Cytolytic activity score as a biomarker for antitumor immunity and clinical outcome in patients with gastric cancer

A Deep Learning-Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study developed two convolutional neural network models to detect TILs and to determine their spatial location in whole slide images, and established a spatial assessment pipeline to objectively quantify intraepithelial and stromal TILs in patients with high-grade serous ovarian carcinoma. The predictions of the established models showed a significant positive correlation with the number of CD8+ T cells and immune gene expressions. Patients with a higher density of intraepithelial TILs had a significantly prolonged overall survival and progression-free survival in multiple cohorts. On the basis of the density of intraepithelial and stromal TILs, patients were classified into three immunophenotypes: immune inflamed, excluded, and desert. The immune-desert subgroup showed the worst prognosis. Gene expression analysis showed that the immune-desert subgroup had lower immune cytolytic activity and T-cell-inflamed gene-expression profile scores, whereas the immune-excluded subgroup had higher expression of interferon-γ and programmed death 1 receptor signaling pathway. The established evaluation method provided detailed and comprehensive quantification of intraepithelial and stromal TILs throughout hematoxylin and eosin-stained slides. It has potential for clinical application for personalized treatment of patients with ovarian cancer.

Emerging measurements for tumor-infiltrating lymphocytes in breast cancer

Tumor-infiltrating lymphocytes are a general term for lymphocytes or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating lymphocytes to be robust prognostic and predictive biomarkers in breast cancer. Recently, immune checkpoint inhibitors, which directly target tumor-infiltrating lymphocytes, have become part of standard of care treatment for triple-negative breast cancer. Surprisingly, tumor-infiltrating lymphocytes quantified by conventional methods do not predict response to immune checkpoint inhibitors, which highlights the heterogeneity of tumor-infiltrating lymphocytes and the complexity of the immune network in the tumor microenvironment. Tumor-infiltrating lymphocytes are composed of diverse immune cell populations, including cytotoxic CD8-positive T lymphocytes, B cells and myeloid cells. Traditionally, tumor-infiltrating lymphocytes in tumor stroma have been evaluated by histology. However, the standardization of this approach is limited, necessitating the use of various novel technologies to elucidate the heterogeneity in the tumor microenvironment. This review outlines the evaluation methods for tumor-infiltrating lymphocytes from conventional pathological approaches that evaluate intratumoral and stromal tumor-infiltrating lymphocytes such as immunohistochemistry, to the more recent advancements in computer tissue imaging using artificial intelligence, flow cytometry sorting and multi-omics analyses using high-throughput assays to estimate tumor-infiltrating lymphocytes from bulk tumor using immune signatures or deconvolution tools. We also discuss higher resolution technologies that enable the analysis of tumor-infiltrating lymphocytes heterogeneity such as single-cell analysis and spatial transcriptomics. As we approach the era of personalized medicine, it is important for clinicians to understand these technologies.

The tumor immune composition of mismatch repair deficient and Epstein-Barr virus-positive gastric cancer: A systematic review

BACKGROUND

Gastric cancer (GC), known for its unfavorable prognosis, has been classified in four distinct molecular subtypes. These subtypes not only exhibit differences in their genome and transcriptome but also in the composition of their tumor immune microenvironment. The microsatellite instable (MSI) and Epstein-Barr virus (EBV) positive GC subtypes show clear clinical benefits from immune checkpoint blockade, likely due to a neoantigen-driven and virus-driven antitumor immune response and high expression of immune checkpoint molecule PD-L1. However, even within these subtypes response to checkpoint inhibition is variable, which is potentially related to heterogeneity in the tumor immune microenvironment (TIME) and expression of co-inhibitory molecules. We conducted a systematic review to outline the current knowledge about the immunological features on the TIME of MSI and EBV + GCs.

METHODS

A systematic search was performed in PubMed, EMBASE and Cochrane Library. All articles from the year 1990 and onwards addressing immune features of gastric adenocarcinoma were reviewed and included based on predefined in- and exclusion criteria.

