Establishment of an Immune Cell Infiltration Score to Help Predict the Prognosis and Chemotherapy Responsiveness of Gastric Cancer Patients

The role of the SOX2 gene in cervical cancer: focus on ferroptosis and construction of a predictive model

BACKGROUND

The intricate interplay between stemness markers and cell death pathways significantly influences the pathophysiology of cervical cancer. SOX2, a pivotal regulator of stem cell pluripotency, has recently been implicated in the modulation of ferroptosis, a specialized form of iron-dependent cell death, in cancer dynamics. This study delineates the role of SOX2 in the ferroptotic landscape of cervical carcinoma.

OBJECTIVE

To delineate the association between SOX2 expression and ferroptosis in cervical cancer and develop a robust, SOX2-centric model for predicting prognosis and enhancing personalized treatment.

METHODS

A multidimensional approach integrating advanced bioinformatics, comprehensive molecular profiling, and state-of-the-art machine learning algorithms was employed to assess SOX2 expression patterns and their correlation with ferroptosis marker expression patterns in cervical cancer tissues. A prognostic model incorporating the expression levels of SOX2 and ferroptosis indicators was meticulously constructed.

RESULTS

This investigation revealed a profound and intricate correlation between SOX2 expression and ferroptotic processes in cervical cancer, substantiated by robust molecular evidence. The developed predictive model based on SOX2 expression exhibited superior prognostic accuracy and may guide therapeutic decision-making.

CONCLUSION

This study underscores the critical role of SOX2 in orchestrating the ferroptosis pathway in cervical cancer and presents a novel prognostic framework. The SOX2-centric predictive model represents a significant advancement in prognosis evaluation, offering a gateway to personalized treatment for gynaecologic cancers.

Comprehensive analysis of the expression level, prognostic value, and immune infiltration of cuproptosis-related genes in human breast cancer

BACKGROUND

As a novel cell death form, cuproptosis results from copper combining with lipidated proteins in the tricarboxylic acid cycle. To the best of our knowledge no study has yet comprehensively analyzed the relationship between cuproptosis-related genes and breast cancer.

METHODS

The expression, prognostic value, mutations, chemosensitivity, and immune infiltration of cuproptosis-related genes in breast carcinoma patients were analyzed, PPI networks were constructed, and enrichment analyses were performed based on these genes. TIMER, UALCAN, Kaplan-Meier plotter, Human Protein Atlas, cBioPortal, STRING, GeneMANIA, DAVID, and R program v4.0.3 were used to accomplish the analyses above.

RESULTS

Compared to normal breast tissues, FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, MTF1, and GLS were down-regulated in breast cancer tissues, while CDKN2A was up-regulated. High expression of FDX1, LIAS, DLD, DLAT, MTF1, GLS, and CDKN2A were associated with favorable overall survival. Cuproptosis-related genes showed a high alteration rate (51.3%) in breast cancer, contributing to worse clinical outcomes. The expression levels of FDX1, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A were associated positively with 1 or more immune cell infiltrations in breast cancer. Patients with high levels of B cell, CD4+ T cell, CD8+ T cell, and dendritic cell infiltration had a higher survival rate at 10 years.

CONCLUSION

This study comprehensively investigated relationships between cuproptosis and breast cancer by bioinformatic analyses. We found that cuproptosis-related genes were generally lowly expressed in breast carcinoma tissue. As the critical gene of cuproptosis, high expression of FDX1 was related to favorable prognoses in breast cancer patients; thus, it might be a potential prognostic marker. Moreover, genes associated with cuproptosis were linked to immune infiltration in breast cancer and this relationship affected the prognosis of breast cancer.

Exploring the mystery of colon cancer from the perspective of molecular subtypes and treatment

The molecular categorization of colon cancer patients remains elusive. Gene set enrichment analysis (GSEA), which investigates the dysregulated genes among tumor and normal samples, has revealed the pivotal role of epithelial-to-mesenchymal transition (EMT) in colon cancer pathogenesis. In this study, we employed multi-clustering method for grouping data, resulting in the identification of two clusters characterized by varying prognostic outcomes. These two subgroups not only displayed disparities in overall survival (OS) but also manifested variations in clinical variables, genetic mutation, and gene expression profiles. Using the nearest template prediction (NTP) method, we were able to replicate the molecular classification effectively within the original dataset and validated it across multiple independent datasets, underscoring its robust repeatability. Furthermore, we constructed two prognostic signatures tailored to each of these subgroups. Our molecular classification, centered on EMT, hold promise in offering fresh insights into the therapy strategies and prognosis assessment for colon cancer.

