis-predicting power was well verified in one internal (n = 78) and other external (n = 110) validation cohorts. Patients with high-risk scores had shorter overall survival (OS) in all cohorts [hazard ratio (HR): 11.79, 5.16 and 2.99, respectively]. Additionally, it can effectively divide patients into low-risk and high-risk groups, with significantly different OS in the diverse subgroups stratified by the standard clinical parameters. As an independent prognostic factor, TLA may assist in improving the nomogram's 5-year OS-predicting ability (AUC 0.756, 95% CI:0.695-0.816), superior to TNM alone (AUC 0.644, 95% CI: 0.590-0.698). Additionally, the relationship of TLA-related genes, TAC1, LHX9, and ALX1, with prognosis and tumour invasion made them serve as potential therapy targets for driver gene-negative LUAD.

Integrated analysis reveals critical cisplatin-resistance regulators E2F7 contributed to tumor progression and metastasis in lung adenocarcinoma

BACKGROUND

Drug resistance poses a significant challenge in cancer treatment, particularly as a leading cause of therapy failure. Cisplatin, the primary drug for lung adenocarcinoma (LUAD) chemotherapy, shows effective treatment outcomes. However, the development of resistance against cisplatin is a major obstacle. Therefore, identifying genes resistant to cisplatin and adopting personalized treatment could significantly improve patient outcomes.

METHODS

By examining transcriptome data of cisplatin-resistant LUAD cells from the GEO database, 181 genes associated with cisplatin resistance were identified. Using univariate regression analysis, random forest and multivariate regression analyses, two prognostic genes, E2F7 and FAM83A, were identified. This study developed a prognostic model utilizing E2F7 and FAM83A as key indicators. The Cell Counting Kit 8 assay, Transwell assay, and flow cytometry were used to detect the effects of E2F7 on the proliferation, migration, invasiveness and apoptosis of A549/PC9 cells. Western blotting was used to determine the effect of E2F7 on AKT/mTOR signaling pathway.

RESULTS

This study has pinpointed two crucial genes associated with cisplatin resistance, E2F7 and FAM83A, and developed a comprehensive model to assist in the diagnosis, prognosis, and evaluation of relapse risk in LUAD. Analysis revealed that patients at higher risk, according to these genetic markers, had elevated levels of immune checkpoints (PD-L1 and PD-L2). The prognostic and diagnosis values of E2F7 and FAM83A were further confirmed in clinical data. Furthermore, inhibiting E2F7 in lung cancer cells markedly reduced their proliferation, migration, invasion, and increased apoptosis. In vivo experiments corroborated these findings, showing reduced tumor growth and lung metastasis upon E2F7 suppression in lung cancer models.

CONCLUSION

Our study affirms the prognostic value of a model based on two DEGs, offering a reliable method for predicting the success of tumor immunotherapy in patients with LUAD. The diagnostic and predictive model based on these genes demonstrates excellent performance. In vitro, reducing E2F7 levels shows antitumor effects by blocking LUAD growth and progression. Further investigation into the molecular mechanisms has highlighted E2F7's effect on the AKT/mTOR signaling pathway, underscoring its therapeutic potential. In the era of personalized medicine, this DEG-based model promises to guide clinical practice.

Identification of a 9-gene signature to enhance biochemical recurrence prediction in primary prostate cancer: A benchmarking study using ten machine learning methods and twelve patient cohorts

Prostate cancer (PCa) is a prevalent malignancy among men worldwide, and biochemical recurrence (BCR) after radical prostatectomy (RP) is a critical turning point commonly used to guide the development of treatment strategies for primary PCa. However, the clinical parameters currently in use are inadequate for precise risk stratification and informing treatment choice. To address this issue, we conducted a study that collected transcriptomic data and clinical information from 1662 primary PCa patients across 12 multicenter cohorts globally. We leveraged 101 algorithm combinations that consisted of 10 machine learning methods to develop and validate a 9-gene signature, named BCR SCR, for predicting the risk of BCR after RP. Our results demonstrated that BCR SCR generally outperformed 102 published prognostic signatures. We further established the clinical significance of these nine genes in PCa progression at the protein level through immunohistochemistry on Tissue Microarray (TMA). Moreover, our data showed that patients with higher BCR SCR tended to have higher rates of BCR and distant metastasis after radical radiotherapy. Through drug target prediction analysis, we identified nine potential therapeutic agents for patients with high BCR SCR. In conclusion, the newly developed BCR SCR has significant translational potential in accurately stratifying the risk of patients who undergo RP, monitoring treatment courses, and developing new therapies for the disease.

