Identification of tumor antigens and immune subtypes of pancreatic adenocarcinoma for mRNA vaccine development

Current status of vaccine immunotherapy for gastrointestinal cancers

Recent advances in tumor immunology and molecular drug development have ushered in a new era of cancer immunotherapy. Immunotherapy has shown promising results for several types of tumors, such as advanced melanoma, non-small cell lung cancer, renal cell carcinoma, bladder cancers, and refractory Hodgkin's lymphoma. Similarly, efforts have been made to develop immunotherapies such as adoptive T-cell transplantation, peptide vaccines, and dendritic cell vaccines, specifically for gastrointestinal tumors. However, before the advent of immune checkpoint inhibitors, immunotherapy did not work as well as expected. In this article, we review immunotherapy, focusing on cancer vaccines for gastrointestinal tumors, which generally target eliciting tumor-specific CD8 + cytotoxic T lymphocytes (CTLs). We also review various vaccine therapies and describe the relationship between vaccines and adjuvants. Finally, we discuss prospects for the combination of immunotherapy with immune checkpoint inhibitors.

Revealing a cancer-associated fibroblast-based risk signature for pancreatic adenocarcinoma through single-cell and bulk RNA-seq analysis

PURPOSE

Proliferation of stromal connective tissue is a hallmark of pancreatic adenocarcinoma (PAAD). The engagement of activated cancer-associated fibroblasts (CAFs) contributes to the progression of PAAD through their involvement in tumor fibrogenesis. However, the prognostic significance of CAF-based risk signature in PAAD has not been explored.

METHODS

The single-cell RNA sequencing (scRNA-seq) data sourced from GSE155698 within the Gene Expression Omnibus (GEO) database was supplemented by bulk RNA sequencing data from The Cancer Genome Atlas (TCGA) and microarray data retrieved from the GEO database. The scRNA-seq data underwent processing via the Seurat package to identify distinct CAF clusters utilizing specific CAF markers. Differential gene expression analysis between normal and tumor samples was conducted within the TCGA-PAAD cohort. Univariate Cox regression analysis pinpointed genes associated with CAF clusters, identifying prognostic CAF-related genes. These genes were utilized in LASSO regression to craft a predictive risk signature. Subsequently, integrating clinicopathological traits and the risk signature, a nomogram model was constructed.

RESULTS

Our scRNA-seq analysis unveiled four distinct CAF clusters in PAAD, with two linked to PAAD prognosis. Among 207 identified DEGs, 148 exhibited significant correlation with these CAF clusters, forming the basis of a seven-gene risk signature. This signature emerged as an independent predictor in multivariate analysis for PAAD and demonstrated predictive efficacy in immunotherapeutic outcomes. Additionally, a novel nomogram, integrating age and the CAF-based risk signature, exhibited robust predictability and reliability in prognosticating PAAD. Moreover, the risk signature displayed substantial correlations with stromal and immune scores, as well as specific immune cell types.

CONCLUSIONS

The prognosis of PAAD can be accurately predicted using the CAF-based risk signature, and a thorough analysis of the PAAD CAF signature may aid in deciphering the patient's immunotherapy response and presenting fresh cancer treatment options.

Clinical signature and associated immune metabolism of NLRP1 in pan-cancer

Inflammations have been linked to tumours, suggesting a potential association between NLRP1 and cancer. Nevertheless, a systematic assessment of NLRP1's role across various cancer types currently absent. A comprehensive bioinformatic analysis was conducted to determine whether NLRP1 exhibits prognostic relevance linked to immune metabolism across various cancers. The study leveraged data from the TCGA and GTEx databases to explore the clinical significance, metabolic features, and immunological characteristics of NLRP1, employing various tools such as R, GEPIA, STRING and TISIDB. NLRP1 exhibited differential expression patterns across various cancers, with elevated expression correlating with a more favourable prognosis in lung adenocarcinoma (LUAD) and pancreatic adenocarcinoma (PAAD). Downregulation of NLRP1 reduced tumour metabolic activity in LUAD. Moreover, the mutational signature of NLRP1 was linked to a favourable prognosis. Interestingly, high NLRP1 expression inversely correlated with tumour stemness while positively correlating with tumour immune infiltration in various cancers including LUAD and PAAD. Through extensive big data analysis, we delved into the role of NLRP1 across various tumour types, constructing a comprehensive role map of its involvement in pan-cancer scenarios. Our findings highlight the potential of NLRP1 as a promising therapeutic target specifically in LUAD and PAAD.

mRNA vaccines in tumor targeted therapy: mechanism, clinical application, and development trends

Malignant tumors remain a primary cause of human mortality. Among the various treatment modalities for neoplasms, tumor vaccines have consistently shown efficacy and promising potential. These vaccines offer advantages such as specificity, safety, and tolerability, with mRNA vaccines representing promising platforms. By introducing exogenous mRNAs encoding antigens into somatic cells and subsequently synthesizing antigens through gene expression systems, mRNA vaccines can effectively induce immune responses. Katalin Karikó and Drew Weissman were awarded the 2023 Nobel Prize in Physiology or Medicine for their great contributions to mRNA vaccine research. Compared with traditional tumor vaccines, mRNA vaccines have several advantages, including rapid preparation, reduced contamination, nonintegrability, and high biodegradability. Tumor-targeted therapy is an innovative treatment modality that enables precise targeting of tumor cells, minimizes damage to normal tissues, is safe at high doses, and demonstrates great efficacy. Currently, targeted therapy has become an important treatment option for malignant tumors. The application of mRNA vaccines in tumor-targeted therapy is expanding, with numerous clinical trials underway. We systematically outline the targeted delivery mechanism of mRNA vaccines and the mechanism by which mRNA vaccines induce anti-tumor immune responses, describe the current research and clinical applications of mRNA vaccines in tumor-targeted therapy, and forecast the future development trends of mRNA vaccine application in tumor-targeted therapy.

pH-Responsive β-Glucans-Complexed mRNA in LNPs as an Oral Vaccine for Enhancing Cancer Immunotherapy

mRNA vaccines for cancer immunotherapy are commonly delivered using lipid nanoparticles (LNPs), which, when administered intravenously, may accumulate in the liver, potentially limiting their therapeutic efficacy. To overcome this challenge, the study introduces an oral mRNA vaccine formulation tailored for efficient uptake by immune cells in the gastrointestinal (GI) tract, known for its high concentration of immune cells, including dendritic cells (DCs). This formulation comprises mRNA complexed with β-glucans (βGlus), a potential adjuvant for vaccines, encapsulated within LNPs (βGlus/mRNA@LNPs). The βGlus/mRNA complexes within the small compartments of LNPs demonstrate a distinctive ability to partially dissociate and reassociate, responding to pH changes, effectively shielding mRNA from degradation in the harsh GI environment. Upon oral administration to tumor-bearing mice, βGlus/mRNA@LNPs are effectively taken up by intestinal DCs and local nonimmune cells, bypassing potential liver accumulation. This initiates antigen-specific immune responses through successful mRNA translation, followed by drainage into the mesenteric lymph nodes to stimulate T cells and trigger specific adaptive immune responses, ultimately enhancing antitumor effects. Importantly, the vaccine demonstrates safety, with no significant inflammatory reactions observed. In conclusion, the potential of oral βGlus/mRNA@LNPs delivery presents a promising avenue in cancer immunotherapy, offering needle-free and user-friendly administration for widespread adoption and self-administration.

Identification of pancreatic adenocarcinoma immune subtype associated with tumor neoantigen from aberrant alternative splicing

Background

Pancreatic adenocarcinoma (PAAD) is referred to as an immunologically "cold" tumor that responds poorly to immunotherapy. A fundamental theory that explains the low immunogenicity of PAAD is the dramatically low tumor mutation burden (TMB) of PAAD tumors, which fails to induce sufficient immune response. Alternative splicing of pre-mRNA, which could alter the proteomic diversity of many cancers, has been reported to be involved in neoantigen production. Therefore, we aim to identify novel PAAD antigens and immune subtypes through systematic bioinformatics research.

Methods

Data for splicing analysis were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq database. Among the available algorithms, we chose CIBERSORT to evaluate the immune cell distribution among PAADs. The TCGA-PAAD expression matrix was used to construct a co-expression network. Single-cell analysis was performed based on the Seurat workflow.

Results

Integrated analysis of aberrantly upregulated genes, alternatively spliced genes, genes associated with nonsense-mediated RNA decay (NMD) factors, antigen presentation and overall survival (OS) in TCGA-PAAD revealed that PLEC is a promising neoantigen for PAAD-targeted therapy. We identified a C2 TCGA-PAAD subtype that had better prognosis and more CD8+ T-cell infiltration. We propose a novel immune subtyping system for PAAD to indicate patient prognosis and opportunities for immunotherapy, such as immune checkpoint (ICP) inhibitors.

Conclusions

In conclusion, the present study used a transcriptome-guided approach to screen neoantigen candidates based on alternative splicing, NMD factors, and antigen-presenting signatures for PAAD. A prognosis model with guidance of immunotherapy will aid in patient selection for appropriate treatment.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Identification of immune-related tumor antigens and immune subtypes in osteosarcoma

Purpose

The development of tumor vaccines has become a hot topic in immunotherapy for osteosarcoma (OS); however, more tumor antigens with stronger immunogenicity need to be identified.