Development of a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma: Insights into Immune Cell Interactions and Drug Sensitivity

Esophageal squamous cell carcinoma (ESCC) presents a five-year survival rate below 20%, underscoring the need for improved prognostic markers. Our study analyzed ESCC-specific datasets to identify consistently differentially expressed genes. A Venn analysis followed by gene network interactions revealed 23 key genes, from which we built a prognostic model using the COX algorithm (p = 0.000245, 3-year AUC = 0.967). This model stratifies patients into risk groups, with high-risk individuals showing worse outcomes and lower chemotherapy sensitivity. Moreover, a link between risk scores and M2 macrophage infiltration, as well as significant correlations with immune checkpoint genes (e.g., SIGLEC15, PDCD1LG2, and HVCR2), was discovered. High-risk patients had lower Tumor Immune Dysfunction and Exclusion (TIDE) values, suggesting potential responsiveness to immune checkpoint blockade (ICB) therapy. Our efficient 23-gene prognostic model for ESCC indicates a dual utility in assessing prognosis and guiding therapeutic decisions, particularly in the context of ICB therapy for high-risk patients.

Ubiquilin-4 induces immune escape in gastric cancer by activating the notch signaling pathway

PURPOSE

We aimed to investigate the role of ubiquilin-4 in predicting the immunotherapy response in gastric cancer.

METHODS

Retrospective RNA-sequencing and immunohistochemical analysis were performed for patients with gastric cancer who received programmed death-1 blockade therapy after recurrence. Multiplex immunohistochemistry identified immune cell types in gastric cancer tissues. We used immunocompetent 615 mice and immunodeficient nude mice to perform tumorigenic experiments.

RESULTS

Ubiquilin-4 expression was significantly higher in responders (p < 0.05, false discovery rate > 2.5) and showed slight superiority over programmed death ligand 1 in predicting programmed death-1 inhibitor therapy response (area under the curve: 87.08 vs. 72.50). Ubiquilin-4-high patients exhibited increased CD4+ and CD8+ T cells, T follicular helper cells, monocytes, and macrophages. Ubiquilin-4-overexpressed mouse forestomach carcinoma cells showed significantly enhanced growth in immunocompetent mice but not in immunodeficient mice. Upregulation or downregulation of ubiquilin-4 synergistically affected programmed death ligand 1 at the protein and messenger RNA levels. Functional enrichment analysis revealed significant enrichment of the Notch, JAK-STAT, and WNT signaling pathways in ubiquilin-4-high gastric cancers. Ubiquilin-4 promoted Numb degaration, activating the Notch signaling pathway and upregulating programmed death ligand 1.

CONCLUSIONS

Ubiquilin-4 may contribute to immune escape in gastric cancer by upregulating programmed death ligand 1 expression in tumor cells through Notch signaling activation. Thus, ubiquilin-4 could serve as a predictive marker for programmed death ligand 1 inhibitor therapy response in gastric cancer.

SLA2 is a prognostic marker in HNSCC and correlates with immune cell infiltration in the tumor microenvironment

PURPOSE

To investigate Src-like adaptor 2 gene (SLA2) expression in head and neck squamous cell carcinoma (HNSCC), its potential prognostic value, and its effect on immune cell infiltration.

METHODS

Through a variety of bioinformatics analyses, we extracted and analyzed data sets from the Cancer Genome Atlas (TCGA), Tumor Immune Estimation Resource (TIMER), and Gene Expression Profile Interaction Analysis (GEPIA) to analyze the correlation between SLA2 and the prognosis, immune checkpoint, tumor microenvironment (TME) and immune cell infiltration of HNSCC, and to explore its potential oncogenic mechanism. To further explore the potential role of SLA2 in HNSCC by Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

RESULTS

SLA2 messenger ribonucleic acid (mRNA) levels were increased in HNSCC tumor tissues compared with normal tissues. In addition, we found that SLA2 may be an independent prognostic factor for HNSCC, and high SLA2 expression is associated with favorable prognosis in HNSCC. SLA2 expression was positively correlated with B cells, cluster of differentiation 8-positive T cells (CD8 + T cells), cluster of differentiation 4-positive T cells (CD4 + T cells), macrophages, neutrophil and dendritic cells infiltration. SLA2 has also been shown to co-express immune-related genes and immune checkpoints. Significant GO term analysis by Gene Set Enrichment Analysis (GSEA) indicated that genes correlated with SLA2 were located mainly in the side of membrane, receptor complex, secretory granule membrane, endocytic vesicle, membrane region, and endosome membrane, where they were involved in leukocyte cell-cell adhesion, response to interferon-gamma, and regulation of immune effector process. These related genes also served as antigen binding, cytokine receptor activity, phosphatidylinositol 3-kinase activity, peptide receptor activity, Src homology domain 3 (SH3) domain binding, and cytokine receptor binding. KEGG pathway analysis demonstrated that these genes related to SLA2 were mainly enriched in signal pathways, such as hematopoietic cell lineage, cell adhesion molecules (CAMs), natural killer cell mediated cytotoxicity, measles, and chemokine signaling pathway.

CONCLUSIONS

SLA2 is increased in HNSCC, and high SLA2 expression is associated with favorable prognosis. SLA2 may affect tumor development by regulating tumor infiltrating cells in TME. SLA2 may be a potential target for immunotherapy.

