Immune Infiltration Subtypes Characterization and Identification of Prognosis-Related lncRNAs in Adenocarcinoma of the Esophagogastric Junction

Bioinformatics Identification and Experimental Validation of a Prognostic Model for the Survival of Lung Squamous Cell Carcinoma Patients

Lung squamous cell carcinoma (LUSC) kills more than four million people yearly. Creating more trustworthy tumor molecular markers for LUSC early detection, diagnosis, prognosis, and customized treatment is essential. Cuproptosis, a novel form of cell death, opened up a new field of study for searching for trustworthy tumor indicators. Our goal was to build a risk model to assess drug sensitivity, monitor immune function, and predict prognosis in LUSC patients. The 19 cuproptosis-related genes were found in the literature, and patient genomic and clinical information was collected using the Cancer Genomic Atlas (TCGA) database. The LUSC patients were grouped using unsupervised clustering techniques, and 7626 differentially expressed genes were identified. Using univariate COX analysis, LASSO regression analysis, and multivariate COX analysis, a prognostic model for LUSC patients was developed. The tumor immune escape was evaluated using the Tumor Immune Dysfunction and Exclusion (TIDE) method. The R packages 'pRRophetic,' 'ggpubr,' and 'ggplot2' were utilized to examine drug sensitivity. For modeling, a 6-cuproptosis-based gene signature was found. Patients with high-risk LUSC had significantly worse survival rates than those with low-risk conditions. The possibility of tumor immunological escape was increased in patients with higher risk scores due to more immune cell inactivation. For patients with high-risk LUSC, we discovered seven potent potential drugs (AZD6482, CHIR.99021, CMK, Embelin, FTI.277, Imatinib, and Pazopanib). In conclusion, the cuproptosis-based genes predictive risk model can be utilized to predict outcomes, track immune function, and evaluate medication sensitivity in LUSC patients.

[High LINC00626 expression promotes esophagogastric junction adenocarcinoma metastasis: the mediating role of the JAK1/STAT3/KHSRP axis]

OBJECTIVE

To investigate the role of JAK1/STAT3/KHSRP axis in mediating the regulatory effect of LINC00626 on progression of esophagogastric junction adenocarcinoma.

METHODS

We collected surgical tumor and adjacent tissue specimens from 64 patients with esophagogastric junction adenocarcinoma and examined the expression levels of LINC00626 and KHSRP. qRT-PCR was used to detect the expressions of LINC00626 and KHSRP in 6 esophageal adenocarcinoma cell lines (OE-19, TE-7, Bic-1, Flo-1, SK-GT-4, and BE-3) and a normal esophageal epithelial cell line (HET-1A). OE-19 and TE-7 cell lines with stable LINC00626 knockdown and FLO-1 and SK-GT-4 cells stably overexpressing LINC00626 were constructed by lentiviral transfection, and the changes in proliferation, migration and invasion of the cells were evaluated using Cell Counting Kit-8 (CCK-8) assay and Transwell migration/invasion assay. The expressions of KHSRP and JAK/STAT pathway proteins in the transfected cells were detected with Western blotting. The effects of LINC006266 knockdown and overexpression on subcutaneous tumor formation and lung metastasis of OE-19 and FLO-1 cell xenografts were tested in nude mice.

RESULTS

The expression levels of LINC00626 and KHSRP were significantly increased in esophagogastric junction adenocarcinoma tissues and in esophageal adenocarcinoma cells. LINC00626 knockdown obviously inhibited the proliferation, migration and invasion of esophageal adenocarcinoma cells in vitro and decreased their tumor formation and lung metastasis abilities in nude mice, while overexpression of LINC00626 produced the opposite effects. In esophageal adenocarcinoma cells, LINC0626 knockdown significantly decreased and LINC00626 overexpression strongly enhanced the phosphorylation of JAK1 and STAT3.