Methods

We downloaded six sets of gene expression profile data from online databases. The overexpressed genes were analyzed, intersected, and used to calculate the immune infiltration abundance in the TARGET OS dataset based on their expression matrix. Potential tumor antigen genes were identified based on whether they exhibited a high correlation with the antigen-presenting cells (APCs). A total of 1330 immune-related genes (IRGs) from the ImmPort website were retrieved based on their expression, and the Consensus Cluster method was used to obtain immune subtypes of the OS samples. Prognosis, immune microenvironment, and sensitivity to drugs were compared among the immune subtypes.

Results

In total, 680 genes were overexpressed in at least two datasets, of which TREM2, TNFRSF12A, and THY1 were positively correlated with different APCs. Based on the expression matrix of 1330 IRGs in TARGET-OS, two immune subtypes, IS1 and IS2, were identified. The prognosis of the IS1 subtype was better than that of IS2, the expression of immune checkpoint (ICP)-related genes was higher in patients with the IS1 subtype, and immune cell infiltration and sensitivity to 16 drugs were generally higher in IS1 subtype patients.

Conclusion

We identified three APC-correlated genes that can be considered to code for potential novel tumor antigens for OS vaccines. Two immune subtypes in patients with OS were identified to implement personalized treatments using mRNA vaccines.

Function of NEK2 in clear cell renal cell carcinoma and its effect on the tumor microenvironment

BACKGROUND

Previous studies have revealed the critical functions of NEK2 in controlling the cell cycle which is linked to poor prognosis in multiple tumor types, but less research has been devoted to clear cell renal cell carcinoma (ccRCC).

METHODS

We downloaded clinical data from the gene expression omnibus (GEO) and TCGA databases together with transcriptional and mutational datasets. Strongly coexpressed genes with NEK2 were extracted from TCGA-KIRC cohort, and were submitted to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional analyses. According to NEK2 levels, the survival status, mutational characteristics, response to immunotherapy and sensitivity to drugs of the patients were studied. The potential correlations between NEK2 levels and immune cell state as well as immune cell infiltration were examined using the GEPIA, TIMER and TISIDB databases. Double immunofluorescence (IF) was performed to identify the NEK2 overexpression and relationship with CD8 in ccRCC.

RESULTS

The NEK2 gene was overexpressed and would enhance the nuclear division and cell cycle activities in ccRCC. ccRCC patients with high NEK2 expression had worse clinical outcomes, higher mutation burden and better therapeutic response. Moreover, NEK2 gene overexpression was positively related to various immune cell marker sets, which was also proved by validation cohort, and more infiltration of various immune cells.

CONCLUSION

ccRCC patients with NEK2 high expression have a poorer prognosis than those with NEK2 low expression, resulting from its function of promoting proliferation, accompanied by increased infiltration of CD8 + T cells and Tregs and T-cell exhaustion and will respond better to proper treatments.

A 15-Inflammation-Related Gene Signature Predicts the Prognosis of Patients With Pancreatic Ductal Adenocarcinoma

Chronic inflammation promotes the development of pancreatic ductal adenocarcinoma (PDAC) and PDAC-related inflammatory tumor microenvironment facilitates tumor growth and metastasis. Thus, we aimed to study the association between inflammatory response and prognosis in patients with PDAC. We conducted the whole transcriptomic sequencing using tissue samples collected from patients diagnosed with PDAC (n = 106) recruited from Shandong Cancer Hospital. We first constructed a prognostic signature using 15 inflammation-related genes in The Cancer Genome Atlas (TCGA) cohort (n = 177) and further validated it in an independent International Cancer Genome Consortium (ICGC) cohort (n = 90) and our in-house cohort. PDAC patients with a higher risk score had poorer overall survival (OS) (P < 0.001; HR, 3.02; 95% CI, 1.94-4.70). The association between the prognostic signature and OS remained significant in the multivariable Cox regression adjusting for age, sex, alcohol exposure, diabetes, and stage (P < 0.001; HR, 2.91; 95% CI, 1.73-4.89). This gene signature also robustly predicted prognosis in the ICGC cohort (P = 0.01; HR, 1.94; 95% CI, 1.14-3.30) and our cohort (P < 0.001; HR, 2.40; 95% CI, 1.45-3.97). Immune subtype C3 (inflammatory) was enriched and CD8+ T cells were higher in patients with a lower risk score (P < 0.05). Furthermore, PDAC patients with higher risk scores were more sensitive to chemotherapy, immunotherapy, and PARP inhibitors (P < 0.05). In sum, we identified a novel gene signature that was associated with inflammatory response for risk stratification, prognosis prediction, and therapy guidance in PDAC patients. Future studies are warranted to validate the clinical utility of the signature.

Alternative Polyadenylation Regulatory Factors Signature for Survival Prediction in Kidney Renal Cell Carcinoma

Background

Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors.

Objective

Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study.

Methods

We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma. We also validated our APA model using independent GEO datasets (GSE29609, GSE76207).

Results

It was found that the expression levels of 5 APA regulatory factors (CPSF1, CPSF2, CSTF2, PABPC1, and PABPC4) were significantly associated with tumor gene mutation burden (TMB) score in renal clear cell carcinoma, and the risk score constructed using the expression level of 5 key APA regulatory factors could be used to predict the outcome of renal clear cell carcinoma. The TMB score is associated with the remodeling of the immune microenvironment.

Conclusions

By identifying key APA regulatory factors in renal cell carcinoma and constructing risk scores for key APA regulatory factors, we showed that key APA regulators affect prognosis of renal clear cell carcinoma patients. In addition, the risk score level is associated with TMB, indicating that APA may affect the efficacy of immunotherapy through immune microenvironment-related genes. This helps us better understand the mRNA processing mechanism of renal clear cell carcinoma.

Identification of Novel Tumor Pyroptosis-Related Antigens and Pyroptosis Subtypes for Developing mRNA Vaccines in Pancreatic Adenocarcinoma

BACKGROUND

As one of the important components of immunotherapies, mRNA vaccines have displayed promising clinical outcomes in solid tumors. Nonetheless, their efficacy remains unclear in pancreatic adenocarcinoma (PAAD). Given the interaction of pyroptosis with anticancer immunity, our study aims to identify pyroptosis-related antigens for mRNA vaccine development and discern eligible candidates for vaccination.

METHODS

Utilizing gene expression data from TCGA and ICGC, we integrated RNA-seq data and compared genetic alterations through cBioPortal. Differential gene expressions were integrated using GEPIA. Relationships between immune cell abundance and tumor antigens were analyzed and visualized via TIMER. WGCNA facilitated the clustering of pyroptosis-related genes, identification of hub genes, and pathway enrichment analyses. Pyroptosis landscape was depicted through graph learning-based dimensional reduction.

RESULTS

Four overexpressed and mutant pyroptosis-related genes associated with poor prognosis were identified as potential antigens for mRNA vaccines in PAAD, including ANO6, PAK2, CHMP2B, and RAB5A. These genes displayed positive associations with antigen-presenting cells. PAAD patients were stratified into three pyroptosis subtypes. Notably, the PS3 subtype, characterized by a lower mutation count and TMB, exhibited "cold" immunological traits and superior survival compared to other subtypes. The pyroptosis landscape exhibited considerable heterogeneity among individuals. Furthermore, the turquoise module emerged as an independent prognostic indicator and patients with high expressions of hub genes might not be suitable candidates for mRNA vaccination.

CONCLUSIONS

In PAAD, ANO6, PAK2, CHMP2B, and RAB5A are prospective pyroptosis-related antigens for mRNA vaccine development, which holds potential benefits for patients classified as PS3 and those with diminished hub gene expressions, providing insights into personalized mRNA vaccine strategies.

Discovering ferroptosis-associated tumor antigens and ferroptosis subtypes in pancreatic adenocarcinoma to facilitate mRNA vaccine development

Pancreatic adenocarcinoma (PAAD) is an aggressive, heterogeneous malignancy. We studied the potential of ferroptosis-related tumor vaccines for PAAD treatment. Ferroptosis-related genes, gene expression profiles, and clinical information were extracted from the FerrDB, UCSC Xena, and International Cancer Genome Consortium databases. Differential expression levels and prognostic indices were calculated, genetic alterations and correlations with immune-infiltrating cells were explored, and consensus clustering analysis was performed to identify ferroptosis subtypes and gene modules. Immune enrichment scores were calculated using gene set enrichment analysis, and gene modules were screened using weighted gene co-expression network analysis. The ferroptosis subtype distribution was visualized using graph learning-based dimensionality reduction analysis of the Monocle package with a Gaussian distribution. We identified four ferroptosis-related tumor antigens, AGPS, KDM5A, NRAS, and OSBPL9, which were associated with pancreatic cancer prognosis and antigen-presenting cell infiltration. We determined three minor ferroptosis subtypes, with different clinical prognosis and tumor immune status. Of the subtypes, FS3 may be more suitable for mRNA therapy. We constructed a PAAD ferroptosis landscape to identify the ferroptosis status of patients and predict their prognosis. Finally, we found that the eigengene of the green module was an independent prognostic factor, with a significantly better prognosis in the high-score group than in the low-score group. In conclusion, we identified four ferroptosis-related genes as targets for mRNA vaccines and three ferroptosis subtypes, providing a theoretical basis for the anti-PAAD mRNA vaccine and defining suitable patients for vaccination.