A modified immune cell infiltration score achieves ideal stratification for CD8+ T cell efficacy and immunotherapy benefit in hepatocellular carcinoma

Immunotherapy, which aims to enhance the function of T cells, has emerged as a novel therapeutic approach for hepatocellular carcinoma (HCC). Nevertheless, the clinical utility of using flow cytometry to assess immune cell infiltration (ICI) is hindered by its cumbersome procedures, prompting the need for more accessible methods. Here, we acquired gene expression profiles and survival data of HCC from TCGA and GSE10186 datasets. The patients were categorized into two clusters of ICI, and a set of 11 characteristic genes responsible for the differentiation performance of these ICI clusters were identified. Subsequently, we successfully developed a modified ICI score (mICIS) by utilizing the expression levels of these genes. The efficacy of our mICIS was confirmed via mass cytometry, flow cytometry, and immunohistochemistry. Our research indicated that the favorable overall survival (OS) rate could be attributed to the improved function of anti-tumor leukocytes rather than their infiltration. Furthermore, we observed that the low score group exhibited lower expression levels of T-cell exhaustion-associated genes, which was confirmed in both HCC tissues from patients and mice, which demonstrated that the benefits of the low scores were due to enhanced active/cytotoxic CD8+ T cells and reduced exhausted CD8+ T cells. Additionally, our mICIS stratified the benefits derived from immunotherapies. Lastly, we observed a misalignment between CD8+ T-cell infiltration and function in HCC. In summary, our mICIS demonstrated proficiency in assessing the OS rate of HCC and offering significant stratified data pertaining to distinct responses to immunotherapy.

Investigation of LGALS2 expression in the TCGA database reveals its clinical relevance in breast cancer immunotherapy and drug resistance

Breast cancer (BRCA) is known as the leading cause of death in women worldwide and has a poor prognosis. Traditional therapeutic strategies such as surgical resection, radiotherapy and chemotherapy can cause adverse reactions such as drug resistance. Immunotherapy, a new treatment approach with fewer side effects and stronger universality, can prolong the survival of BRCA patients and even achieve clinical cure. However, due to population heterogeneity and other reasons, there are still certain factors that limit the efficacy of immunotherapy. Therefore, the importance of finding new tumor immune biomarker cannot be emphasized enough. Studies have reported that LGALS2 was closely related to immunotherapy efficacy, however, it is unclear whether it can act as an immune checkpoint for BRCA immunotherapy. In the current study, changes in LGALS2 expression were analyzed in public datasets such as TCGA-BRCA. We found that LGALS2 expression was associated with immune infiltration, drug resistance and other characteristics of BRCA. Moreover, high LGALS2 expression was closely related to immunotherapy response, and was associated with methylation modifications and clinical resistance for the first time. These findings may help to elucidate the role of LGALS2 in BRCA for the development and clinical application of future immunotherapy strategies against BRCA.

The multi-omics analyses of acsl1 reveal its translational significance as a tumor microenvironmental and prognostic biomarker in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of kidney cancer. Dysregulation of long-chain acyl-CoA synthetase 1 (ACSL1) is strongly implicated in undesirable results in varieties of cancers. Nevertheless, the dysregulation and associated multi-omics characteristics of ACSL1 in ccRCC remain elusive.

METHODS

We probed the mRNA and protein profiles of ACSL1 in RCC using data from the Cancer Genome Atlas, Gene Expression Omnibus, the Human Protein Atlas (HPA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) and verified them in our patient cohort and RCC cell lines. Correlations between ACSL1 expression and clinicopathological features, epigenetic modification and immune microenvironment characteristics were analyzed to reveal the multi-omics profile associated with ACSL1.

RESULTS

ACSL1 was down-regulated in ccRCC tissues compared to adjacent normal tissues. Lower expression of ACSL1 was linked to unfavorable pathological parameters and prognosis. The dysregulation of ACSL1 was greatly ascribed to CpG island-associated methylation modification. The ACSL1 high-expression subgroup had enriched fatty acid metabolism-related pathways and high expression of ferroptosis-related genes. In contrast, the ACSL1 low-expression subgroup exhibited higher immune and microenvironment scores, elevated expression of immune checkpoints PDCD1, CTLA4, LAG3, and TIGIT, and higher TIDE scores. Using data from the GDSC database, we corroborated that down-regulation of ACSL1 was associated with higher sensitivity towards Erlotinib, Pazopanib, and PI3K-Akt-mTOR-targeted therapeutic strategies.

CONCLUSION

Taken together, our findings point to ACSL1 as a biomarker for prognostic prediction of ccRCC, identifying the tumor microenvironment (TME) phenotype, and even contributing to treatment decision-making in ccRCC patients.