Pan-Cancer Proteomics Analysis Reveals Wiskott-Aldrich Syndrome Protein as a Potential Regulator of Programmed Death-Ligand 1

The programmed death-ligand 1 (PD-L1) is a key mediator of immunosuppression in the tumor microenvironment. The expression of PD-L1 in cancer cells is useful for the clinical determination of an immune checkpoint blockade (ICB). However, the regulatory mechanism of the PD-L1 abundance remains incompletely understood. Here, we integrated the proteomics of 52 patients with solid tumors and examined immune cell infiltration to reveal PD-L1-related regulatory modules. Wiskott-Aldrich syndrome protein (WASP) was identified as a potential regulator of PD-L1 transcription. In two independent cohorts containing 164 cancer patients, WASP expression was significantly associated with PD-L1. High WASP expression contributed to immunosuppressive cell composition, including cells positive for immune checkpoints (PD1, CTLA4, TIGIT, and TIM3), FoxP3+ Treg cells, and CD163+ tumor-associated macrophages. Overexpression of WASP increased, whereas knockdown of WASP decreased the protein level of PD-L1 in cancer cells without alteration of PD-L1 protein stability. The WASP-mediated cell migration and invasion were markedly attenuated by the silence of PD-L1. Collectively, our data suggest that WASP is a potential regulator of PD-L1 and the WASP/PD-L1 axis is responsible for cell migration and an immunosuppressive microenvironment.

CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity

Drug therapy is vital in cancer treatment. Accurate analysis of drug sensitivity for specific cancers can guide healthcare professionals in prescribing drugs, leading to improved patient survival and quality of life. However, there is a lack of web-based tools that offer comprehensive visualization and analysis of pancancer drug sensitivity. We gathered cancer drug sensitivity data from publicly available databases (GEO, TCGA and GDSC) and developed a web tool called Comprehensive Pancancer Analysis of Drug Sensitivity (CPADS) using Shiny. CPADS currently includes transcriptomic data from over 29 000 samples, encompassing 44 types of cancer, 288 drugs and more than 9000 gene perturbations. It allows easy execution of various analyses related to cancer drug sensitivity. With its large sample size and diverse drug range, CPADS offers a range of analysis methods, such as differential gene expression, gene correlation, pathway analysis, drug analysis and gene perturbation analysis. Additionally, it provides several visualization approaches. CPADS significantly aids physicians and researchers in exploring primary and secondary drug resistance at both gene and pathway levels. The integration of drug resistance and gene perturbation data also presents novel perspectives for identifying pivotal genes influencing drug resistance. Access CPADS at https://smuonco.shinyapps.io/CPADS/ or https://robinl-lab.com/CPADS.

Dual COX-2/5-LOX inhibitors from Zanthoxylum simulans inhibit gastric cancer cells by cross-mediating thyroid, estrogen, and oxytocin signaling pathways