Redox-Responsive Polymeric Nanoparticle for Nucleic Acid Delivery and Cancer Therapy: Progress, Opportunities, and Challenges

Cancer development and progression of cancer are closely associated with the activation of oncogenes and loss of tumor suppressor genes. Nucleic acid drugs (e.g., siRNA, mRNA, and DNA) are widely used for cancer therapy due to their specific ability to regulate the expression of any cancer-associated genes. However, nucleic acid drugs are negatively charged biomacromolecules that are susceptible to serum nucleases and cannot cross cell membrane. Therefore, specific delivery tools are required to facilitate the intracellular delivery of nucleic acid drugs. In the past few decades, a variety of nanoparticles (NPs) are designed and developed for nucleic acid delivery and cancer therapy. In particular, the polymeric NPs in response to the abnormal redox status in cancer cells have garnered much more attention as their potential in redox-triggered nanostructure dissociation and rapid intracellular release of nucleic acid drugs. In this review, the important genes or signaling pathways regulating the abnormal redox status in cancer cells are briefly introduced and the recent development of redox-responsive NPs for nucleic acid delivery and cancer therapy is systemically summarized. The future development of NPs-mediated nucleic acid delivery and their challenges in clinical translation are also discussed.

Discovery of lung adenocarcinoma tumor antigens and ferroptosis subtypes for developing mRNA vaccines

mRNA vaccines are becoming a feasible alternative for treating cancer. To develop mRNA vaccines against LUAD, potential antigens were identified and LUAD ferroptosis subtypes distinguished for selecting appropriate patients. The genome expression omnibus, cancer genome atlas (TCGA) and FerrDB were used to collect gene expression profiles, clinical information, and the genes involved in ferroptosis, respectively. cBioPortal was used to visualize and compare genetic alterations, GEPIA2 to calculate prognostic factors of the selected antigens, and TIMER to visualize the relationship between potential antigens and tumor immune cell infiltration. Consensus clustering analysis was utilized to identify ferroptosis subtypes and their prognostic value assessed by Log-rank and cox regression tests. The modules of ferroptosis-related gene screening were conducted by weight gene co-expression network analysis. The LUAD ferroptosis landscape was visualized through dimensionality reduction and graph learning. Six tumor antigens had obvious LUAD-mutations, positively correlated with different antigen-presenting cells, and might induce tumor cell ferroptosis. LUAD patients were stratified into three ferroptosis subtypes (FS1, FS2, and FS3) according to diverse molecular, cellular, and clinical characteristics. FS3 showed the highest tumor mutation burden and the most somatic mutations, deemed potential indicators of mRNA vaccine effectiveness. Moreover, different ferroptosis subtypes expressed distinct immune checkpoints and immunogenic cell death modulators. AGPS, NRAS, MTDH, PANX1, NOX4, and PPARD are potentially suitable for mRNA vaccinations against LUAD, specifically in patients with FS3 tumors. This study defines vaccination candidates and establishes a theoretical basis for LUAD mRNA vaccinations.

A novel risk score system based on immune subtypes for identifying optimal mRNA vaccination population in hepatocellular carcinoma

PURPOSE

Although mRNA vaccines have shown certain clinical benefits in multiple malignancies, their therapeutic efficacies against hepatocellular carcinoma (HCC) remains uncertain. This study focused on establishing a novel risk score system based on immune subtypes so as to identify optimal HCC mRNA vaccination population.

METHODS

GEPIA, cBioPortal and TIMER databases were utilized to identify candidate genes for mRNA vaccination in HCC. Subsequently, immune subtypes were constructed based on the candidate genes. According to the differential expressed genes among various immune subtypes, a risk score system was established using machine learning algorithm. Besides, multi-color immunofluorescence of tumor tissues from 72 HCC patients were applied to validate the feasibility and efficiency of the risk score system.

RESULTS

Twelve overexpressed and mutated genes associated with poor survival and APCs infiltration were identified as potential candidate targets for mRNA vaccination. Three immune subtypes (e.g. IS1, IS2 and IS3) with distinct clinicopathological and molecular profiles were constructed according to the 12 candidate genes. Based on the immune subtype, a risk score system was developed, and according to the risk score from low to high, HCC patients were classified into four subgroups on average (e.g. RS1, RS2, RS3 and RS4). RS4 mainly overlapped with IS3, RS1 with IS2, and RS2+RS3 with IS1. ROC analysis also suggested the significant capacity of the risk score to distinguish between the three immune subtypes. Higher risk score exhibited robustly predictive ability for worse survival, which was further independently proved by multi-color immunofluorescence of HCC samples. Notably, RS4 tumors exhibited an increased immunosuppressive phenotype, higher expression of the twelve potential candidate targets and increased genome altered fraction, and therefore might benefit more from vaccination.

CONCLUSIONS

This novel risk score system based on immune subtypes enabled the identification of RS4 tumor that, due to its highly immunosuppressive microenvironment, may benefit from HCC mRNA vaccination.

Exploring the landscape of drug resistance in gastrointestinal cancer immunotherapy: A review

Gastrointestinal (GI) cancers pose a significant challenge due to high prevalence and mortality. While advancements in detection and conventional treatments have been made, prognosis often remains poor, particularly for advanced-stage cancers. Immunotherapy has emerged as a transformative approach, leveraging the body immune system against cancer, including immune checkpoint inhibitors (ICIs), cancer vaccines, and adoptive cell transfer. These modalities have shown promise, achieving sustained responses and improved survival in some patients. However, their efficacy in GI cancers is less pronounced, hindered by drug resistance mechanisms that are either intrinsic or acquired over time. This review examines the latest understanding of immunotherapy in GI cancers, focusing on ICIs, cancer vaccines, and adoptive cell transfer, along with their associated outcomes and limitations. It delves into the mechanisms behind drug resistance, including alterations in immune checkpoints, the immunosuppressive tumor microenvironment, and genetic/epigenetic changes. The role of the gut microbiome is also considered as an emerging factor in resistance. To combat drug resistance, strategies such as enhancing immune response, targeting the tumor microenvironment, and modulating resistance mechanisms are explored. The review underscores the potential of ferroptosis induction as a novel approach. Looking forward, it highlights the need for personalized immunotherapies, understanding the influence of the gut microbiome, and further exploration of ferroptosis in overcoming resistance. While challenges persist, the continuous evolution in GI cancer immunotherapy research promises innovative treatments that could significantly improve patient outcomes.

Tumor immune microenvironment-based therapies in pancreatic ductal adenocarcinoma: time to update the concept

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid tumors. The tumor immune microenvironment (TIME) formed by interactions among cancer cells, immune cells, cancer-associated fibroblasts (CAF), and extracellular matrix (ECM) components drives PDAC in a more immunosuppressive direction: this is a major cause of therapy resistance and poor prognosis. In recent years, research has advanced our understanding of the signaling mechanism by which TIME components interact with the tumor and the evolution of immunophenotyping. Through revolutionary technologies such as single-cell sequencing, we have gone from simply classifying PDACs as "cold" and "hot" to a more comprehensive approach of immunophenotyping that considers all the cells and matrix components. This is key to improving the clinical efficacy of PDAC treatments. In this review, we elaborate on various TIME components in PDAC, the signaling mechanisms underlying their interactions, and the latest research into PDAC immunophenotyping. A deep understanding of these network interactions will contribute to the effective combination of TIME-based therapeutic approaches, such as immune checkpoint inhibitors (ICI), adoptive cell therapy, therapies targeting myeloid cells, CAF reprogramming, and stromal normalization. By selecting the appropriate integrated therapies based on precise immunophenotyping, significant advances in the future treatment of PDAC are possible.

Screening of novel tumor-associated antigens for lung adenocarcinoma mRNA vaccine development based on pyroptosis phenotype genes

This study aimed to identify new pyroptosis-associated tumor antigens for use in mRNA vaccines and the screening of sensitive LUAD populations suitable for vaccination. The association between tumor immune infiltrating cell abundance and potential tumor antigens was investigated and visualized using the analysis modules of gene expression, clinical outcomes, and somatic copy number variation. In addition, the pyroptosis-related genes (PRGs) were clustered, the relative pyroptosis subtypes (PSs) and gene modules were identified, and the prognostic value of the PSs was examined. The expression of key PRGs in two lung adenocarcinoma cell lines was verified by RT-qPCR. Four tumor pyroptosis-associated antigens, CARD8, NAIP, NLRP1, and NLRP3, were screened as potential candidates for LUAD mRNA vaccine development. In the construction of consensus clusters for PRGs, two PSs, PS1 and PS2, were classified, in which patients with PS1 LUAD had a better prognosis. In contrast, patients with PS2 LUAD may have better responsiveness to mRNA vaccine treatment. The key PRGs can be regarded as biomarkers to predict the LUAD prognosis and identify patients suitable for mRNA vaccines. The RT-qPCR results showed that the expression levels of CSMD3, LRP1B, MUC16 and TTN were significantly increased in the two lung adenocarcinoma cell lines, while the expression levels of CARD8, TP53 and ZFHX4 were significantly reduced. The antigens CARD8, NAIP, NLRP1, and NLRP3, which are associated with tumor pyroptosis, could be candidate molecules for LUAD mRNA vaccine development. Patients with PS2 LUAD may be suitable candidates for mRNA vaccine treatment.

Screening of tumor antigens and immunogenic cell death landscapes of prostate adenocarcinoma for exploration of mRNA vaccine

BACKGROUND

In this study, effective antigens of mRNA vaccine were excavated from the perspective of ICD, and ICD subtypes of PRAD were further distinguished to establish an ICD landscape, thereby determining suitable vaccine recipients.