Construction of an m6A-related lncRNA model for predicting prognosis and immunotherapy in patients with lung adenocarcinoma

N6-methyladenosine (m6A)-related lncRNAs could be involved in the development of multiple tumors with an unknown role in lung adenocarcinoma (LUAD). Hence, gene expression data and clinical data of LUAD patients were acquired from The Cancer Genome Atlas Database. The prognostic m6A-related lncRNAs were identified through differential lncRNA expression analysis and Spearman's correlation analysis. The least absolute shrinkage and selection operator regression was used to establish the prognostic risk model, so as to evaluate and validate the predictive performance with survival analysis and receiver operating characteristic curve analysis. The expression of immune checkpoints, immune cell infiltration and drug sensitivity of patients in different risk groups were analyzed separately. A total of 19 prognostic m6A-related lncRNAs were identified to set up the prognostic risk model. The patients were divided into high- and low-risk groups based on the median value of the risk scores. Compared with the patients in the low-risk group, the prognosis of the patients in the high-risk group was relatively worse. The receiver operating characteristic curves indicated that this model had excellent sensitivity and specificity. Multivariate Cox regression analysis demonstrated that the risk score could be supposed as an independent prognostic risk factor. We highlighted that the risk scores were correlated with immune cell infiltration and drug sensitivity for constructing a prognostic risk model in LUAD patients based on m6A-related lncRNAs.

Clinical significance and integrative analysis of the cuproptosis-associated genes in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is a kind of malignant tumor originating from the oropharynx, larynx, nasopharynx and oral cavity. The incidence of HNSC is increasing and it is the sixth malignant tumor in the world at present. "Cuprotosis" is a novel cuper-dependent cell death mode that is closely related to mitochondrial respiration. Tumorigenesis is closely related to the dysregulation of cell death. However, the relationship between cuprotosis and HNSC remains unclear. Here, we investigated the association between 10 cuprotosis-associated genes (CAGs) and HNSC using multi-omics public data. We found that CAGs had abnormal expression and significant genetic changes in HNSC, especially CDKN2A with 54% mutation rate. Expression of CAGs significantly correlates with the prognosis of HNSC patients. Moreover, the CAGs expression is correlated with the immune checkpoints expression and immune cells infiltration. These CAGs expression was associated with multiple drugs sensitivity of cancer cells, such as cisplatin and docetaxel. These findings indicate that CAGs are likely to serve an essential role in the diagnosis, prognosis, immunotherapy and drug therapy prediction of HNSC.

Hsa_circ_0015278 Regulates FLT3-ITD AML Progression via Ferroptosis-Related Genes

AML with the FLT3-ITD mutation seriously threatens human health. The mechanism by which circRNAs regulate the pathogenesis of FLT3-ITD mutant-type AML through ferroptosis-related genes (FerRGs) remains unclear. Differentially expressed circRNAs and mRNAs were identified from multiple integrated data sources. The target miRNAs and mRNAs of the circRNAs were predicted using various databases. The PPI network, ceRNA regulatory network, GO, and KEGG enrichment analyses were performed. The "survival" and the "pROC" R packages were used for K-M and ROC analysis, respectively. GSEA, immune infiltration analysis, and clinical subgroup analysis were performed. Finally, circRNAs were validated by Sanger sequencing and qRT-PCR. In our study, 77 DECircs-1 and 690 DECircs-2 were identified. Subsequently, 11 co-up-regulated DECircs were obtained by intersecting DECircs-1 and DECircs-2. The target miRNAs of the circRNAs were screened by CircInteractome, circbank, and circAtlas. Utilizing TargetScan, ENCORI, and miRWalk, the target mRNAs of the miRNAs were uncovered. Ultimately, 73 FerRGs were obtained, and the ceRNA regulatory network was constructed. Furthermore, MAPK3 and CD44 were significantly associated with prognosis. qRT-PCR results confirmed that has_circ_0015278 was significantly overexpressed in FLT3-ITD mutant-type AML. In summary, we constructed the hsa_circ_0015278/miRNAs/FerRGs signaling axis, which provides new insight into the pathogenesis and therapeutic targets of AML with FLT3-ITD mutation.

A novel signature based on CeRNA and immune status predicts prognostic risk and drug sensitivity in gastric cancer patients

Background

At present, there is increasing evidence that both competitive endogenous RNAs (ceRNAs) and immune status in the tumor microenvironment (TME) can affect the progression of gastric cancer (GC), and are closely related to the prognosis of patients. However, few studies have linked the two to jointly determine the prognosis of patients with GC. This study aimed to develop a combined prognostic model based on ceRNAs and immune biomarkers.

Methods

First, the gene expression profiles and clinical information were downloaded from TCGA and GEO databases. Then two ceRNA networks were constructed on the basis of circRNA. Afterwards, the key genes were screened by univariate Cox regression analysis and Lasso regression analysis, and the ceRNA-related prognostic model was constructed by multivariate Cox regression analysis. Next, CIBERSORT and ESTIMATE algorithms were utilized to obtain the immune cell infiltration abundance and stromal/immune score in TME. Furthermore, the correlation between ceRNAs and immunity was found out through co-expression analysis, and another immune-related prognosis model was established. Finally, combining these two models, a comprehensive prognostic model was built and visualized with a nomogram.