CONCLUSION

High LINC00626 expression promotes esophageal-gastric junction adenocarcinoma metastasis by activating the JAK1/STAT3/KHSRP signal axis.

Chemokine- and chemokine receptor-based signature predicts immunotherapy response in female colorectal adenocarcinoma patients

The clinical significance and comprehensive characteristics of chemokines and chemokine receptors in female patients with advanced colorectal adenocarcinoma have not ever been reported. Our study explored the expression profiles of chemokines and chemokine receptors and constructed a chemokine- and chemokine receptor-based signature in female patients with advanced colorectal adenocarcinoma. Four independent cohorts containing 1335 patients were enrolled in our study. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were performed to construct the signature. CIBERSORT was used to evaluate the landscape of immune cell infiltration. Thirty-two pairs of tissue specimens of female advanced colorectal cancer (CRC) patients and two CRC cell lines were used to validate the signature in vitro. Quantitative real-time PCR and western blotting were performed to validate the mRNA and protein expression levels of signature genes. EdU and colony formation assays were performed to examine proliferative ability. Transwell and wound healing assays were used to evaluate cell invasion and migration capacity. During the signature construction and validation process, we found that the signature was more applicable to female patients with advanced colorectal adenocarcinoma. Hence, the subsequent study mainly focused on the particular subgroup. Enrichment analyses revealed that the signature was closely related to immunity. The landscape of immune cell infiltration presented that the signature was significantly associated with T cells CD8 and neutrophils. Gene set enrichment analysis (GSEA) confirmed that the high-risk group was chiefly enriched in the tumor-promoting related pathways and biological processes, whereas the low-risk group was mainly enriched in anti-tumor immune response pathways and biological processes. The signature was closely correlated with CTLA4, PDL1, PDL2, TMB, MSI, and TIDE, indicating that our signature could serve as a robust biomarker for immunotherapy and chemotherapy response. ROC curves verified that our signature had more robust prognostic power than all immune checkpoints and immunotherapy-related biomarkers. Finally, we used 32 pairs of tissue specimens and 2 CRC cell lines to validate our signature in vitro. We first provided a robust prognostic chemokine- and chemokine receptor-based signature, which could serve as a novel biomarker for immunotherapy and chemotherapy response to guide individualized treatment for female patients with advanced colorectal adenocarcinoma.

Stemness genes and miR-1247-3p expression associate with clinicopathological parameters and prognosis in lung adenocarcinoma

Lung cancer makes up one-fourth of all cancer-related mortality with the highest mortality rate among all cancers. Despite recent scientific advancements in cancer therapeutics, the 5-year survival rate of lung adenocarcinoma (LUAD) cancer patients remains below 15 percent. It has been suggested that the high mortality rate of LUAD is linked to the acquisition of progenitor-like cells with stem-like characteristics that assist the whole tumor in regulating immune cell infiltration. To examine this hypothesis further, this study mined several databases to explore the presence of stemness-related genes and miRNAs in LUAD cancers. We examine their association with immune and accessory cell infiltration rates and patient survival. We found 3 stem cell-related genes, ORC1L, KIF20A, and DLGAP5, present in LUAD that also correlate with changes in immune infiltration rates and reduced patient survival rates. Additionally, the modulation in myeloid-derived suppressor cell (MDSC) infiltration and miRNA hsa-mir-1247-3p mediated targeting of tumor suppressor SLC24A4 and oncogenes RAB3B and HJURP appears to primarily regulate LUAD patient survival. Given these findings, hsa-mir-1247-3p and/or its associated gene targets may offer a promising avenue to enhance patient survivability.