RESEARCH DESIGN AND METHODS

TCGA and MSKCC databases were applied to acquire RNA-seq data and corresponding clinical data of 554 and 131 patients, respectively. GEPIA was employed to measure prognostic indices. Then, a comparison of genetic alterations was performed utilizing cBioPortal, and correlation of identified ICD antigens with immune infiltrating cells was analyzed employing TIMER. Moreover, ICD subtypes were identified by means of consensus cluster, and ICD landscape of PRAD was depicted utilizing graph learning-based dimensional reduction.

RESULTS

In total, 4 PRAD antigens were identified in PRAD, including FUS, LMNB2, RNPC3, and ZNF700, which had association with adverse prognosis and infiltration of APCs. PRAD patients were classified as two ICD subtypes based on their differences in molecular, cellular, and clinical features. Furthermore, ICD modulators and immune checkpoints were also differentially expressed between two ICD subtype tumors. Finally, the ICD landscape of PRAD showed substantial heterogeneity among individual patients.

CONCLUSIONS

In summary, the research may provide a theoretical foundation for developing mRNA vaccine against PRAD as well as determining appropriate vaccine recipients.

Improved prediction of prognosis and therapy response for lung adenocarcinoma after identification of DNA-directed RNA polymerase-associated lncRNAs

BACKGROUND

DNA-directed RNA polymerase (DDRP) related genes and long non-coding RNAs (lncRNAs) play an important role in the development of lung adenocarcinoma (LUAD), the leading cause of cancer-related death worldwide. Therefore, we aimed to construct a DDRP-associated lncRNA model to predict the prognosis of LUAD and to evaluate its sensitivity to immunotherapy and chemotherapy.

METHODS

To construct a predictive signature, we used univariate and multivariate Cox regression analyses, as well as the least absolute shrinkage and selection operator regression analysis. The prognostic model was verified by applying the ROC curve analysis, Kaplan-Meier analysis, GO/KEGG analysis, and a predictive nomogram. Eventually, immunotherapy and drug susceptibility were examined and stemness indices were analyzed.

RESULTS

24 DDRP-associated lncRNAs were found as independent prognosis factors, which may be further developed as potential therapeutic vaccines for LUAD. The area under the ROC curve and the conformance index showed that the constructed model can predict the prognosis of LUAD patients. The predicted incidences of overall survival showed perfect conformance. And there were significant changes in immunological markers between the two risk subgroups in the model. Finally, an analysis of 50% maximum inhibitory concentration between the two risk subgroups showed that the high-risk subgroup was more sensitive to certain chemotherapy drugs.

CONCLUSION

We constructed a model that accurately predicts the outcomes of LUAD based on 24 DDRP-related lncRNAs and provided promising treatment options for the future.

Upregulation of SOX9 promotes the self-renewal and tumorigenicity of cervical cancer through activating the Wnt/β-catenin signaling pathway

Sry-box9 (SOX9) maintains stem cell properties and plays crucial roles in many cancers. However, whether SOX9 is correlated with cervical cancer cell stemness and its detailed mechanism remains obscure. We studied the relationship between SOX9 and prognosis of cervical cancer through public database, and SOX9 was related to poor prognosis of cervical cancer. Elevated SOX9 expression enhanced the self-renewal properties and promotes tumorigenicity in cervical cancer. Overexpression of SOX9 could promote the expression of stem cell-related factors in cervical cancer cells and xenografts. Meanwhile, overexpression of SOX9 could also enhance the expressions of FZD10, β-catenin, and c-Myc in cervical cancer cells and xenografts, while inhibiting the expression of DDK1. The activation of Wnt pathway by chir-99 021 raised the tumor spheroid ability of SOX9 knockdown HeLa cells. In addition, SOX9 could transcriptional inhibit DKK1 and activate FZD10 and MYC by binding to their promoters to affect the Wnt/β-catenin pathway. These results demonstrated SOX9 regulated the self-renewal and tumorigenicity of cervical cancer through Wnt/β-catenin pathway by directly transcriptional activation of FZD10, MYC and transcriptional inhibition of DKK1.

EFHD1 expression is correlated with tumor-infiltrating neutrophils and predicts prognosis in gastric cancer

Background

Gastric cancer (GC) ranks third in terms of mortality worldwide. The tumor microenvironment is critical for the progression of gastric cancer. This study investigated the association between EF-hand domain containing 1 (EFHD1) expression and its clinical significance in the tumor microenvironment (TME) of gastric cancer.

Methods

We used bioinformatic analyses to assess the relevance of EFHD1 mRNA in the TME of gastric carcinoma tissues and its relationship with clinical features. Therefore, we performed multiplex immunohistochemistry analyses to determine the potential role of the EFHD1 protein in the TME of gastric cancer.

Results

EFHD1 expression increased dramatically in gastric cancer tissues compared to levels in non-cancerous tissue samples (t = 6.246, P < 0.001). The EFHD1 protein presentation was associated with invasion depth (χ2 = 19.120, P < 0.001) and TNM stages (χ2 = 14.468, P = 0.002). Notably, EFHD1 protein expression was significantly related to CD66b + neutrophil infiltration of the intratumoral (r = 0.420, P < 0.001) and stromal (r = 0.367, P < 0.001) TME in gastric cancer. Additionally, Cox regression analysis revealed that EFHD1 was an independent prognostic predictor (hazard ratio [HR] = 2.262, P < 0.001) in patients with gastric cancer.

Conclusions

Our study revealed the pattern of EFHD1 overexpression in the TME of patients with gastric cancer and demonstrated its utility as a biomarker for unfavorable clinical outcomes, thereby providing a potential immunotherapy target.

mRNA vaccines in disease prevention and treatment

mRNA vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases, thanks largely although not totally to their extraordinary performance in recent years against the worldwide plague COVID-19. The huge superiority of mRNA vaccines regarding their efficacy, safety, and large-scale manufacture encourages pharmaceutical industries and biotechnology companies to expand their application to a diverse array of diseases, despite the nonnegligible problems in design, fabrication, and mode of administration. This review delves into the technical underpinnings of mRNA vaccines, covering mRNA design, synthesis, delivery, and adjuvant technologies. Moreover, this review presents a systematic retrospective analysis in a logical and well-organized manner, shedding light on representative mRNA vaccines employed in various diseases. The scope extends across infectious diseases, cancers, immunological diseases, tissue damages, and rare diseases, showcasing the versatility and potential of mRNA vaccines in diverse therapeutic areas. Furthermore, this review engages in a prospective discussion regarding the current challenge and potential direction for the advancement and utilization of mRNA vaccines. Overall, this comprehensive review serves as a valuable resource for researchers, clinicians, and industry professionals, providing a comprehensive understanding of the technical aspects, historical context, and future prospects of mRNA vaccines in the fight against various diseases.

Identification of Tumor Antigens and Immune Subtypes of High-grade Serous Ovarian Cancer for mRNA Vaccine Development

High-grade serous ovarian cancer (HGSC) is the most common pathology of ovarian cancer and has aggressive characteristics and poor prognosis. mRNA vaccines are a novel tool for cancer immune treatment and may play an important role in HGSC therapy. Our study aimed to explore tumour antigens for vaccine development and identify potential populations amenable to vaccine treatment. Based on transcription data from The Cancer Genome Atlas (TCGA), we identified four tumour-specific antigens for vaccine production: ARPC1B, ELF3, VSTM2L, and IL27RA. In addition to being associated with HGSC patient prognosis, the expression of these antigens was positively correlated with the abundances of antigen-presenting cells (APCs). Furthermore, we stratified HGSC samples into three immune subtypes (IS1-IS3) with different immune characteristics. A corhort from ICGC (International Cancer Genome Consortium) was used to validate. Patients of IS3 had the best prognosis, while patients of IS1 were most likely to benefit from vaccination. There was substantial heterogeneity in immune signatures and immune-associated molecule expression in HGSC. Finally, weighted gene coexpression network analysis (WGCNA) was employed to cluster immune-related genes and explore potential biomarkers related to vaccination. In conclusion, we identified four potential tumour antigens for mRNA vaccine production for HGSC treatment, and the immune subtype could be an important indicator to select suitable HGSC patients to receive vaccination.

The identification of tumor antigens and immune subtypes based on the development of immunotherapies targeting head and neck squamous cell carcinomas resulting from periodontal disease

Among cancer treatments, immunotherapy is considered a promising strategy. Nonetheless, only a small number of individuals with head and neck squamous cell carcinoma exhibit positive responses to immunotherapy. This study aims to discover possible antigens for head and neck squamous cell carcinoma, create an mRNA vaccine for this type of cancer, investigate the connection between head and neck squamous cell carcinoma and periodontal disease, and determine the immune subtype of cells affected by head and neck squamous cell carcinoma. To ascertain gene expression profiles and clinical data corresponding to them, an examination was carried out on the TCGA database. Antigen-presenting cells were detected using TIMER. Targeting six immune-related genes (CXCL5, ADM, FGF9, AIMP1, STC1, and CDKN2A) in individuals diagnosed with head and neck squamous cell carcinoma has shown promising results in immunotherapy triggered by periodontal disease. These genes have been linked to improved prognosis and increased immune cell infiltration. Additionally, CXCL5, ADM, FGF9, AIMP1, STC1, and CDKN2A exhibited potential as antigens in the creation of an mRNA vaccine. A nomogram model containing ADM expression and tumor stage was constructed for clinical practice. To summarize, ADM shows potential as a candidate biomarker for predicting the prognosis, molecular features, and immune characteristics of head and neck squamous cell carcinoma cells. Our results, obtained through real-time PCR analysis, showed a significant upregulation of ADM in the SCC-25 cell line compared to the NOK-SI cell line. This suggests that ADM might be implicated in the pathogenesis of HNSC, highlighting the potential of ADM as a target in HNSC treatment. However, further research is needed to elucidate the functional role of ADM in HNSC. Our findings provide a basis for the further exploration of the molecular mechanisms underlying HNSC and could help develop novel therapeutic strategies.