Cyclooxygenase 2 (COX-2) and 5-lipoxygenase (5-LOX) are overexpressed in gastric cancer cells, the dual inhibitors of which exhibit potential against metastasis and invasion with fewer side effects. To discover inhibitors targeting COX-2 and 5-LOX, we conducted ultrafiltration and enrichment calculation to screen candidates in quaternary alkaloids (QAs) from Zanthoxylum simulans through LC and LC-Q-TOF. For intensive peaks, peaks 19 (berberine) and 21 (chelerythrine) were observed as the most potent dual candidates and showed selective affinity to 5-LOX over COX-2. Peak 19 showed an enrichment at 4.36 for COX-2 and 22.81 for 5-LOX, while peak 21 showed an enrichment at 7.81 for COX-2 and 24.49 for 5-LOX. Molecular docking results revealed chelerythrine as a better dual inhibitor, showing time- and dose-dependent anti-proliferation against AGS cells. Bio-informatics strategies, such as Gene Expression Omnibus (GEO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG), suggested that hormone pathways in gastric cancer cells might be mediated by chelerythrine. Further reviews and summaries helped outline the mechanisms by which COX-2/5-LOX inhibitors might promote apoptosis in gastric cancer cells via estrogen, thyroid, and oxytocin signaling pathways. Chelerythrine was also added to gastric cancer cells to verify the regulation of these three signaling pathways. As a result, significant calling back of thyroid-stimulating hormone receptor (TSHR), thyroid hormone α3 (TRα3), and thyroid hormone receptor β1 (TRβ1) and suppressing estrogen receptor α36 (ER-α36)-Src could benefit the anti-proliferation of chelerythrine. However, it was disappointing that regulation of estrogen receptor α66 (ER-α66), estrogen receptor β (ER-β), and oxytocin receptor (OTR) contributed inversely negative effects on anti-gastric cancer cells. At present, the integrative study not only revealed chelerythrine as the most potent dual COX-2/5-LOX inhibitor from QAs but also generally highlighted that comprehensive regulation of the estrogen, thyroid, and oxytocin pathway should be noted once gastric cancer cells were treated with inflammatory inhibitors.

The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma

Due to the high heterogeneity, lung adenocarcinoma (LUAD) cannot be distinguished into precise molecular subtypes, thereby resulting in poor therapeutic effect and low 5-year survival rate clinically. Although the tumor stemness score (mRNAsi) has been shown to accurately characterize the similarity index of cancer stem cells (CSCs), whether mRNAsi can serve as an effective molecular typing tool for LUAD isn't reported to date. In this study, we first demonstrate that mRNAsi is significantly correlated with the prognosis and disease degree of LUAD patients, i.e., the higher the mRNAsi, the worse the prognosis and the higher the disease degree. Second, we identify 449 mRNAsi-related genes based on both weighted gene co-expression network analysis (WGCNA) and univariate regression analysis. Third, our results display that 449 mRNAsi-related genes can accurately distinguish the LUAD patients into two molecular subtypes: ms-H subtype (with high mRNAsi) and ms-L subtype (with low mRNAsi), particularly the ms-H subtype has a worse prognosis. Remarkably, significant differences in clinical characteristics, immune microenvironment, and somatic mutation exist between the two molecular subtypes, which might lead to the poorer prognosis of the ms-H subtype patients than that of the ms-L subtype ones. Finally, we establish a prognostic model containing 8 mRNAsi-related genes, which can effectively predict the survival rate of LUAD patients. Taken together, our work provides the first molecular subtype related to mRNAsi in LUAD, and reveals that these two molecular subtypes, the prognostic model and marker genes may have important clinical value for effectively monitoring and treating LUAD patients.

Osimertinib resistance prognostic gene signature: STRIP2 is associated with immune infiltration and tumor progression in lung adenocarcinoma

OBJECTIVE

Although the use of osimertinib can significantly improve the survival time of lung adenocarcinoma (LUAD) patients with epithelial growth factor receptor mutation, eventually drug resistance will limit the survival benefit of most patients. This study aimed to develop a novel prognostic predictive signature based on genes associated with osimertinib resistance.

METHODS

The differentially expressed genes (DEGs) associated with osimertinib resistance in LUAD were screened from Gene Expression Omnibus datasets and The Cancer Genome Atlas datasets. Multivariate cox regression was used to establish a prognostic signature, and then a nomogram was developed to predict the survival probability of LUAD patients. We used ROC curve and DCA curve to evaluate its clinical prediction accuracy and net benefit. In addition, the differentially expressed genes significantly associated with prognosis were selected for immune infiltration analysis and drug sensitivity analysis, and their roles in the progression of lung adenocarcinoma were verified by in vitro experiments.