Results

The (circRNA, lncRNA)-miRNA-mRNA regulatory network of GC was constructed. The predictive power of ceRNA-related and immune-related prognosis models was moderate. Co-expression analysis showed that the ceRNA network was correlated with immunity. The integrated model of combined ceRNAs and immunity in the TCGA training set, the AUC values of 1, 3, and 5-year survival rates were 0.78, 0.76, and 0.78, respectively; in the independent external validation set GSE62254, they were 0.81, 0.79, and 0.78 respectively; in GSE15459, they were 0.84, 0.88 and 0.89 respectively. Besides, the prognostic score of the comprehensive model can predict chemotherapeutic drug resistance. Moreover, we found that plasma variant translocation 1 (PVT1) and infiltrating immune cells (mast cells) are worthy of further investigation as independent prognostic factors.

Conclusions

Two ceRNA regulatory networks were constructed based on circRNA. At the same time, a comprehensive prognosis model was established, which has a high clinical significance for prognosis prediction and chemotherapy drug selection of GC patients.

A Comprehensive Evaluation of Prognostic Value and Immune Infiltration of KDM1 Family in Hepatocellular Carcinoma

INTRODUCTION

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies in the world. Previous studies indicated that the expression of the KDM1 genes (KDM1s), members of the amine oxidase superfamily, has prognostic value for breast and prostate cancer and malignant neuroblastoma. This study aimed to investigate the expression of KDM1s, their prognostic value, and their correlation with immune infiltration in patients with HCC.

METHODS

Multiomics analyses were utilized to analyze differential expression, prognostic value, genetic alteration, and immune cell infiltration of KDM1s in patients with HCC.

RESULTS

The high expression of KDM1A indicated poor overall survival (OS) and disease-free survival, whereas the high expression of KDM1B was significantly associated with poor OS. The genetic alterations and biological interaction network of KDM1s may provide detailed information for the dysregulated function of KDM1s in patients with HCC. KDM1-related signaling pathways and miRNA targets were explored and may provide value as therapeutic targets or tumor progression markers. The increased mRNA expression of KDM1s was significantly correlated with the infiltration of diverse immune cells in HCC.

CONCLUSIONS

This data-driven study indicates that KDM1s are promising prognostic biomarkers for survival and have the potential to become novel molecular targets in HCC treatments.

A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies

Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers.

Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model.

Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p < 0.001, HR: 3.81, 95% CI: 2.44–5.956) and GSE15459 (p < 0.001, HR: 2.65, 95% CI: 1.892–3.709) cohorts and the external validation GSE84437 cohort (p < 0.001, HR: 2.06, 95% CI: 1.554–2.735). The nomogram constructed based on two independent predictive factors, tumor stage and the signature, predicted events tightly consistent with the actual (Hosmer–Lemeshow p value: 1-year, 0.624; 3-years, 0.795; 5-years, 0.824). For the molecular features, we observed the activation of apical junction, epithelial mesenchymal transition, and immune pathways in the high-risk group, while in the low-risk group, cell cycle associated G2M, E2F and MYC target pathways were activated. Based on the results we obtained, we indicated that gastric patients in the low-risk group are more suitable for 5-fluorouracil therapy, while high-risk group patients are more suitable for anti-CTLA4 immunotherapy, these results need more support in the further studies. After compare with proposed molecular subtypes, we realized that the nine-consensus prognostic gene signature is a powerful addition to identify the gastric patients with poor prognosis.

Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.

Pan-cancer analysis reveals interleukin-17 family members as biomarkers in the prediction for immune checkpoint inhibitor curative effect

Background

The interleukin-17 (IL-17) family contains six homologous genes, IL-17A to IL-17F. Growing evidence indicates that dysregulated IL-17 family members act as major pathogenic factors in the early and late stages of cancer development and progression. However, the prevalence and predictive value of IL-17 for immune checkpoint inhibitor (ICI) therapeutic effectiveness in multiple tumor types remain largely unknown, and the associations between its expression levels and immunotherapy-associated signatures also need to be explored.

Methods

The pan-cancer dataset in The Cancer Genome Atlas (TCGA) was downloaded from UCSC Xena (http://xena.ucsc.edu/). The immunotherapeutic cohorts included IMvigor210, which were obtained from the Gene Expression Omnibus database and included in a previously published study. Other datasets, namely, the GEO dataset and PRECOG, GEO, and METABRIC databases, were also included. In 33 TCGA tumor types, a pan-cancer analysis was carried out including their expression map, clinical risk assessment, and immune subtype analysis, along with their association with the stemness indices, tumor microenvironment (TME) in pan-cancer, immune infiltration analysis, ICI-related immune indicators, and drug sensitivity. RT-PCR was also carried out to verify the gene expression levels among MCF-10A and MCF-7 cell lines.