SnRNA-seq reveals the heterogeneity of spinal ventral horn and mechanism of motor neuron axon regeneration

Spinal motor neurons, the distinctive neurons of the central nervous system, extend into the peripheral nervous system and have outstanding ability of axon regeneration after injury. Here, we explored the heterogeneity of spinal ventral horn cells after rat sciatic nerve crush via single-nuclei RNA sequencing. Interestingly, regeneration mainly occurred in a Sncg⁺ and Anxa2⁺ motor neuron subtype (MN2) surrounded by a newly emerged microglia subtype (Mg6) after injury. Subsequently, microglia depletion slowed down the regeneration of sciatic nerve. OPCs were also involved into the regeneration process. Knockdown of Cacna2d2 in vitro and systemic blocking of Cacna2d2 in vivo improved the axon growth ability, hinting us the importance of Ca²⁺. Ultimately, we proposed three possible phases of motor neuron axon regeneration: preparation stage, early regeneration stage, and regeneration stage. Taken together, our study provided a resource for deciphering the underlying mechanism of motor neuron axon regeneration in a single cell dimension.

Comprehensive analysis of the immunogenic cell death-related signature for predicting prognosis and immunotherapy efficiency in patients with lung adenocarcinoma

BACKGROUND

Although immunotherapy has been considered as a potent strategy for lung adenocarcinoma (LUAD), only a small part of patients was served as potentially clinical benefiters. Immunogenic cell death (ICD), a type of regulated cell death (RCD), which enable to reshape the tumor immune microenvironment and contribute to the immunotherapy efficiency. Developing a novel ICD-based signature may be a potential strategy to differentiate prognosis of patients with LUAD and predict efficacy of immunotherapy.

METHODS

In this study, 34 ICD-related genes (ICDRGs) were identified and analyzed in LUAD samples from the Cancer Genome Atlas (TCGA). 572 patients with LUAD were divided into two distinct clusters according to ICDRGs expression levels. Patients were subsequently classified into two distinct gene subtypes based on differentially expressed genes (DEGs) analyzed between two ICD-related clusters. We further developed and validated a novel ICD-related score (ICDRS) followed by comprehensive investigation about the landscape of the prognosis, immune-based features, immunotherapautic responses and sensitivity of target drugs in patients with LUAD.

RESULTS

After confirming transcriptomic aberrations and appraising prognostic value of ICDRGs, two ICD-associated subtypes were initially determined by consensus clustering in accordance with differentially expressional levels of ICDRGs. It was shown that patients in the ICD high-subtype possessed the superior clinical prognosis, abundant immune cell infiltration and higher involvement in immune-related signaling compared with the ICD low-subtype. A signature of ICD-related score (ICDRS) was further established and validated, which was served as an independent prognostic indicator for LUAD patients. These comprehensive results revealed that the high-score patients represented better clinical prognosis, higher immune infiltration-related characteristics, stronger expression of immune checkpoints, and better response to immune checkpoint inhibitor therapy and multiple targeted drugs. To further verify our analysis, we selected TLR4 as the representative of ICDRGs and evaluated its expression on the lung normal cells and cancer cells in vitro. Then, relative animal experiments were performed in vivo, with results of that the stimulation of TLR4 suppressed the growth of lung cancer.

CONCLUSIONS

In conclusion, our comprehensive analysis of ICDRGs in LUAD demonstrated their function in serving as a biomarker of predicting prognosis and clinical effects of immunotherapy and targeted drugs, which is meaningful to improve our understanding of ICDRGs and brought inspirations about evaluating prognosis and developing effective therapeutic strategies to patients with LUAD.

Rethinking Antigen Source: Cancer Vaccines Based on Whole Tumor Cell/tissue Lysate or Whole Tumor Cell

Cancer immunotherapies have improved human health, and one among the important technologies for cancer immunotherapy is cancer vaccine. Antigens are the most important components in cancer vaccines. Generally, antigens in cancer vaccines can be divided into two categories: pre-defined antigens and unidentified antigens. Although, cancer vaccines loaded with predefined antigens are commonly used, cancer vaccine loaded with mixed unidentified antigens, especially whole cancer cells or cancer cell lysates, is a very promising approach, and such vaccine can obviate some limitations in cancer vaccines. Their advantages include, but are not limited to, the inclusion of pan-spectra (all or most kinds of) antigens, inducing pan-clones specific T cells, and overcoming the heterogeneity of cancer cells. In this review, the recent advances in cancer vaccines based on whole-tumor antigens, either based on whole cancer cells or whole cancer cell lysates, are summarized. In terms of whole cancer cell lysates, the focus is on applying whole water-soluble cell lysates as antigens. Recently, utilizing the whole cancer cell lysates as antigens in cancer vaccines has become feasible. Considering that pre-determined antigen-based cancer vaccines (mainly peptide-based or mRNA-based) have various limitations, developing cancer vaccines based on whole-tumor antigens is a promising alternative.

The use of RNA-based treatments in the field of cancer immunotherapy

Over the past several decades, mRNA vaccines have evolved from a theoretical concept to a clinical reality. These vaccines offer several advantages over traditional vaccine techniques, including their high potency, rapid development, low-cost manufacturing, and safe administration. However, until recently, concerns over the instability and inefficient distribution of mRNA in vivo have limited their utility. Fortunately, recent technological advancements have mostly resolved these concerns, resulting in the development of numerous mRNA vaccination platforms for infectious diseases and various types of cancer. These platforms have shown promising outcomes in both animal models and humans. This study highlights the potential of mRNA vaccines as a promising alternative approach to conventional vaccine techniques and cancer treatment. This review article aims to provide a thorough and detailed examination of mRNA vaccines, including their mechanisms of action and potential applications in cancer immunotherapy. Additionally, the article will analyze the current state of mRNA vaccine technology and highlight future directions for the development and implementation of this promising vaccine platform as a mainstream therapeutic option. The review will also discuss potential challenges and limitations of mRNA vaccines, such as their stability and in vivo distribution, and suggest ways to overcome these issues. By providing a comprehensive overview and critical analysis of mRNA vaccines, this review aims to contribute to the advancement of this innovative approach to cancer treatment.

Focus on Therapeutic Options for Surgically Resectable Pancreatic Adenocarcinoma Based on Novel Biomarkers

Pancreatic ductal adenocarcinoma remains associated with a poor prognosis, even when diagnosed at an early stage. Consequently, it is imperative to carefully consider the available therapeutic options and tailor them based on clinically relevant biomarkers. In our comprehensive review, we specifically concentrated on the identification of novel predictive and prognostic markers that have the potential to be integrated into multiparametric scoring systems. These scoring systems aim to accurately predict the efficacy of neoadjuvant chemotherapy in surgically resectable pancreatic cancer cases. By identifying robust predictive markers, we can enhance our ability to select patients who are most likely to benefit from neoadjuvant chemotherapy. Furthermore, the identification of prognostic markers can provide valuable insights into the overall disease trajectory and inform treatment decisions. The development of multiparametric scoring systems that incorporate these markers holds great promise for optimizing the selection of patients for neoadjuvant chemotherapy, leading to improved outcomes in resectable pancreatic neoplasia. Continued research efforts are needed to validate and refine these markers and scoring systems, ultimately advancing the field of personalized medicine in pancreatic adenocarcinoma management.

Anoikis-Related Gene Signature for Prognostication of Pancreatic Adenocarcinoma: A Multi-Omics Exploration and Verification Study

Anoikis, a form of apoptosis that occurs due to detachment of cells from the extracellular matrix, has been linked to the development of cancer in several studies. However, its role in pancreatic cancer remains incompletely understood. In this study, we utilized univariate Cox regression and LASSO regression analyses to establish a prognostic model for pancreatic adenocarcinoma based on anoikis-related genes in the TCGA database. Additionally, we performed univariate and multifactorial Cox analyses of protein expression results for TCGA pancreatic adenocarcinoma. We further explored the difference in immune infiltration between the high-risk and low-risk groups and verified the expression of the screened genes using quantitative real-time PCR (qRT-PCR). Our findings indicate that numerous anoikis-related genes are linked to pancreatic adenocarcinoma prognosis. We identified seven prognostic genes (MET, DYNLL2, CDK1, TNFSF10, PIP5K1C, MSLN, GKN1) and validated that their related proteins, such as EGFR and MMP2, have a significant impact on the prognosis of pancreatic adenocarcinoma. Based on clustering analyses of the seven prognostic genes, patients could be classified into three distinct categories, for which somatic mutations varied significantly across the groups. High-risk and low-risk groups also exhibited significant differences in immune infiltration. All genes were found to be highly expressed in pancreatic cancer cell lines (ASPC-1, CFPAC-1) as compared to a normal pancreatic cell line (HPDE). Based on the seven anoikis-related genes, we formulated a robust prognostic model with high predictive accuracy. We also identified the significant impact of KRAS, P53, and CDKN2A mutations on the prognosis of this fatal disease. Therefore, our study highlights the crucial role of anoikis in the development of the pancreatic adenocarcinoma tumor microenvironment.