RESULTS

Our evaluation results indicated that the new nomogram had higher clinical prediction accuracy and net benefit value than the TN nomogram. Further analysis showed that patients with low STRIP2 expression had a higher level of immune response, and may be more likely to benefit from immune checkpoint inhibitors and conventional antitumor drugs. This may help to select more precise and appropriate therapy for LUAD patients with osimertinib resistance. Furthermore, in vitro experiments showed that STRIP2 promoted the LUAD cells proliferation, migration and invasion. This further demonstrates the importance of this gene signature for prognostic prediction.

CONCLUSION

We developed a reliable prognostic model based on DEGs associated with osimertinib resistance and screened for biomarker that can predict the immune response in LUAD patients, which may help in the selection of treatment regimens after osimertinib resistance.

Machine Learning-Based Integration Develops a Macrophage-Related Index for Predicting Prognosis and Immunotherapy Response in Lung Adenocarcinoma

BACKGROUND

Macrophages play a critical role in tumor immune microenvironment (TIME) formation and cancer progression in lung adenocarcinoma (LUAD). However, few studies have comprehensively and systematically described the characteristics of macrophages in LUAD.

METHODS

This study identified macrophage-related markers with single-cell RNA sequencing data from the GSE189487 dataset. An integrative machine learning-based procedure based on 10 algorithms was developed to construct a macrophage-related index (MRI) in The Cancer Genome Atlas (TCGA), GSE30219, GSE31210, and GSE72094 datasets. Several algorithms were used to evaluate the associations of MRI with TIME and immunotherapy-related biomarkers. The role of MRI in predicting the immunotherapy response was evaluated with the GSE91061 dataset.

RESULTS

The optimal MRI constructed by the combination of the Lasso algorithm and plsRCox was an independent risk factor in LUAD and showed a stable and powerful performance in predicting the overall survival rate of patients with LUAD. Those with low MRI scores had a higher TIME score, a higher level of immune cells, a higher immunophenoscore, and a lower Tumor Immune Dysfunction and Exclusion (TIDE) score, indicating a better response to immunotherapy. The IC50 value of common drugs for chemotherapy and target therapy with low MRI scores was higher compared to high MRI scores. Moreover, the survival prediction nomogram, developed from MRI, had good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of LUAD.

CONCLUSION

Our study constructed for the first time a consensus MRI for LUAD with 10 machine learning algorithms. The MRI could be helpful for risk stratification, prognosis, and selection of treatment approach in LUAD.

FSCN1 promotes proliferation, invasion and glycolysis via the IRF4/AKT signaling pathway in oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a disease with increasing incidence worldwide that leads to deformity and death. In OSCC, fascin actin-bundling protein 1 (FSCN1) is an oncogene involved in the tumorigenesis process. However, the functions and potential mechanisms of FSCN1 in the OSCC tumorigenesis process have not been reported thus far.

METHODS

We used qRT‒PCR to detect the expression of FSCN1 in 40 paired OSCC tumor tissues (tumor) and neighboring noncancerous tissues. The role of FSCN1 was also assessed in vitro through colony formation, CCK-8, and transwell assays. Moreover, glucose consumption was detected. Western blotting was used to confirm the interaction of FSCN1, IRF4 and AKT.

RESULTS

FSCN1 was remarkably overexpressed in OSCC tissues and cell lines compared to corresponding controls. In addition, colony formation, CCK-8, and transwell assays revealed a notable reduction in OSCC growth and invasion when FSCN1 was silenced. FSCN1 silencing remarkably suppressed OSCC glycolysis. Mechanistic studies showed that FSCN1 achieves its function partially by activating interferon regulatory factor 4 (IRF4) and the AKT pathway in OSCC.

CONCLUSION

In conclusion, our study investigated the functions and mechanisms of the FSCN1/IRF4/AKT pathway in OSCC progression. In OSCC, FSCN1 is likely to be a biomarker and therapeutic target.

TRAF2 promotes M2-polarized tumor-associated macrophage infiltration, angiogenesis and cancer progression by inhibiting autophagy in clear cell renal cell carcinoma

BACKGROUND

The management of advanced clear cell renal cell carcinoma (ccRCC) remains a major challenge in clinical practice, and the construction of more reliable prognostic prediction models and the further elucidation of key molecular mechanisms of tumor progression are topics in urgent need of in-depth investigation.