Identification of hub necroptosis-related lncRNAs for prognosis prediction of esophageal carcinoma

Necroptosis is a newly identified programmed cell death associated with the biological process of various cancers, including esophageal carcinoma (ESCA). Meanwhile, the dysregulation of long non-coding RNAs (lncRNAs) is greatly implicated in ESCA progression and necroptosis regulation. However, the lncRNAs involved in regulating necroptosis in ESCA are still unclear. In this study, we aim to explore the expression profile of necroptosis-related lncRNAs (NRLs), and evaluate their roles in ESCA prognosis and treatment. In the present study, 198 differentially expressed NRLs were identified between the ESCA and adjacent normal tissues through screening the data extracted from the Cancer Genome Atlas (TCGA) database. And, a prognostic panel consisting of 6 NRLs was constructed using the LASSO algorithm and multivariate Cox regression analysis. The ESCA patients with high risks had a markedly reduced survival time and higher mortality prevalence. Moreover, C-index of 6 NRLs-panel was superior to 48 published prognostic models based on lncRNAs or mRNAs for ESCA. There were significant differences between the high-risk and low-risk groups in tumor-related pathways, genetic mutations, and drug sensitivity responses. In vitro analysis revealed that inhibition of PVT1 impeded the proliferation, migration, and colony formation of ESCA cells, increased the expressions of p-RIP1 and p-MLKL and promoted necroptosis. By contrast, PVT1 overexpression resulted in a decrease in necroptotic cell death events, thus promoting tumor progression. Collectively, the established 6-NRLs panel was a promising biomarker for the prognostic prediction of ESCA. Moreover, our current findings provided potential targets for individualized therapy for ESCA patients.

Comprehensive analysis of autophagy-related clusters and individual risk model for immunotherapy response prediction in gastric cancer

Introduction

Autophagy can be triggered by oxidative stress and is a double-edged sword involved in the progression of multiple malignancies. However, the precise roles of autophagy on immune response in gastric cancer (GC) remain clarified.

Methods

We endeavor to explore the novel autophagy-related clusters and develop a multi-gene signature for predicting the prognosis and the response to immunotherapy in GC. A total of 1505 patients from eight GC cohorts were categorized into two subtypes using consensus clustering. We compare the differences between clusters by the multi-omics approach. Cox and LASSO regression models were used to construct the prognostic signature.

Results

Two distinct clusters were identified. Compared with cluster 2, the patients in cluster 1 have favorable survival outcomes and lower scores for epithelial-mesenchymal transition (EMT). The two subtypes are further characterized by high heterogeneity concerning immune cell infiltration, somatic mutation pattern, and pathway activity by gene set enrichment analysis (GSEA). We obtained 21 autophagy-related differential expression genes (DEGs), in which PTK6 amplification and BCL2/CDKN2A deletion were highly prevalent. The four-gene (PEA15, HSPB8, BNIP3, and GABARAPL1) risk signature was further constructed with good predictive performance and validated in 3 independent datasets including our local Tianjin cohort. The risk score was proved to be independent prognostic factor. A prognostic nomogram showed robust validity of GC survival. The risk score was significantly associated with immune cell infiltration status, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint molecules. Furthermore, the model was efficient for predicting the response to tumor-targeted agent and immunotherapy and verified by the IMvigor210 cohort. This model is also capable of discriminating between low and high-risk patients receiving chemotherapy.

Conclusion

Altogether, our exploratory research on the landscape of autophagy-related patterns may shed light on individualized therapies and prognosis in GC.

Prognostic signature of lipid metabolism associated LncRNAs predict prognosis and treatment of lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most predominant histological subtype of lung cancer. Abnormal lipid metabolism is closely related to the development of LUAD. LncRNAs are involved in the regulation of various lipid metabolism-related genes in various cancer cells including LUAD. Here, we aimed to identify lipid metabolism-related lncRNAs associated with LUAD prognosis and to propose a new prognostic signature.