TPX2 expression as a negative predictor of gemcitabine efficacy in pancreatic cancer

BACKGROUND

Targeting protein for Xenopus kinesin-like protein 2 (TPX2) overexpression in human tumours is associated with increased malignancy. Its effect on gemcitabine resistance in pancreatic ductal adenocarcinoma (PDAC) has not been studied yet.

METHODS

The prognostic impact of TPX2 expression was examined in the tumour tissue of 139 patients with advanced PDAC (aPDAC) treated within the AIO-PK0104 trial or translational trials and of 400 resected PDAC (rPDAC) patients. The findings were validated using RNAseq data of 149 resected PDAC patients.

RESULTS

In the aPDAC cohorts, 13.7% of all samples showed high TPX2 expression, conferring significantly shorter progression-free survival (PFS, HR 5.25, P < 0.001) and overall survival times (OS, HR 4.36, P < 0.001) restricted to gemcitabine-based treated patients (n = 99). In the rPDAC cohort, 14.5% of all samples showed high TPX2 expression, conferring significantly shorter disease-free survival times (DFS, HR 2.56, P < 0.001) and OS times (HR 1.56, P = 0.04) restricted to patients treated with adjuvant gemcitabine. RNAseq data from the validation cohort confirmed the findings.

CONCLUSIONS

High TPX2 expression may serve as a negative predictor of gemcitabine-based palliative and adjuvant chemotherapy in PDAC and could be used to inform clinical therapy decisions.

CLINICAL TRIAL REGISTRY

The clinical trial registry identifier is NCT00440167.

A tumor microenvironment-based prognostic index for osteosarcoma

BACKGROUND

The tumor microenvironment (TME) has a central role in the oncogenesis of osteosarcomas. The composition of the TME is essential for the interaction between tumor and immune cells. The aim of this study was to establish a prognostic index (TMEindex) for osteosarcoma based on the TME, from which estimates about patient survival and individual response to immune checkpoint inhibitor (ICI) therapy can be deduced.

METHODS

Based on osteosarcoma samples from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, the ESTIMATE algorithm was used to estimate ImmuneScore and StromalScore. Combined differentially expressed gene analysis, weighted gene co-expression network analyses, the Least Absolute Shrinkage and Selection Operator regression and stepwise regression to construct the TMEindex. The prognostic role of TMEindex was validated in three independent datasets. The molecular and immune characteristics of TMEindex and the impact on immunotherapy were then comprehensively investigated. The expression of TMEindex genes in different cell types and its effects on osteosarcoma cells were explored by scRNA-Seq analysis and molecular biology experiments.

RESULTS

Fundamental is the expression of MYC, P4HA1, RAMP1 and TAC4. Patients with high TMEindex had worse overall survival, recurrence-free survival, and metastasis-free survival. TMEindex is an independent prognostic factor in osteosarcoma. TMEindex genes were mainly expressed in malignant cells. The knockdown of MYC and P4HA1 significantly inhibited the proliferation, invasion and migration of osteosarcoma cells. A high TME index is related to the MYC, mTOR, and DNA replication-related pathways. In contrast, a low TME index is related to immune-related signaling pathways such as the inflammatory response. The TMEindex was negatively correlated with ImmuneScore, StromalScore, immune cell infiltration, and various immune-related signature scores. Patients with a higher TMEindex had an immune-cold TME and higher invasiveness. Patients with a low TME index were more likely to respond to ICI therapy and achieve clinical benefit. In addition, the TME index correlated with response to 29 oncologic drugs.

CONCLUSIONS

The TMEindex is a promising biomarker to predict the prognosis of patients with osteosarcoma and their response to ICI therapy, and to distinguish the molecular and immune characteristics.

Integrative analysis to screen novel pyroptosis-related LncRNAs for predicting clinical outcome of glioma and validation in tumor tissue

BACKGROUND

Pyroptosis, also known as inflammatory necrosis, is a programmed cell death that manifests itself as a continuous swelling of cells until the cell membrane breaks, leading to the liberation of cellular contents, which triggers an intense inflammatory response. Pyroptosis might be a panacea for a variety of cancers, which include immunotherapy and chemotherapy-insensitive tumors such as glioma. Several findings have observed that long non-coding RNAs (lncRNAs) modulate the bio-behavior of tumor cells by binding to RNA, DNA and protein. Nevertheless, there are few studies reporting the effect of lncRNAs in pyroptosis processes in glioma.

METHODS

The principal goal of this study was to identify pyroptosis-related lncRNAs (PRLs) utilizing bioinformatic algorithm and to apply PCR techniques for validation in human glioma tissues. The second goal was to establish a prognostic model for predicting the overall survival patients with glioma. Predict algorithm was used to construct prognosis model with good diagnostic precision for potential clinical translation.

RESULTS

Noticeably, molecular subtypes categorized by the PRLs were not distinct from any previously published subtypes of glioma. The immune and mutation landscapes were obviously different from previous subtypes of glioma. Analysis of the sensitivity (IC50) of patients to 30 chemotherapeutic agents identified 22 agents as potential therapeutic agents for patients with low riskscores.

CONCLUSIONS

We established an exact prognostic model according to the expression profile of PRLs, which may facilitate the assessment of patient prognosis and treatment patterns and could be further applied to clinical.

Utilizing chemotherapy-induced tumor RNA nanoparticles to improve cancer chemoimmunotherapy

Chemotherapy has become a popular combination strategy to improve the response rate of immunotherapy since certain chemotherapeutic drugs kill tumor cells by an immunogenic cell death (ICD) pathway, which activates antitumor immune responses. Unfortunately, the synergistic effect of chemoimmunotherapy can be impaired due to the toxicities of chemotherapeutic agent-induced lymphatic depletion and immunosuppression. In this study, we present an approach to improve immunotherapy by using tumor RNA nanoparticles (RNA-NPs) where RNA is directly extracted from chemotherapy-treated cancer cells and then condensed by protamine via electrostatic interactions to form complexes. Such RNA-NPs can be effectively taken up by dendritic cells (DCs) in the draining lymph nodes after subcutaneous injection. Compared with noninduced tumor RNA nanoparticles (N-RNA-NPs), chemotherapy-induced tumor RNA nanoparticles (C-RNA-NPs) can significantly promote DC maturation and stimulate a stronger immune response against established CT-26 colon carcinoma. Besides, C-RNA-NPs can improve the efficacy of immune checkpoint blockade (ICB) therapy by facilitating the infiltration of intratumoral T cells and increasing the ratio of CD8⁺ T cells to regulatory T cells (Tregs). More importantly, the synergistic effect of chemoimmunotherapy is also enhanced by treatment with C-RNA-NPs. STATEMENT OF SIGNIFICANCE: Although immune checkpoint blockade therapy has been demonstrated to be effective in some advanced cancers, the low response rate has significantly limited its clinical application. To address this issue, a new strategy for improving cancer immunotherapy using chemotherapy-induced tumor RNA nanoparticles (C-RNA-NPs) is developed in this work. The proposed C-RNA-NPs could be captured by dendritic cells, which were then stimulated to the maturation status to initiate an anticancer immune response. Furthermore, the response rate to immunotherapy was significantly increased by promoting intratumoral T-cell infiltration and elevating the intratumoral ratio of CD8⁺ T cells to regulatory T cells after treatment with C-RNA-NPs. Therefore, C-RNA-NPs have the potential to improve cancer immunotherapy.

Anterior gradient-2 regulates cell communication by coordinating cytokine-chemokine signaling and immune infiltration in breast cancer

Anterior gradient-2 (AGR2) is crucial to breast cancer progression. However, its role in the tumor immune microenvironment remains unclear. RNA sequencing expression profiles and associated clinical information were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. The AGR2 expression patterns were verified using clinical samples of breast cancer. Based on single-cell transcriptomic data, AGR2 expression patterns were identified and cell communication analysis was carried out. Furthermore, the roles of AGR2 in breast tumor progression were explored by a series of functional experiments. We found that DNA methylation was an important mechanism for regulating the expression patterns of AGR2. Patients with AGR2 low expression displayed an immune "hot" and immunosuppressive phenotype characterized by high abundance of tumor immune cell infiltration and increased enrichment scores for transforming growth factor-β (TGF-β) and epithelial-mesenchymal transition pathways, whereas patients with AGR2 high expression showed an opposite immunologic feature with a lack of immune cell infiltration, suggestive of an immune "cold" and desert phenotype. Moreover, single-cell analysis further revealed that AGR2 in malignant cells alters cell-cell interactions by coordinating cytokine-chemokine signaling and immune infiltration. Notably, two immunotherapy cohorts revealed that AGR2-coexpressed genes could serve as prognostic indicators of patient survival. In conclusion, AGR2 could promote breast cancer progression by affecting the tumor immune microenvironment. Patients with AGR2 low expression could be suitable for combination treatment with immune checkpoint inhibitor agents and TGF-β blockers. Therefore, this study provides a theoretical foundation for developing a strategy for personalized immunotherapy to patients with breast cancer.