METHODS

We used CIBERSORT to estimate the proportion of 22 tumor-infiltrating immune cell types in the TCGA-KIRC cohort. Weighted gene co-expression network analysis, least absolute shrinkage and selection operator regression analysis were used to build risk prediction models. Expression patterns and clinical significance of TRAF2 were determined through bioinformatics analysis, real-time qPCR, Western Blot, immunohistochemistry. GSEA analysis, transmission electron microscopy, 2D/3D colony formation assay, cell migration and invasion assay, and tube-formation assay were used to investigate the underlying function and mechanism of the TRAF2/M2 macrophage/autophagy axis.

RESULTS

We constructed a novel prognostic prediction model based on M2 macrophage-related genes, which was identified as an accurate, independent and specific prognostic risk model for ccRCC patients. A reliable nomogram was constructed to predict 1-, 3-, and 5-year overall survival for patients with ccRCC. As one of the constituent genes of the risk model, TRAF2 was determined to be upregulated in ccRCC and associated with poor clinical prognosis. We found that TRAF2 promotes malignant progression of ccRCC by regulating macrophage polarization, migration and angiogenesis. Mechanistically, we found that TRAF2 promotes the polarization of M2 macrophages, and this chemotaxis is achieved in an autophagy-dependent pathway. Orthotopic tumor growth assay results revealed that TRAF2 plays a key role as a promotor of ccRCC growth and metastasis.

CONCLUSIONS

In conclusion, this risk model is highly predictive of prognostic in ccRCC patients, which is expected to promote improved treatment evaluation and comprehensive management of ccRCC. Moreover, our findings reveal that the TRAF2/M2 macrophage/autophagy axis plays a key regulatory role in the malignant progression of ccRCC, and suggest that TRAF2 is a potential novel therapeutic target for advanced ccRCC.

Improvement strategy for immune checkpoint blockade: A focus on the combination with immunogenic cell death inducers

Cancer immunotherapies have yielded promising outcomes in various malignant tumors by blocking specific immune checkpoint molecules, such as programmed cell death 1 and cytotoxic T lymphocyte antigen 4. However, only a few patients respond to immune checkpoint blockade therapy because of the poor immunogenicity of tumor cells and immune-suppressive tumor microenvironment. Accumulating evidence suggests that chemotherapeutic agents, including oxaliplatin and doxorubicin, not only mediate direct cytotoxicity in tumor cells but also induce immunogenic cancer cell death to stimulate a powerful anti-cancer immune response in the tumor microenvironment. In this review, we summarize the recent advances in cancer combination therapy based on immune checkpoint inhibitors plus immunogenic cell death inducers. Despite some clinical failures and challenges, immunogenic cell death inducers have displayed great potential when combined with immune checkpoint inhibitors for anti-cancer treatment in both preclinical studies and clinical trials.

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

OBJECTIVES

This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy.

METHODS

LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activities and pathways in different risk populations, we calculated immune checkpoints, immune escape, immune phenomena (IPS), and tumor mutation burden (TMB) based on TCGA datasets. Finally, the relationship between the model and drug sensitivity was analyzed.

RESULTS

Fifteen (15) key differentially expressed genes (DEGs) with prognostic value were screened and a new prognostic model was constructed. Four hundred and forty-three (443) samples were grouped into two different risk cohorts based on median model risk values. It was observed that survival rates in high-risk groups were significantly low. ROC curves were used to evaluate the model's accuracy in determining the survival time and clinical outcome of LUAD patients. Cox analysis of various clinical factors proved that the risk score has great potential as an independent prognostic factor. The results of immunological analysis can reveal the immune infiltration and the activity of related functions in different pathways in the two risk groups, and immunotherapy was more effective in low-risk patients. Most chemotherapeutic agents are more sensitive to low-risk patients, making them more likely to benefit.

CONCLUSION

A novel prognostic model for LUAD patients was established based on IGRG, which could more accurately predict the prognosis and an effective immunotherapy approach for patients.

Correlation of tumor mutational burden with prognosis and immune infiltration in lung adenocarcinoma

Background

Tumor mutational burden (TMB) plays an important role in the evaluation of immunotherapy efficacy in lung adenocarcinoma (LUAD).