METHODS

First, differentially expressed lncRNAs (DE-lncRNAs) from the TCGA-LUAD and the GSE31210 dataset were identified. Then the correlation analysis between DE-lncRNAs and lipid metabolism genes was performed to screen lipid metabolism-related lncRNAs. Cox regression analyses were performed in the training set to establish a prognostic model and the model was validated in the testing set and the validation set. Moreover, The role of this model in the underlying molecular mechanisms, immunotherapy, and chemotherapeutic drug sensitivity analysis was predicted by methods such as Gene Set Enrichment Analysis, immune infiltration, tumor mutational burden (TMB), neoantigen, Tumor Immune Dysfunction and Exclusion, chemosensitivity analysis between the high- and low-risk groups. The diagnostic ability of prognostic lncRNAs has also been validated. Finally, we validated the expression levels of selected prognostic lncRNAs by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

The prognostic model was constructed based on four prognostic lncRNAs (LINC00857, EP300-AS1, TBX5-AS1, SNHG3) related to lipid metabolism. The receiver operating characteristic curve (ROC) and Kaplan Meier (KM) curves of the risk model showed their validity. The results of Gene Set Enrichment Analysis suggested that differentially expressed genes in high- and low-risk groups were mainly enriched in immune response and cell cycle. There statistical differences in TMB and neoantigen between high- and low-risk groups. Drug sensitivity analysis suggested that patients with low risk scores may have better chemotherapy outcomes. The results of qRT-PCR were suggesting that compared with the normal group, the expressions of EP300-AS1 and TBX5-AS1 were down-regulated in the tumor group, while the expressions of LINC00857 and SNHG3 were up-regulated. The four prognostic lncRNAs had good diagnostic capabilities, and the overall diagnostic model of the four prognostic lncRNAs was more effective.

CONCLUSION

A total of 4 prognostic lncRNAs related to lipid metabolism were obtained and an effective risk model was constructed.

Construction of a Prognostic Evaluation Model for Stomach Adenocarcinoma on the Basis of Immune-Related lncRNAs

Progression, prognosis, and therapeutic strategy of stomach adenocarcinoma (STAD) have a close connection with tumor microenvironment (TME). Thus, it is pivotal to delve into the TME and immune-related genes, which may bring possibilities for improving patient's prognosis. TCGA-STAD dataset was analyzed to acquire differentially expressed lncRNAs in tumor samples, which were overlapped with the immune-related lncRNA datasets in the ImmLnc database. Twenty-six lncRNAs related to STAD immunity and patient's prognosis were acquired by univariate Cox analysis. Following lncRNA expression patterns, STAD samples could be classified into two clusters with completely different immune patterns. We performed multivariate Cox regression analysis on lncRNAs to identify 7-feature lncRNAs and constructed a corresponding prognostic model. The model validity was verified by survival analysis and ROC curve in validation and training sets. To explore connection between model and TME and tumor drug resistance, this study analyzed differences in immune cell infiltration between samples from high- and low-risk groups and then revealed immune cells follicular helper with significant differences in tumor tissue infiltration. Analysis of resistance to chemotherapeutic drugs revealed that samples in the high-risk group had resistance to cisplatin, doxorubicin, bleomycin, and gemcitabine. Through univariate and multivariate Cox analyses, we manifested that risk score could be an independent prognostic factor. Combining risk score and clinical factors, a nomogram was constructed to accurately predict patient's prognosis. This model can effectively predict prognosis, TME, and drug resistance of STAD patients, which may provide a reference for tumor development evaluation and precise treatment for clinical STAD.

Comprehensive Analysis of Programmed Cell Death Signature in the Prognosis, Tumor Microenvironment and Drug Sensitivity in Lung Adenocarcinoma