RESULTS

In total 5962 records were screened, of which 139 were included that reported immunological data on molecular GC subtypes. MSI and EBV + GCs were reported to have a more inflamed TIME compared to non-MSI and EBV- GC subtypes. Compared to microsatellite stable (MSS) tumors, MSI tumors were characterized by higher numbers of CD8 + and FoxP3 + T cells, and tumor infiltrating pro- and anti-inflammatory macrophages. HLA-deficiency was most common in MSI tumors compared to other molecular GC subtypes and associated with lower T and B cell infiltrates compared to HLA-proficient tumors. EBV + was associated with a high number of CD8 + T cells, Tregs, NK cells and macrophages. Expression of PD-L1, CTLA-4, Granzyme A and B, Perforin and interferon-gamma was enriched in EBV + tumors. Overall, MSI tumors harbored a more heterogeneous TIME in terms of immune cell composition and immune checkpoints compared to the EBV + tumors.

DISCUSSION AND CONCLUSION

MSI and EBV + GCs are highly Handbook for Conducting a Literature-Based Health Assessment Using OHAT Approach for Systematic Review and Evidence Integration.; 2019pro-inflammatory immune cell populations. Although studies on the direct comparison of EBV + and MSI tumors are limited, EBV + tumors show less intra-subgroup heterogeneity compared to MSI tumors. More studies are needed to identify how Intra-subgroup heterogeneity impacts response to immunotherapy efficacy.

Immune Cytolytic Activity and Strategies for Therapeutic Treatment

Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.

Individualized detection of TMPRSS2-ERG fusion status in prostate cancer: a rank-based qualitative transcriptome signature

BACKGROUND

TMPRSS2-ERG (T2E) fusion is highly related to aggressive clinical features in prostate cancer (PC), which guides individual therapy. However, current fusion prediction tools lacked enough accuracy and biomarkers were unable to be applied to individuals across different platforms due to their quantitative nature. This study aims to identify a transcriptome signature to detect the T2E fusion status of PC at the individual level.

METHODS

Based on 272 high-throughput mRNA expression profiles from the Sboner dataset, we developed a rank-based algorithm to identify a qualitative signature to detect T2E fusion in PC. The signature was validated in 1223 samples from three external datasets (Setlur, Clarissa, and TCGA).

RESULTS

A signature, composed of five mRNAs coupled to ERG (five ERG-mRNA pairs, 5-ERG-mRPs), was developed to distinguish T2E fusion status in PC. 5-ERG-mRPs reached 84.56% accuracy in Sboner dataset, which was verified in Setlur dataset (n = 455, accuracy = 82.20%) and Clarissa dataset (n = 118, accuracy = 81.36%). Besides, for 495 samples from TCGA, two subtypes classified by 5-ERG-mRPs showed a higher level of significance in various T2E fusion features than subtypes obtained through current fusion prediction tools, such as STAR-Fusion.

CONCLUSIONS

Overall, 5-ERG-mRPs can robustly detect T2E fusion in PC at the individual level, which can be used on any gene measurement platform without specific normalization procedures. Hence, 5-ERG-mRPs may serve as an auxiliary tool for PC patient management.

Construction of a 5-gene prognostic signature based on oxidative stress related genes for predicting prognosis in osteosarcoma

BACKGROUND

The understanding of the complex biological scenario of osteosarcoma will open the way to identifying new strategies for its treatment. Oxidative stress is a cancer-related biological scenario. At present, it is not clear the oxidative stress genes in affecting the prognosis and progression of osteosarcoma, the underlying mechanism as well as their impact on the classification of osteosarcoma subtypes.

METHODS

We selected samples and sequencing data from TARGET data set and GSE21257 data set, and downloaded oxidative stress related-genes (OSRGs) from MsigDB. Univariate Cox analysis of OSRG was conducted using TARGET data, and the prognostic OSRG was screened to conduct unsupervised clustering analysis to identify the molecular subtypes of osteosarcoma. Through least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression analysis of differentially expressed genes (DEGs) between subgroups, a risk assessment system for osteosarcoma was developed.

RESULTS

45 prognosis-related OSRGs genes were acquired, and two molecular subtypes of osteosarcoma were clustered. C2 cluster displayed prolonged overall survival (OS) accompanied with high degree of immune infiltration and enriched immune pathways. While cell cycle related pathways were enriched in C2 cluster. Based on DEGs between subgroups and Lasso analysis, 5 hub genes (ZYX, GJA5, GAL, GRAMD1B, and CKMT2) were screened to establish a robust prognostic risk model independent of clinicopathological features. High-risk group had more patients with cancer metastasis and death as well as C1 subtype with poor prognosis. Low-risk group exhibited favorable OS and high immune infiltration status. Additionally, the risk assessment system was optimized by building decision tree and nomogram.