Identification of Five Tumor Antigens for Development and Two Immune Subtypes for Personalized Medicine of mRNA Vaccines in Papillary Renal Cell Carcinoma

Increasing evidence has revealed the promise of mRNA-type cancer vaccines as a new direction for cancer immune treatment in several solid tumors, however, its application in papillary renal cell carcinoma (PRCC) remains unclear. The purpose of this study was to identify potential tumor antigens and robust immune subtypes for the development and appropriate use of anti-PRCC mRNA vaccines, respectively. Raw sequencing data and clinical information of PRCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The cBioPortal was utilized for the visualization and comparison of genetic alterations. The TIMER was used to assess the correlation between preliminary tumor antigens and the abundance of infiltrated antigen presenting cells (APCs). Immune subtypes were determined by the consensus clustering algorithm, and clinical and molecular discrepancies were further explored for a deeper understanding of immune subtypes. Five tumor antigens, including ALOX15B, HS3ST2, PIGR, ZMYND15 and LIMK1, were identified for PRCC, which were correlated with patients' prognoses and infiltration levels of APCs. Two immune subtypes (IS1 and IS2) were disclosed with obviously distinct clinical and molecular characteristics. Compared with IS2, IS1 exhibited a significantly immune-suppressive phenotype, which largely weakened the efficacy of the mRNA vaccine. Overall, our study provides some insights for the design of anti-PRCC mRNA vaccines and, more importantly, the selection of suitable patients to be vaccinated.

LRP2 and DOCK8 Are Potential Antigens for mRNA Vaccine Development in Immunologically 'Cold' KIRC Tumours

The administration of mRNA-based tumour vaccines is considered a promising strategy in tumour immunotherapy, although its application against kidney renal clear cell carcinoma (KIRC) is still at its infancy stage. The purpose of this study was to identify potential antigens and to further select suitable patients for vaccination. Gene expression data and clinical information were retrieved from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. GEPIA2 was used to evaluate the prognostic value of selected antigens. The relationship of antigens presenting cell infiltration with antigen expression was evaluated by TIMER, and immune subtypes were determined using unsupervised cluster analysis. Tumour antigens LRP2 and DOCK8, which are associated with prognosis and tumour-infiltrating antigen-presenting cells, were identified in KIRC. A total of six immune subtypes were identified, and patients with immune subtype 1-4 (IS1-4) tumours had an immune 'cold' phenotype, a higher tumour mutation burden, and poor survival. Moreover, these immune subtypes showed significant differences in the expression of immune checkpoint and immunogenic cell death modulators. Finally, the immune landscape of KIRC revealed the immune-related cell components in individual patients. This study suggests that LRP2 and DOCK8 are potential KIRC antigens in the development of mRNA vaccines, and patients with immune subtypes IS1-4 are suitable for vaccination.

Immunosuppression, immune escape, and immunotherapy in pancreatic cancer: focused on the tumor microenvironment

Pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, is characterized by poor treatment response and low survival time. The current clinical treatment for advanced PDAC is still not effective. In recent years, the research and application of immunotherapy have developed rapidly and achieved substantial results in many malignant tumors. However, the translational application in PDAC is still far from satisfactory and needs to be developed urgently. To carry out the study of immunotherapy, it is necessary to fully decipher the immune characteristics of PDAC. This review summarizes the recent progress of the tumor microenvironment (TME) of PDAC and highlights its link with immunotherapy. We describe the molecular cues and corresponding intervention methods, collate several promising targets and progress worthy of further study, and put forward the importance of integrated immunotherapy to provide ideas for future research of TME and immunotherapy of PDAC.

LINC00669 promotes lung adenocarcinoma growth by stimulating the Wnt/β-catenin signaling pathway

Lung cancer poses severe threats to human health. It is indispensable to discover more druggable molecular targets. We identified a novel dysregulated long non-coding RNA (lncRNA), LINC00669, in lung adenocarcinoma (LUAD) by analyzing the TCGA and GEO databases. Pan-cancer analysis indicated significantly upregulated LINC00669 across 33 cancer types. GSEA revealed a tight association of LINC00669 with the cell cycle. We next attempted to improve the prognostic accuracy of this lncRNA by establishing a risk signature in reliance on cell cycle genes associated with LINC00669. The resulting risk score combined with LINC00669 and stage showed an AUC of 0.746. The risk score significantly stratified LUAD patients into low- and high-risk subgroups, independently predicting prognosis. Its performance was verified by nomogram (C-index = 0.736) and decision curve analysis. Gene set variation analysis disclosed the two groups' molecular characteristics. We also evaluated the tumor immune microenvironment by dissecting 28 infiltrated immune cells, 47 immune checkpoint gene expressions, and immunophenoscore within the two subgroups. Furthermore, the risk signature could predict sensitivity to immune checkpoint inhibitors and other anticancer therapies. Eventually, in vitro and in vivo experiments were conducted to validate LINC00669's function using qRT-PCR, CCK8, flow cytometry, western blot, and immunofluorescence staining. The gain- and loss-of-function study substantiated LINC00669's oncogenic effects, which stimulated non-small cell lung cancer cell proliferation but reduced apoptosis via activating the Wnt/β-catenin pathway. Its oncogenic potentials were validated in the xenograft mouse model. Overall, we identified a novel oncogenic large intergenic non-coding RNA (lincRNA), LINC00669. The resulting signature may facilitate predicting prognosis and therapy responses in LUAD.

Dissection of tumor antigens and immune landscape in clear cell renal cell carcinoma: Preconditions for development and precision medicine of mRNA vaccine

Accumulating evidence reveals that mRNA-type cancer vaccines could be exploited as cancer immunotherapies in various solid tumors. However, the use of mRNA-type cancer vaccines in clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to identify potential tumor antigens for the development of an anti-ccRCC mRNA vaccine. In addition, this study aimed to determine immune subtypes of ccRCC to guide the selection of patients to receive the vaccine. Raw sequencing and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Further, the cBioPortal website was used to visualize and compare genetic alterations. GEPIA2 was employed to evaluate the prognostic value of preliminary tumor antigens. Moreover, the TIMER web server was used to evaluate correlations between the expression of specific antigens and the abundance of infiltrated antigen-presenting cells (APCs). Single-cell RNA sequencing data of ccRCC was used to explore the expression of potential tumor antigens at single-cell resolution. The immune subtypes of patients were analyzed by the consensus clustering algorithm. Furthermore, the clinical and molecular discrepancies were further explored for a deep understanding of the immune subtypes. Weighted gene co-expression network analysis (WGCNA) was used to cluster the genes according to the immune subtypes. Finally, the sensitivity of drugs commonly used in ccRCC with diverse immune subtypes was investigated. The results revealed that the tumor antigen, LRP2, was associated with a good prognosis and enhanced the infiltration of APCs. ccRCC could be divided into two immune subtypes (IS1 and IS2) with distinct clinical and molecular characteristics. The IS1 group showed a poorer overall survival with an immune-suppressive phenotype than the IS2 group. Additionally, a large spectrum of differences in the expression of immune checkpoints and immunogenic cell death modulators were observed between the two subtypes. Lastly, the genes correlated with the immune subtypes were involved in multiple immune-related processes. Therefore, LRP2 is a potential tumor antigen that could be used to develop an mRNA-type cancer vaccine in ccRCC. Furthermore, patients in the IS2 group were more suitable for vaccination than those in the IS1 group.

Identification of tumor antigens and immune landscapes for bladder urothelial carcinoma mRNA vaccine

Background

Bladder urothelial carcinoma (BLCA) is associated with high mortality and recurrence. Although mRNA-based vaccines are promising treatment strategies for combating multiple solid cancers, their efficacy against BLCA remains unclear. We aimed to identify potential effective antigens of BLCA for the development of mRNA-based vaccines and screen for immune clusters to select appropriate candidates for vaccination.

Methods

Gene expression microarray data and clinical information were retrieved from The Cancer Genome Atlas and GSE32894, respectively. The mRNA splicing patterns were obtained from the SpliceSeq portal. The cBioPortal for Cancer Genomics was used to visualize genetic alteration profiles. Furthermore, nonsense-mediated mRNA decay (NMD) analysis, correlation analysis, consensus clustering analysis, immune cell infiltration analysis, and weighted co-expression network analysis were conducted.

Results

Six upregulated and mutated tumor antigens related to NMD, and infiltration of APCs were identified in patients with BLCA, including HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2. The patients were subdivided into two immune clusters (IC1 and IC2) with distinct clinical, cellular and molecular features. Patients in IC1 represented immunologically 'hot' phenotypes, whereas those in IC2 represented immunologically 'cold' phenotypes. Moreover, the survival rate was better in IC2 than in IC1, and the immune landscape of BLCA indicated significant inter-patient heterogeneity. Finally, CALD1, TGFB3, and ANXA6 were identified as key genes of BLCA through WGCNA analysis, and their mRNA expression levels were measured using qRT-PCR.

Conclusion

HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2 were identified as potential antigens for developing mRNA-based vaccines against BLCA, and patients in IC2 might benefit more from vaccination.

Screening of Tumor Antigens and Construction of Immune Subtypes for mRNA Vaccine Development in Head and Neck Squamous Cell Carcinoma

BACKGROUND

A growing number of clinical studies have confirmed that mRNA vaccines are effective in the treatment of malignant tumors; however, their efficacy in head and neck squamous cell carcinoma (HNSCC) has not been determined. This study aimed to identify the potential antigens of HNSCC for mRNA vaccine development and further distinguish the immune subtypes of HNSCC to select suitable patients for vaccination.