Programmed cell death (PCD) is a process that regulates the homeostasis of cells in the body, and it plays an important role in tumor immunity. However, the expression profile and clinical characteristics of PCD-related genes remain unclear. In this study, we comprehensively analysed the PCD genes with the tumor microenvironment (TME), drug sensitivity, immunothearapy response, and evaluated their prognostic value through systematic bioinformatics methods.We identified 125 PCD-related regulatory factors, which were expressed differently in lung adenocarcinoma (LUAD) and normal lung tissues. 32 PCD related prognostic genes associated with LUAD were identified by univariate Cox analysis. 23 PCD-related gene signature was constructed, and all LUAD patients in the Cancer Genome Atlas (TCGA) dataset were stratified as low-risk or high-risk groups according to the risk score. This signature had a powerful prognostic value, which was validated in three independent data sets and clinical subtypes. Additionally, it has unique properties in TME. Further analysis showed that different risk groups have different immune cell infiltration, immune inflammation profile, immune pathways, and immune subtypes. In addition, the low-risk group had a better immunotherapy response with higher levels of multiple immune checkpoints and lower Tumor immune dysfunction and exclusion (TIDE) score, while the high-risk group was sensitive to multiple chemotherapeutic drugs because of its lower IC50. In short, this is the first model to predict the prognosis and immunological status of LUAD patients based on PCD-related genes. It may be used as a predictor of immunotherapy response to achieve customized treatment of LUAD.

Endoplasmic Reticulum Stress-Related Four-Biomarker Risk Classifier for Survival Evaluation in Esophageal Cancer

Purpose

Esophageal cancer (EC) is a lethal digestive tumor worldwide with a dismal clinical outcome. Endoplasmic reticulum (ER) stress poses essential implications for a variety of tumor malignant behaviors. Here, we set up an ER stress-based risk classifier for assessing patient outcome and exploiting robust targets for medical decision-making of EC cases.

Methods

340 EC cases with transcriptome and survival data from two independent public datasets (TCGA and GEO) were recruited for this project. Cox regression analyses were employed to create a risk classifier based on ER stress-related genes (ERGs) which were strongly linked to EC cases' outcomes. Then, we detected and confirmed the predictive ability of our proposed classifier via a host of statistical methods, including survival analysis and ROC method. In addition, immune-associated algorithm was implemented to analyze the immune activity of EC samples.

Results

Four EGRs (BCAP31, HSPD1, PDHA1, and UBE2D1) were selected to build an EGR-related classifier (ERC). This classifier could distinguish the patients into different risky subgroups. The remarkable differences in patient outcome between the two groups were observed, and similar results were also confirmed in GEO cohort. In terms of the immune analysis, the ERC could forecast the infiltration level of immunocytes, such as Tregs and NK cells.

Conclusion

We created a four-ERG risk classifier which displays the powerful capability of survival evaluation for EC cases.

Characterization of Two Ferroptosis Subtypes With Distinct Immune Infiltration and Gender Difference in Gastric Cancer

Background: Iron is an essential nutrient involved in the redox cycle and the formation of free radicals. The reprogramming of iron metabolism is the main link to tumor cell survival. Ferroptosis is an iron-dependent form of regulated cell death associated with cancer; the characteristics of ferroptosis in cancers are still uncertain. This study aimed to explore the application value and gender difference of ferroptosis in prognosis and immune prediction to provide clues for targeted therapy of gastric cancer.

Methods: We comprehensively evaluated the ferroptosis levels of 1,404 gastric cancer samples from six independent GC cohorts based on ferroptosis-related specific genes and systematically correlated ferroptosis with immune cell infiltrating and gender characteristics. The ferroptosis score was constructed to quantify the ferroptosis levels of individual tumors using principal component analysis (PCA) algorithms.

Results: We identified two distinct ferroptosis subtypes in gastric cancer, namely Subtype-A and Subtype-B. We found that male patients in Subtype-B had the worst prognosis in contrast with the other groups. Three sex hormone receptors (AR, ER, and PR) in Subtype-B tumor patients were higher than in Subtype-A tumor patients in GC, while the HER2 displayed an opposite trend. We developed a risk model termed ferroptosis score to evaluate ferroptosis levels within individual tumors. The low-ferroptosis score group was characterized by activation of immune cells and increased mutation burden, which is also linked to increased neoantigen load and enhanced response to anti-PD-1/L1 immunotherapy. The patients with a low-ferroptosis score showed a high microsatellite instability status (MSI-H) and had a higher response to immunotherapy. Furthermore, the patients with low-ferroptosis scores have a lower estimated IC50 in the several chemotherapy drugs, including paclitaxel, gemcitabine, and methotrexate.