Objective

To improve the clinical management of LUAD by investigating the prognostic value of TMB and the relationship between TMB and immune infiltration.

Methods

TMB scores were calculated from the mutation data of 587 LUAD samples from The Cancer Genome Atlas (TCGA), and patients were divided into low-TMB and high-TMB groups based on the quartiles of the TMB score. Differentially expressed genes (DEGs), immune cell infiltration and survival analysis were compared between the low-TMB and high-TMB groups. We queried the expression of genes in lung cancer tissues through the GEPIA online database and performed experimental validation of the function of aberrant genes expressed in lung cancer tissues.

Results

We obtained sample information from TCGA for 587 LUAD patients, and the results of survival analysis for the high- and low- TMB groups suggested that patients in the high-TMB group had lower survival rates than those in the low-TMB group. A total of 756 DEGs were identified in the study, and gene set enrichment analysis (GSEA) showed that DEGs in the low-TMB group were enriched in immune-related pathways. Among the differentially expressed genes obtained, 15 immune-related key genes were screened with the help of ImmPort database, including 5 prognosis-related genes (CD274, PDCD1, CTLA4, LAG3, TIGIT). No difference in the expression of PDCD1, CTLA4, LAG3, TIGIT in lung cancer tissues and differential expression of CD274 in lung cancer tissues.

Conclusions

The survival rate of LUAD patients with low TMB was better than that of LUAD patients with high TMB. CD274 expression was down regulated in human LUAD cell lines H1299, PC-9, A549 and SPC-A1, which inhibited malignant progression of A549 cells.

The diagnostic, prognostic role and molecular mechanism of miR-328 in human cancer

MicroRNA are non-coding small RNAs that bind to their target mRNA and cause mRNA degradation or translation inhibition. MiRNA dysregulation is linked to a variety of human cancers and has a role in the genesis and development of cancer pathology. MiR-328 has been reported to be involved in various human cancers. And miR-328 is considered a key regulator in human cancer. It participates in biological processes such as proliferation, apoptosis, invasion, migration, and EMT. The present review will combine the basic and clinical studies to find that miR-328 promotes tumorigenesis and metastasis in human cancer. And we will describe the diagnostic, prognostic, and therapeutic value of miR-328 in various human cancers.

Evaluating the role of IDO1 macrophages in immunotherapy using scRNA-seq and bulk-seq in colorectal cancer

Background

Macrophage infiltration is crucial for colorectal cancer (CRC) immunotherapy. Detailed classification of macrophage subsets will facilitate the selection of patients suitable for immunotherapy. However, the classification of macrophages in CRC is not currently detailed.

Methods

In this study, we combined single-cell RNA sequencing (scRNA-seq) and bulk-seq to analyze patients with colorectal cancer. scRNA-seq data were used to study cell-cell communication and to differentiate immune-infiltrating cells and macrophage subsets. Bulk-seq data were used to further analyze immune infiltration, clinical features, tumor mutational burden, and expression of immune checkpoint molecules in patients with CRC having different macrophage subsets.

Results

Seven macrophage subpopulations were identified, among which indoleamine 2,3 dioxygenase 1 (IDO1) macrophages had the most significant difference in the degree of infiltration among normal, microsatellite-unstable, and microsatellite-stable populations. We then performed gene set variation analysis using 12 marker genes of IDO1 macrophages and divided the patients into two clusters: high-IDO1 macrophages (H-IDO1M) and low-IDO1 macrophages (L-IDO1M). H-IDO1M showed higher infiltration of immune cells, higher expression of immune checkpoints, and less advanced pathological stages than L-IDO1M (p < 0.05).

Conclusions

This study elucidated that IDO1-macrophage-based molecular subtypes can predict the response to immunotherapy in patients with CRC. The results provide new insights into tumor immunity and help in clinical decisions regarding designing effective immunotherapy for these patients.