CONCLUSIONS

This study defined two molecular subtypes of osteosarcoma with different prognosis and tumor immune microenvironment status based on the expression of OSRGs, and provided a new risk assessment system for the prognosis of osteosarcoma.

Mechanisms and biomarkers of immune-related adverse events in gastric cancer

Immune-checkpoint inhibitors (ICIs), different from traditional cancer treatment models, have shown unprecedented anti-tumor effects in the past decade, greatly improving the prognosis of many malignant tumors in clinical practice. At present, the most widely used ICIs in clinical immunotherapy for a variety of solid tumors are monoclonal antibodies against cytotoxic T lymphocyte antigen-4 (CTLA-4), programmed cell death protein 1 (PD-1) and their ligand PD-L1. However, tumor patients may induce immune-related adverse events (irAEs) while performing immunotherapy, and irAE is an obstacle to the prospect of ICI treatment. IrAE is a non-specific disease caused by immune system imbalance, which can occur in many tissues and organs. For example, skin, gastrointestinal tract, endocrine system and lung. Although the exact mechanism is not completely clear, related studies have shown that irAE may develop through many ways. Such as excessive activation of autoreactive T cells, excessive release of inflammatory cytokines, elevated levels of autoantibodies, and common antigens between tumors and normal tissues. Considering that the occurrence of severe IrAE not only causes irreversible damage to the patient's body, but also terminates immunotherapy due to immune intolerance. Therefore, accurate identification and screening of sensitive markers of irAE are the main beneficiaries of ICI treatment. Additionally, irAEs usually require specific management, the most common of which are steroids and immunomodulatory therapies. This review aims to summarize the current biomarkers for predicting irAE in gastric cancer and their possible mechanisms.

Combination of verteporfin-photodynamic therapy with 5-aza-2'-deoxycytidine enhances the anti-tumour immune response in triple negative breast cancer

Introduction

Triple negative breast cancer (TNBC) is a subtype of breast cancer characterised by its high tumourigenic, invasive, and immunosuppressive nature. Photodynamic therapy (PDT) is a focal therapy that uses light to activate a photosensitizing agent and induce a cytotoxic effect. 5-aza-2'-deoxycytidine (5-ADC) is a clinically approved immunomodulatory chemotherapy agent. The mechanism of the combination therapy using PDT and 5-ADC in evoking an anti-tumour response is not fully understood.

Methods

The present study examined whether a single dose of 5-ADC enhances the cytotoxic and anti-tumour immune effect of low dose PDT with verteporfin as the photosensitiser in a TNBC orthotopic syngeneic murine model, using the triple negative murine mammary tumour cell line 4T1. Histopathology analysis, digital pathology and immunohistochemistry of treated tumours and distant sites were assessed. Flow cytometry of splenic and breast tissue was used to identify T cell populations. Bioinformatics were used to identify tumour immune microenvironments related to TNBC patients.

Results

Functional experiments showed that PDT was most effective when used in combination with 5-ADC to optimize its efficacy. 5-ADC/PDT combination therapy elicited a synergistic effect in vitro and was significantly more cytotoxic than monotherapies on 4T1 tumour cells. For tumour therapy, all types of treatments demonstrated histopathologically defined margins of necrosis, increased T cell expression in the spleen with absence of metastases or distant tissue destruction. Flow cytometry and digital pathology results showed significant increases in CD8 expressing cells with all treatments, whereas only the 5-ADC/PDT combination therapy showed increase in CD4 expression. Bioinformatics analysis of in silico publicly available TNBC data identified BCL3 and BCL2 as well as the following anti-tumour immune response biomarkers as significantly altered in TNBC compared to other breast cancer subtypes: GZMA, PRF1, CXCL1, CCL2, CCL4, and CCL5. Interestingly, molecular biomarker assays showed increase in anti-tumour response genes after treatment. The results showed concomitant increase in BCL3, with decrease in BCL2 expression in TNBC treatment. In addition, the treatments showed decrease in PRF1, CCL2, CCL4, and CCL5 genes with 5-ADC and 5-ADC/PDT treatment in both spleen and breast tissue, with the latter showing the most decrease.