Results

The expression of the IL-17 family is different between tumor and normal tissue in most cancers, and consistency has been observed between gene activity and gene expression. RT-PCR results show that the expression differences in the IL-17 family of human cell (MCF-10A and MCF-7) are consistent with the bioinformatics differential expression analysis. Moreover, the expression of the IL-17 family can be a sign of patients’ survival prognosis in some tumors and varies in different immune subtypes. Moreover, the expression of the IL-17 family presents a robust correlation with immune cell infiltration, ICI-related immune indicators, and drug sensitivity. High expression of the IL-17 family is significantly related to immune-relevant pathways, and the low expression of IL-17B means a better immunotherapeutic response in BLCA.

Conclusion

Collectively, IL-17 family members may act as biomarkers in predicting the prognosis of the tumor and the therapeutic effects of ICIs, which provides new guidance for cancer treatment.

Tertiary lymphoid structure patterns predicted anti-PD1 therapeutic responses in gastric cancer

OBJECTIVE

Recent studies have highlighted the distinct value of tertiary lymphoid structure (TLS) for immunotherapeutic response prediction. However, it remains unclear whether TLS could play such roles in gastric cancer (GC).

METHODS

In this study, tumor tissue slices from 292 GC patients from Zhongshan Hospital were firstly reviewed to explore the correlation between TLS and clinical characteristics. Subsequently, we curated 38 reported genes that may function as triggers of TLS and performed consensus molecular subtyping in public RNA-seq datasets to determine TLS patterns in GC. Based on the differentially expressed genes acquired from two TLS patterns, we quantified TLS-related genes on the principal component analysis (PCA) algorithm to develop TLS score. A Zhongshan immunotherapy cohort including 13 patients who received programmed cell death 1 (PD1) blockade therapy was established to conduct RNA sequencing analysis and multiplex immunohistochemistry (mIHC) tests using formalin-fixed and paraffin-embedded (FFPE) tissues. The corresponding TLS score and immune cell counts were further compared based on therapeutic response variations.

RESULTS

Mature TLS was revealed as an independent prognostic factor in 292 GC patients. Patients with higher TLS score was characterized by prolonged survival time and superior response to immunotherapy. TLS score was correlated with immunotherapy-related characters, such as microsatellite instability (MSI) and tumor mutation burden (TMB). In addition, RNA-seq data analysis in the Zhongshan immunotherapy cohort indicated that a higher TLS score was correlated with a superior response to PD1 blockade therapy. mIHC tests also revealed that PD1+CD8+ T cell counts were significantly increased in the high-TLS score group.

CONCLUSIONS

This study highlighted that TLS was significantly associated with immune landscape diversity and complexity. Quantitatively evaluating TLS patterns of individual tumor will strengthen our understanding of TME characteristics and promote more effective immunotherapy strategies.

KLHL14: A Novel Prognostic Biomarker and Therapeutic Target for Ovarian Cancer

Ovarian cancer (OV) is a gynaecological malignancy that poses a serious risk to the health status of women. To date, effective molecular markers are unavailable for the diagnosis and management of ovarian malignancies. In this study, we aimed to investigate the molecular markers associated with the development of this cancer. We used bioinformatic analysis to determine the molecules and genes related to ovarian cancer using the gene expression profiling interactive analysis (GEPIA) and the cancer genome Atlas (TCGA) databases. In addition, we examined the genes and mechanisms underlying ovarian cancer. Our results showed that the KLHL14 gene is overexpressed in some cancers. An increase in the KLHL14 expression indicates a poor prognosis in patients with ovarian cancer. Results of immune cell infiltration analysis and half-maximal inhibitory concentration (IC50) analysis provide novel insights into the treatment of ovarian cancer. KLHL14 is anticipated to emerge as a novel molecular marker specifically for ovarian carcinoma.

Computational-Model-Based Biopharmaceutics for p53 Pathway Using Modern Control Techniques for Cancer Treatment

The p53 pathway has been the focus of many researchers in the last few decades owing to its pivotal role as a frontline cancer suppressant protein. It plays a vital role in maintaining cell cycle checkpoints and cell apoptosis in response to a broken DNA strand. This is why it is found in the mutated form in more than 50% of malignant tumors. To overcome this, various drugs have been proposed to revive the p53 pathway in cancer patients. Small-molecule-based drugs, such as Nutlin 3a, which are capable of performing this stimulation, are at the fore of advanced clinical trials. However, the calculation of their dosage is a challenge. In this work, a method to determine the dosage of Nutlin 3a is investigated. A control-systems-based model is developed to study the response of the wild-type p53 protein to this drug. The proposed strategy regulates the p53 protein along with negative and positive feedback loops mediated by the MDM2 and MDM2 mRNA, respectively, along with the reversible repression of MDM2 caused by Nutlin 3a. For a broader perspective, the reported PBK dynamics of Nutlin 3a are also incorporated. It has been reported that p53 responds to stresses in two ways in terms of concentration to this drug: either it is a sustained (constant) or an oscillatory response. The claimed dosage strategy turned out to be appropriate for sustained p53 response. However, for the induction of oscillations, inhibition of MDM2 is not enough; rather, anti-repression of the p53–MDM2 complex is also needed, which opens new horizons for a new drug design paradigm.