Unlocking phenotypic plasticity provides novel insights for immunity and personalized therapy in lung adenocarcinoma

Background: Unlocking phenotype plasticity (UPP) has been shown to have an essential role in the mechanism of tumor development and therapeutic response. However, the clinical significance of unlocking phenotypic plasticity in patients with lung adenocarcinoma is unclear. This study aimed to explore the roles of unlocking phenotypic plasticity in immune status, prognosis, and treatment in patients with lung adenocarcinoma (LUAD).

Methods: Differentially expressed genes (DEGs) and clinical information of UPP were selected from the cancer genome atlas (TCGA) database, and the GO, KEGG enrichment analyses were performed. The independent prognostic genes were determined by univariate and multivariate Cox regression, and the UPP signature score was constructed. Patients with LUAD were divided into high- and low-risk groups according to the median of score, and the immunocytes and immune function, the gene mutation, and drug sensitivities between the two groups were analyzed. Finally, the results were validated in the GEO database.

Results: Thirty-nine significantly DEGs were determined. Enrichment analysis showed that UPP-related genes were related to protein polysaccharides and drug resistance. The prognostic results showed that the survival of patients in the high-risk group was poorer than that in the low-risk group (p < 0.001). In the high- and low-risk groups, single nucleotide polymorphism (SNP) and C > T are the most common dissent mutations. The contents of immune cells were significantly different between high- and low-risk groups. And the immune functions were also significantly different, indicating that UPP affects the immunity in LUAD. The results from TCGA were validated in the GEO.

Conclusion: Our research has proposed a new and reliable prognosis indicator to predict the overall survival. Evaluation of the UPP could help the clinician to predict therapeutic responses and make individualized treatment plans in patients with LUAD.

OAS3 is a Co-Immune Biomarker Associated With Tumour Microenvironment, Disease Staging, Prognosis, and Treatment Response in Multiple Cancer Types

2′,5′-oligoadenylate synthase (OAS) is a class of enzymes induced by interferons and mainly encoded by the OAS1, OAS2, and OAS3 genes, which activate the potential RNA enzymes to degrade viral mRNA, inhibit viral protein synthesis and promote apoptosis in virus-infected cells. OAS3 is associated with breast cancer prognosis. However, the expression and prognosis of OAS3 and tumour-infiltrating lymphocytes in pan-cancer remain unknown. In the present study, we have systematically investigated and confirmed the role of OAS3 in tumour immune infiltration, immune escape, tumour progression, response to treatment, and prognosis of different cancer types using various bioinformatics methods. The findings suggest that OAS3 is aberrantly expressed in almost all TCGA cancer types and subtypes and is associated with tumour staging, metastasis, and prognostic deterioration in different tumours. In addition, OAS3 expression is associated with the prognosis and chemotherapeutic outcomes of various cancers. In terms of immune-infiltrating levels, OAS3 expression is positively associated with the infiltration of immunosuppressive cells. These findings suggest that OAS3 is correlated with prognosis and immune-infiltrating levels.

Development of a 5-Gene Signature to Evaluate Lung Adenocarcinoma Prognosis Based on the Features of Cancer Stem Cells

Cancer stem cells (CSCs) can induce recurrence and chemotherapy resistance of lung adenocarcinoma (LUAD). Reliable markers identified based on CSC characteristic of LUAD may improve patients' chemotherapy response and prognosis. OCLR was used to calculate mRNA expression-based stemness index (mRNAsi) of LUAD patients' data in TCGA. Association analysis of mRNAsi was performed with clinical features, somatic mutation, and tumor immunity. A prognostic prediction model was established with LASSO Cox regression. Kaplan-Meier Plotter (KM-plotter) and time-dependent ROC were applied to assess signature performance. For LUAD, univariate and multivariate Cox analysis was performed to identify independent prognostic factors. LUAD tissues showed a noticeably higher mRNAsi in than nontumor tissues, and it showed significant differences in T, N, M, AJCC stages, and smoking history. The most frequently mutated gene was TP53, with a higher mRNAsi relating to more frequent mutation of TP53. The mRNAsi was significantly negatively correlated with immune score, stromal score, and ESTIMATE score in LUAD. The blue module was associated with mRNAsi. The 5-gene signature was confirmed as an independent indicator of LUAD prognosis that could promote personalized treatment of LUAD and accurately predict overall survival (OS) of LUAD patients.