METHODS

We obtained gene expression profiles and corresponding clinical information of HNSCC from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We visualized the genetic alterations of potential antitumor antigens using cBioPortal and obtained the immune gene set from Immport. The correlation between the expression of the identified antigens and the infiltration of antigen-presenting cells was visualized by Tumor Immune Estimation Resource (TIMER). We evaluated the potential biological functions of different samples and described the immune landscape.

RESULTS

Increased expression of three potential tumor antigens, CCR4, TMCO1, and SPACA4, associated with superior prognoses and infiltration of antigen-presenting cells, was identified in HNSCC. Three immune subtypes (C1-C3) with different molecular, cellular, and clinical characteristics were defined. Patients with C3 tumor had a better prognosis, representing an immune "cold" phenotype, which may be more suitable for mRNA vaccination. In addition, different immune characteristics were observed among the three immune subtypes, including markers of immune cells, mutation burden, expression of immune checkpoints, and immune modulators. Finally, the immune landscape of HNSCC showed a high degree of heterogeneity between individual patients.

CONCLUSION

CCR4, TMCO1, and SPACA4 may be potential antigens for developing mRNA vaccines against HNSCC, especially for patients with C3 tumor. This study could provide a theoretical basis for the development of an mRNA vaccine against HNSCC.

Prognostic and Immunological Implications of FAM72A in Pan-Cancer and Functional Validations

The family with sequence similarity 72 Member A (FAM72A) is overexpressed in several types of cancer. However, its contributions to tumorigenesis remain largely unknown. Based on The Cancer Genome Atlas (TCGA) database, FAM72A was upregulated across 33 types of cancer. Accordingly, high levels of FAM72A predicted inferior outcomes in half of the cancer types using survival analysis (the Kaplan-Meier curve and univariate Cox regression model). Receiver operating characteristic (ROC) analysis demonstrated that FAM72A showed high accuracy in distinguishing cancerous tissues from normal ones. FAM72A was correlated with immune and stromal scores and immune cell infiltrations in various tumors. Moreover, FAM72A was also associated with tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint genes. Immunophenoscore (IPS) further validated that the FAM72A^low tumor showed high immunogenicity and tended to respond to anti-PD1/PDL1/PDL2, anti-CTLA4 treatment, and combined immunotherapies. We also investigated the functional role of FAM72A in lung adenocarcinoma (LUAD). In vitro studies demonstrated that the ectopic expression of FAM72A accelerated the proliferation and migration of NSCLC cells, whereas silencing FAM72A showed the opposite effects on them. In short, FAM72A had prognostic potential and correlated with tumor immunogenicity in various tumors. Functional analysis indicated that FAM72A is an oncogene in LUAD.

Therapy sculpts the complex interplay between cancer and the immune system during tumour evolution

Cancer development is an evolutionary process. A key selection pressure is exerted by therapy, one of the few players in cancer evolution that can be controlled. As such, an understanding of how treatment acts to sculpt the tumour and its microenvironment and how this influences a tumour's subsequent evolutionary trajectory is critical. In this review, we examine cancer evolution and intra-tumour heterogeneity in the context of therapy. We focus on how radiotherapy, chemotherapy and immunotherapy shape both tumour development and the environment in which tumours evolve and how resistance can develop or be selected for during treatment.

Identification and Validation of Novel Immunogenic Cell Death- and DNA Damage Response-Related Molecular Patterns Correlated with Immune Status and Prognosis in Hepatocellular Carcinoma

Immunogenic cell death (ICD) and DNA damage response (DDR) are involved in cancer progression and prognosis. Currently, chemotherapy is the first-line treatment for intermediate or advanced hepatocellular carcinoma (HCC), which is mostly based on platinum and anthracyclines that induce DNA damage and ICD. With the treatment of HCC with immune checkpoint inhibitors (ICIs), it is important to understand the molecular characteristics and prognostic values of ICD and DDR-related genes (IDRGs). We aimed to explore the characteristics of ICD and DDR-related molecular patterns, immune status, and the association of immunotherapy and prognosis with IDRGs in HCC. We identified IDRGs in HCC and evaluated their differential expression, biological behaviors, molecular characteristics, immune cell infiltration, and prognostic value. Prognostic IDRGs and subtypes were identified and validated. FFAR3, DDX1, POLR3G, FANCL, ADA, PI3KR1, DHX58, TPT1, MGMT, SLAMF6, and EIF2AK4 were determined as risk factors for HCC, and the biological experiments indicated that high FANCL expression is harmful to the treatment and prognosis. HCC was classified into high- and low-risk groups based on the median values of the risk factors to construct a predictive nomogram. These findings provide novel insights into the treatment and prognosis of HCC and provide a new research direction for HCC.

Identification of GINS1 as a therapeutic target in the cancer patients infected with COVID-19: a bioinformatics and system biology approach

BACKGROUND

Coronavirus disease 2019 (COVID-19) caused a series of biological changes in cancer patients which have rendered the original treatment ineffective and increased the difficulty of clinical treatment. However, the clinical treatment for cancer patients infected with COVID-19 is currently unavailable. Since bioinformatics is an effective method to understand undiscovered biological functions, pharmacological targets, and therapeutic mechanisms. The aim of this study was to investigate the influence of COVID-19 infection in cancer patients and to search the potential treatments.

METHODS

Firstly, we obtained the COVID-19-associated genes from seven databases and analyzed the cancer pathogenic genes from Gene Expression Omnibus (GEO) databases, respectively. The Cancer/COVID-19-associated genes were shown by Venn analyses. Moreover, we demonstrated the signaling pathways and biological functions of pathogenic genes in Cancer/COVID-19.

RESULTS

We identified that Go-Ichi-Ni-San complex subunit 1 (GINS1) is the potential therapeutic target in Cancer/COVID-19 by GEPIA. The high expression of GINS1 was not only promoting the development of cancers but also affecting their prognosis. Furthermore, eight potential compounds of Cancer/COVID-19 were identified from CMap and molecular docking analysis.

CONCLUSION

We revealed the GINS1 is a potential therapeutic target in cancer patients infected with COVID-19 for the first time, as COVID-19 will be a severe and prolonged pandemic. However, the findings have not been verified actually cancer patients infected with COVID-19, and further studies are needed to demonstrate the functions of GINS1 and the clinical treatment of the compounds.

PVR-A Prognostic Biomarker Correlated with Immune Cell Infiltration in Hepatocellular Carcinoma

The poliovirus receptor (PVR) is a member of the immunoglobulin superfamily (Ig SF) and is essential for the promotion of cancer cell proliferation and invasion. However, the correlation between PVR expression and prognosis as well as immune infiltration in hepatocellular carcinoma (HCC) remains unclear. The expression level of PVR was quantified using the Tumor and Tumor Immunity Evaluation Resource (TIMER) and Sangerbox. The Gene Expression Omnibus (GEO) database was used to validate the PVR expression. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of using PVR as a differentiating factor according to the area under curve (AUC) score. A PVR binding protein network was built using the STRING tool. An enrichment analysis using the R package clusterProfiler was used to explore the potential function of PVR. Immune infiltration analysis was calculated with ESTIMATE algorithms. We also assessed the correlation between PVR expression and immune infiltration by the single-sample Gene Set Enrichment Analysis (ssGSEA) method from the R package GSVA and TIMER database. The results showed that PVR was commonly overexpressed in multiple types of tumors including HCC. The data of GSE64041 confirmed the same result. The ROC curve suggested that PVR could be a potential diagnostic biomarker. Additionally, high mRNA expression of PVR in HCC was significantly correlated with poor overall survival (OS) and relapse free survival (RFS). Results also indicated correlations between PVR mRNA expression with the level of infiltration immune cells including B cells, CD8+ T cells, cytotoxic cells, DCs, CD56dim NK cells, pDCs, and Th2 cells. Furthermore, the PVR level was significantly correlated with immune markers for immunosuppressive cells in HCC. In conclusion, PVR might be an important regulator of tumor immune cell infiltration and a valuable prognostic biomarker in HCC. However, additional work is needed to fully elucidate the underlying mechanisms.

Establishment and Systematic Evaluation of Gastric Cancer Classification Model Based on Pyroptosis

Background: Gastric cancer (GC) is considered the fifth most prevalent type of cancer and the third leading cause of cancer deaths worldwide. This in-depth investigation was performed to generate fresh concepts for the clinical classification, diagnosis, and prognostic evaluation of GC. Methods: The data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Unsupervised cluster analysis was used to divide up the GC patients using pyroptosis-related differentially expressed genes (DEGs), which were discovered to be significantly linked with GC prognosis. The therapeutic importance of pyroptosis in GC patients was discovered using PCA analysis of genes associated with pyroptosis. The models were then carefully scrutinized. Results: Three hub genes, ELANE, IL6, and TIRAP, exhibit significant predictive importance among the 15 pyroptosis-related genes. Unsupervised clustering analysis revealed that the DEGs were enriched in the pathway of cytokine-cytokine receptor interactions, and Clusters 1 and 2 had statistically distinct prognoses. PCA analysis revealed significant differences in the area under the curve, immunological checkpoints, immunogenic cell death, and prognostic value between the high- and low-risk groups. Conclusions: These two GC classification models, based on pyroptosis, have significant clinical value for patients with GC.