Comprehensive Analysis of the Expression and Prognostic Value of LMAN2 in HER2+ Breast Cancer

Lectin, Mannose Binding 2 (LMAN2) encodes a type I transmembrane lectin that shuttles between the plasma membrane, the Golgi apparatus, and the endoplasmic reticulum. However, its expression, prognosis, and function in invasive breast carcinoma remain unknown. Nine databases were consulted to evaluate LMAN2 expression and prognosis in breast cancer. The possible function of LMAN2 in breast cancer was investigated in the Human Cell Landscape (HCL) database, Gene Regulatory Network database (GRNdb), and CancerSEA database. Moreover, N6-methyladenosine (m6A) modifications were analyzed using the RMBase v2.0 and M6A2Target databases. Seven databases were then used to analyze the potential action mechanisms of LMAN2. Our findings suggest that LMAN2, which is expressed at a high level in breast cancer, is linked to an unfavorable prognosis. Therefore, LMAN2 has the potential to be utilized as a treatment target in breast cancer. Furthermore, the single-cell analysis illustrated that LMAN2 expression had a positive link to breast cancer stemness, proliferation, metastasis, and differentiation. Moreover, m6A modifications were found in the LMAN2 gene. Consequently, modifications to m6A methylation may influence LMAN2 expression, which is associated with the homologous recombination (HR) in its DNA damage repair pathway .

Dissecting the Role of Immune Checkpoint Regulation Patterns in Tumor Microenvironment and Prognosis of Gastric Cancer

Many studies suggest that immune checkpoint molecules play a vital role in tumor progression and immune responses. However, the impact of the comprehensive regulation pattern of immune checkpoint molecules on immune responses, tumor microenvironment (TME) formation, and patient prognosis is poorly understood. In this study, we evaluated immune checkpoint regulation patterns in 1,174 gastric cancer (GC) samples based on 31 immune checkpoint genes (ICGs). Three distinct immune checkpoint regulation patterns with significant prognostic differences were ultimately identified. Moreover, GC patients were divided into two subgroups according to immune checkpoint score (ICscore). Patients with lower ICscore were characterized by a favorable prognosis and enhanced immune infiltration as well as an increased tumor mutation burden, non-recurrence, and microsatellite instability-high. Collectively, this study indicated that immune checkpoint regulation patterns were essential to forming the diversity of TME and a better understanding of that will contribute to assessing the characteristics of TME in GC, which intends to improve the development of immunotherapy.

Characterization of the Different Subtypes of Immune Cell Infiltration to Aid Immunotherapy

Background?PD-1 ablation or PD-L1 specific monoclonal antibody against PD-1 can recruit the accumulation of functional T cells, leading to tumor rejection in the microenvironment and significantly improving the prognosis of various cancers. Despite these unprecedented clinical successes, intervention remission rates remain low after treatment, rarely exceeding 40%. The observation of PD-1/L1 blocking in patients is undoubtedly multifactorial, but the infiltrating degree of CD8+T cell may be an important factor for immunotherapeutic resistance.

Methods:We proposed two computational algorithms to reveal the immune cell infiltration (ICI) landscape of 1646 lung adenocarcinoma patients. Three immune cell infiltration patterns were defined and the relative ICI scoring depended on principal-component analysis.

Results:A high ICI score was associated with the increased tumor mutation burden and cell proliferation-related signaling pathways. Different cellular signaling pathways were observed in low ICI score subtypes, indicating active cell proliferation, and may be associated with poor prognosis.

Conclusion:Our research identified that the ICI scores worked as an effective immunotherapy index, which may provide promising therapeutic strategies on immune therapeutics for lung adenocarcinoma.

Identification of a Novel Survival-Related circRNA–miRNA–mRNA Regulatory Network Related to Immune Infiltration in Liver Hepatocellular Carcinoma

Increasing studies have reported that circular RNAs (circRNAs) play critical roles in tumorigenesis and cancer progression. However, the underlying regulatory mechanisms of circRNA-related competing endogenous RNA (ceRNA) in liver hepatocellular carcinoma (LIHC) are still unclear. In the present study, we discovered dysregulated circRNAs through Gene Expression Omnibus (GEO) analysis and validated the expression of the top seven circRNAs with upregulated expression by qRT–PCR and Sanger sequencing. Then, the Cancer-Specific CircRNA Database (CSCD) was used to predict the downstream miRNAs of seven circRNAs, and expression and survival analyses through The Cancer Genome Atlas (TCGA) were performed to identify the key miRNA in LIHC. Thereafter, the hsa_circ_0017264-hsa-miR-195–5p subnetwork was successfully constructed. Subsequently, we predicted downstream target genes of hsa-miR-195–5p with TargetScan, miRDB, and mirtarbase and overlapped them with differentially expressed mRNAs to obtain 21 target genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to predict the biological and functional roles of these target genes. Finally, with Pearson correlation and prognostic value analysis, a survival-related hsa_circ_0017264-hsa-miR-195-5p-CHEK1/CDC25A/FOXK1 axis was established. Gene set enrichment analysis (GSEA) was performed to determine the function of CHEK1/CDC25A/FOXK1 in the ceRNA network. Moreover, immune infiltration analysis revealed that the ceRNA network was markedly associated with the levels of multiple immune cell infiltrates, immune cell biomarkers and immune checkpoints. Overall, the hsa_circ_0017264-hsa-miR-195-5p-CHEK1/CDC25A/FOXK1 network might provide novel insights into the potential mechanisms underlying LIHC onset and progression.

Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Gastric cancer (GC) is a malignant tumor with poor survival outcomes. Immunotherapy can improve the prognosis of many cancers, including GC. However, in clinical practice, not all cancer patients are sensitive to immunotherapy. Therefore, it is essential to identify effective biomarkers for predicting the prognosis and immunotherapy sensitivity of GC. In recent years, chemokines have been widely reported to regulate the tumor microenvironment, especially the immune landscape. However, whether chemokine-related lncRNAs are associated with the prognosis and immune landscape of GC remains unclear. In this study, we first constructed a novel chemokine-related lncRNA risk model to predict the prognosis and immune landscape of GC patients. By using various algorithms, we identified 10 chemokine-related lncRNAs to construct the risk model. Then, we determined the prognostic efficiency and accuracy of the risk model. The effectiveness and accuracy of the risk model were further validated in the testing set and the entire set. In addition, our risk model exerted a crucial role in predicting the infiltration of immune cells, immune checkpoint genes expression, immunotherapy scores and tumor mutation burden of GC patients. In conclusion, our risk model has preferable prognostic performance and may provide crucial clues to formulate immunotherapy strategies for GC.

Construction of an Immune Cell Infiltration Score to Evaluate the Prognosis and Therapeutic Efficacy of Ovarian Cancer Patients

Background

Ovarian cancer (OC) is an immunogenetic disease that contains tumor-infiltrating lymphocytes (TILs), and immunotherapy has become a novel treatment for OC. With the development of next-generation sequencing (NGS), profiles of gene expression and comprehensive landscape of immune cells can be applied to predict clinical outcome and response to immunotherapy.

Methods

We obtained data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and applied two computational algorithms (CIBERSORT and ESTIMATE) for consensus clustering of immune cells. Patients were divided into two subtypes using immune cell infiltration (ICI) levels. Then, differentially expressed genes (DEGs) associated with immune cell infiltration (ICI) level were identified. We also constructed ICI score after principle-component analysis (PCA) for dimension reduction.

Results

Patients in ICI cluster B had better survival than those in ICI cluster A. After construction of ICI score, we found that high ICI score had better clinical OS and significantly higher tumor mutation burden (TMB). According to the expression of immune checkpoints, the results showed that patients in high ICI group showed high expression of CTLA4, PD1, PD-L1, and PD-L2, which implies that they might benefit from immunotherapy. Besides, patients in high ICI group showed higher sensitivity to two first-line chemotherapy drugs (Paclitaxel and Cisplatin).

Conclusion

ICI score is an effective prognosis-related biomarker for OC and can provide valuable information on the potential response to immunotherapy.

A novel lncRNA-miRNA-mRNA competing endogenous RNA regulatory network in lung adenocarcinoma and kidney renal papillary cell carcinoma

Background

GPRIN1 may be a novel tumor regulator, but its role and mechanism in tumors are still unclear.

Methods

First, a pan‐cancer correlation analysis was conducted on the expression and prognosis of GPRIN1 based on the data downloaded from The Cancer Genome Atlas (TCGA) database. Second, the Starbase database was used to predict the upstream miRNAs and lncRNAs of GPRIN1, and the expression analysis, survival analysis, and correlation analysis were performed to screen the microRNA (miRNAs)/long non‐coding RNAs (lncRNAs) that had a correlation with kidney renal papillary cell carcinoma (KIRP) or lung adenocarcinoma (LUAD). Third, the CIBERSORT algorithm was employed to calculate the proportion of various types of immune cells, and then the R packages were used for evaluating the relation between GPRIN1 expression and tumor immune cell infiltration as well as between GPRIN1 and the immune cell biomarker. Finally, the correlation analysis was made on GPRIN1 and immune checkpoints (CD274, CTLA4, and PDCD1).

Results

The pan‐cancer analysis suggested that GPRIN1 was up‐expressed in KIRP and LUAD, and it correlated with poor prognosis. LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG‐miR‐140‐3p was likely to be the most promising upstream regulation pathway of GPRIN1. Upexpression of LINC00894/MMP25‐AS1/SNHG1/LINC02298/MIR193BHG and downexpression of miR‐140‐3p were found relevant with poor outcomes of KIRP and LUAD. GPRIN1 expression was significantly correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoints.

Conclusions

The competitive endogenous (ceRNA) of miR‐140‐3p‐GPRIN1 axis and its upstream lncRNAs are closely related to KIRP and LUAD, and might affect the prognosis and therapeutic effect of KIRP and LUAD.