Discussion

To our knowledge, this is the first study that shows which of the innate and adaptive immune biomarkers are activated during PDT related treatment of the TNBC 4T1 mouse models. The results also indicate that some of the immune response biomarkers can be used to monitor the effectiveness of PDT treatment in TNBC murine model warranting further investigation in human subjects.

Genomic characterization between HER2-positive and negative gastric cancer patients in a prospective trial

BACKGROUND

We aimed to clarify the genomic characteristics of HER2-positive and negative gastric cancer cases that potentially affect tumor progression and treatment response in a prospective trial.

METHODS

We collected 80 formalin-fixed paraffin-embedded (FFPE) samples (49 HER2+ and 31 HER2-) from gastric cancer patients who participated in the TROX-A1 trial (UMIN000036865). We queried a 435-gene panel (CANCERPLEX-JP) to generate comprehensive genomic profiling data, including the tumor mutation burden, somatic mutations, and copy number variations. In addition, the genomic differences between HER2+ and HER2- gastric cancer patients were analyzed.

RESULTS

Mutational analyses showed that TP53 was the most frequently mutated gene regardless of HER2 status. ARID1A mutation was significantly enriched in HER2-negative patients. The number of total mutations in HER2-negative patients with ARID1A mutation was remarkably higher than that in HER2-positive patients. Next, copy number variation analyses showed that the number of amplified genes (such as CCNE1, PGAP3, and CDK12) in HER2-positive cases was significantly higher than that in HER2-negative cases. Moreover, PTEN deletion was more common in HER2-positive cases. Finally, we found that, compared with HER2-positive patients, HER2-negative patients tended to have a higher tumor mutation burden, particularly in patients with ARID1A mutation. Pathway analyses of the gene alterations showed an enrichment of several immune-related pathways in HER2-negative patients.

CONCLUSIONS

According to the genomic profiling of HER2-positive and negative gastric cancer, several gene alterations in the HER2 pathway may be the potential mechanism underlying trastuzumab resistance. Relative to HER2-positive gastric cancer, HER2-negative gastric tumors with ARID1A mutation may be sensitive to immune checkpoint inhibitors.

Tumor-secreted IFI35 promotes proliferation and cytotoxic activity of CD8+ T cells through PI3K/AKT/mTOR signaling pathway in colorectal cancer

BACKGROUND

A large proportion of the patients with cancer do not respond to immunotherapies. Recent studies suggested an important role for tumor-infiltrating cytotoxic T lymphocytes (CTL) in enhancing response to immunotherapy. Here, we aim to identify gene that induce proliferative and cytotoxic states of CD8⁺ T cells, and to investigate its effect on CAR-T cells against colorectal cancer.

METHODS

Correlation between the expression of IFI35 with the activation and cytotoxicity of CD8⁺ T cells was assessed with TCGA and proteomic databases. Then we constructed murine colon cancer cells over-expressing IFI35 and tested their effect on anti-tumor immunity in both immunodeficient and immunocompetent mouse models. Flow cytometry and immunohistochemistry were performed to assess the immune microenvironment. Western blot analysis was used to identify the potential down-stream signaling pathway regulated by IFI35. We further investigated the efficacy of the rhIFI35 protein in combination with immunotherapeutic treatment.

RESULTS

The transcriptional and proteomic analysis of the activation and cytotoxicity of CD8⁺ T cells in human cancer samples demonstrated that IFI35 expression is correlated with increased CD8⁺ T cell infiltration and predicted a better outcome in colorectal cancer. The number and cytotoxicity of CD8⁺ T cells were significantly increased in IFI35-overexpressing tumors. Mechanistically, we identified that the IFNγ-STAT1-IRF7 axis stimulated IFI35 expression, and that IFI35-mediated regulation of CD8⁺ T cell proliferation and cytotoxicity was dependent on PI3K/AKT/mTOR signaling pathway in vitro. Furthermore, IFI35 protein enhanced the efficacy of CAR-T cells against colorectal cancer cells.

CONCLUSION

Our findings identify IFI35 as a new biomarker that can enhance the proliferation and function of CD8⁺ T cells, as well as increase the efficacy of CAR-T cells against colorectal cancer cells.