Conclusions: We revealed that sex hormone receptors and immune cell infiltration were markedly different between ferroptosis subtypes in GC patients. The results suggested that gender difference may be critical when the ferroptosis-related strategy is applied in GC treatment. Further, ferroptosis levels were identified with an extreme variety of prognosis and tumor immune characteristics, which might benefit GC individualized treatment.

Identification of an m6A Regulators-Mediated Prognosis Signature For Survival Prediction and Its Relevance to Immune Infiltration in Melanoma

Despite robust evidence for the role of m6A in cancer development and progression, its association with immune infiltration and survival outcomes in melanoma remains obscure. Here, we aimed to develop an m6A-related risk signature to improve prognostic and immunotherapy responder prediction performance in the context of melanoma. We comprehensively analyzed the m6A cluster and immune infiltration phenotypes of public datasets. The TCGA (n = 457) and eleven independent melanoma cohorts (n = 758) were used as the training and validation datasets, respectively. We identified two m6A clusters (m6A-clusterA and m6A-clusterB) based on the expression pattern of m6A regulators via unsupervised consensus clustering. IGF2BP1 (7.49%), KIAA1429 (7.06%), and YTHDC1 (4.28%) were the three most frequently mutated genes. There was a correlation between driver genes mutation statuses and the expression of m6A regulators. A significant difference in tumor-associated immune infiltration between two m6A clusters was detected. Compared with m6A-clusterA, the m6A-clusterB was characterized by a lower immune score and immune cell infiltration but higher mRNA expression-based stemness index (mRNAsi). An m6A-related risk signature consisting of 12 genes was determined via Cox regression analysis and divided the patients into low- and high-risk groups (IL6ST, MBNL1, NXT2, EIF2A, CSGALNACT1, C11orf58, CD14, SPI1, NCCRP1, BOK, CD74, PAEP). A nomogram was developed for the prediction of the survival rate. Compared with the high-risk group, the low-risk group was characterized by high expression of immune checkpoints and immunophenoscore (IPS), activation of immune-related pathways, and more enriched in immune cell infiltrations. The low-risk group had a favorable prognosis and contained the potential beneficiaries of the immune checkpoint blockade therapy and verified by the IMvigor210 cohort (n = 298). The m6A-related signature we have determined in melanoma highlights the relationships between m6A regulators and immune cell infiltration. The established risk signature was identified as a promising clinical biomarker of melanoma.

Immune-Related LncRNAs Affect the Prognosis of Osteosarcoma, Which Are Related to the Tumor Immune Microenvironment

Background: Abnormal expression of lncRNA is closely related to the occurrence and metastasis of osteosarcoma. The tumor immune microenvironment (TIM) is considered to be an important factor affecting the prognosis and treatment of osteosarcoma. This study aims to explore the effect of immune-related lncRNAs (IRLs) on the prognosis of osteosarcoma and its relationship with the TIM.

Methods: Ninety-five osteosarcoma samples from the TARGET database were included. Iterative LASSO regression and multivariate Cox regression analysis were used to screen the IRLs signature with the optimal AUC. The predict function was used to calculate the risk score and divide osteosarcoma into a high-risk group and low-risk group based on the optimal cut-off value of the risk score. The lncRNAs in IRLs signature that affect metastasis were screened for in vitro validation. Single sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithms were used to evaluate the role of TIM in the influence of IRLs on osteosarcoma prognosis.

Results: Ten IRLs constituted the IRLs signature, with an AUC of 0.96. The recurrence and metastasis rates of osteosarcoma in the high-risk group were higher than those in the low-risk group. In vitro experiments showed that knockdown of lncRNA (AC006033.2) could increase the proliferation, migration, and invasion of osteosarcoma. ssGSEA and ESTIMATE results showed that the immune cell content and immune score in the low-risk group were generally higher than those in the high-risk group. In addition, the expression levels of immune escape-related genes were higher in the high-risk group.

Conclusion: The IRLs signature is a reliable biomarker for the prognosis of osteosarcoma, and they alter the prognosis of osteosarcoma. In addition, IRLs signature and patient prognosis may be related to TIM in osteosarcoma. The higher the content of immune cells in the TIM of osteosarcoma, the lower the risk score of patients and the better the prognosis. The higher the expression of immune escape-related genes, the lower the risk score of patients and the better the prognosis.

Clinical Significance and Immunologic Landscape of a Five-IL(R)-Based Signature in Lung Adenocarcinoma

Interleukins (ILs) and interleukin receptors (ILRs) play important role in the antitumor immune response. However, the expression signature and clinical characteristics of the IL(R) family in lung adenocarcinoma (LUAD) remains unclear. The main purpose of this study was to explore the expression profile of IL(R) family genes and construct an IL(R)-based prognostic signature in LUAD. Five public datasets of 1,312 patients with LUAD were enrolled in this study. Samples from The Cancer Genome Atlas (TCGA) were used as the training set, and samples from the other four cohorts extracted from Gene Expression Omnibus (GEO) database were used as the validation set. Additionally, the profile of IL(R) family signature was explored, and the association between this signature and immunotherapy response was also analyzed. Meanwhile, the prognostic value was compared between this IL(R)-based signature and different immunotherapy markers. A signature based on five identified IL(R)s (IL7R, IL5RA, IL20RB, IL11, IL22RA1) was constructed using the TCGA dataset through univariate/multivariable Cox proportional hazards regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. These cases with LUAD were stratified into high- and low-risk group according to the risk score. This signature showed a strong prognostic ability, which was verified by the five independent cohorts and clinical subtypes. The IL(R)-based models presented unique characteristics in terms of immune cell infiltration and immune inflammation profile in tumor microenvironment (TME). Biological pathway analysis confirmed that high-risk patients showed significant T- and B-cell immunosuppression and rapid tumor cell proliferation. More importantly, we researched the relationship between this IL(R)-based signature and immune checkpoints, tumor mutation burden (TMB), tumor purity and ploidy, and tumor immune dysfunction and exclusion (TIDE) score, which confirmed that this signature gave the best prognostic value. We first provided a robust prognostic IL(R)-based signature, which had the potential as a predictor for immunotherapy response to realize individualized treatment of LUAD.

Arginine Methyltransferase PRMT1 Regulates p53 Activity in Breast Cancer

The protein p53 is one of the most important tumor suppressors, responding to a variety of stress signals. Mutations in p53 occur in about half of human cancer cases, and dysregulation of the p53 function by epigenetic modifiers and modifications is prevalent in a large proportion of the remainder. PRMT1 is the main enzyme responsible for the generation of asymmetric-dimethylarginine, whose upregulation or aberrant splicing has been observed in many types of malignancies. Here, we demonstrate that p53 function is regulated by PRMT1 in breast cancer cells. PRMT1 knockdown activated the p53 signal pathway and induced cell growth-arrest and senescence. PRMT1 could directly bind to p53 and inhibit the transcriptional activity of p53 in an enzymatically dependent manner, resulting in a decrease in the expression levels of several key downstream targets of the p53 pathway. We were able to detect p53 asymmetric-dimethylarginine signals in breast cancer cells and breast cancer tissues from patients, and the signals could be significantly weakened by silencing of PRMT1 with shRNA, or inhibiting PRMT1 activity with a specific inhibitor. Furthermore, PRMT1 inhibitors significantly impeded cell growth and promoted cellular senescence in breast cancer cells and primary tumor cells. These results indicate an important role of PRMT1 in the regulation of p53 function in breast tumorigenesis.