The characteristics and clinical relevance of tumor fusion burden in non-EBV (+) gastric cancer with MSS

BACKGROUND

Next-generation sequencing (NGS) is maturely applied for gene fusion detection. Although tumor fusion burden (TFB) has been identified as an immune marker for cancer, the relationship between these fusions and the immunogenicity and molecular characteristics of gastric cancer (GC) patients remains unclear. GCs have different clinical significance depending on their subtypes, and thus, this study aimed to investigate the characteristics and clinical relevance of TFB in non-Epstein-Barr-virus-positive (EBV+) GC with microsatellite stability (MSS).

METHODS

A total of 319 GC patients from The Cancer Genome Atlas stomach adenocarcinoma (TCGA-STAD) and a cohort of 45-case from ENA (PRJEB25780) were included. The cohort characteristics and distribution of TFB among the patients were analyzed. Additionally, the correlations of TFB with mutation characteristics, pathway differences, relative abundance of immune cells, and prognosis were examined in the TCGA-STAD cohort of MSS and non-EBV (+) patients.

RESULTS

We observed that in the MSS and non-EBV (+) cohort, the TFB-low group exhibited significantly lower gene mutation frequency, gene copy number, loss of heterozygosity score, and tumor mutation burden than in the TFB-high group. Additionally, the TFB-low group exhibited a higher abundance of immune cells. Furthermore, the immune gene signatures were significantly upregulated in the TFB-low group, 2-year disease-specific survival was markedly increased in the TFB-low group compared with to the TFB-high group. The rates of TFB-low cases were significantly higher TFB-than high cases in durable clinical benefit (DCB) and response groups with pembrolizumab treatment. Low TFB may serve as a predictor of GC prognosis, and the TFB-low group exhibits higher immunogenicity.

CONCLUSION

In conclusion, this study reveals that the TFB-based classification of GC patient may be instructive for individualized immunotherapy regimens.

Identification and Biological Validation of a Chemokine/Chemokine Receptor-Based Risk Model for Predicting Immunotherapeutic Response and Prognosis in Head and Neck Squamous Cell Carcinoma

Over 80% of head and neck squamous cell carcinoma (HNSCC) patients failed to respond to immunotherapy, which can likely be attributed to the tumor microenvironment (TME) remolding mediated by chemokines/chemokine receptors (C/CR). This study aimed to establish a C/CR-based risk model for better immunotherapeutic responses and prognosis. After assessing the characteristic patterns of the C/CR cluster from the TCGA-HNSCC cohort, a six-gene C/CR-based risk model was developed to stratify patients by LASSO Cox analysis. The screened genes were multidimensionally validated by RT-qPCR, scRNA-seq, and protein data. A total of 30.4% of patients in the low-risk group had better responses to anti-PD-L1 immunotherapy. A Kaplan-Meier analysis showed that patients in the low-risk group had longer overall survival. A time-dependent receiver operating characteristic curve and Cox analyses indicated that risk score served as an independent predictive indicator. The robustness of the immunotherapy response and prognosis prediction was also validated in independent external datasets. Additionally, the TME landscape revealed that the low-risk group was immune activated. Furthermore, the cell communication analysis on the scRNA-seq dataset revealed that cancer-associated fibroblasts were the main communicators within the C/CR ligand-receptor network of TME. Collectively, The C/CR-based risk model simultaneously predicted immunotherapeutic response and prognosis, potentially optimizing personalized therapeutic strategies of HNSCC.

Expression patterns and prognostic value of key regulators associated with m7G RNA modification based on all gene expression in colon adenocarcinoma

BACKGROUND

N7-methylguanosine (m7G) is present in a wide variety of organisms and has important roles. m7G has been reported to be involved in multiple biological processes, and recent studies have reported that changes in RNA modifications result in tumor cellular transformation and cancer, such as colon adenocarcinoma, lung cancer, and intrahepatic cholangiocarcinoma. However, little is known about the function of the m7G in colon adenocarcinoma.

METHODS

We established two clusters based on the expression of all genes associated with m7G to explore the expression pattern of 31 key regulatory factors of m7G RNA and assess the prognostic value of regulatory factors. Wilcoxon test and differential box line plots were applied for bioinformatics analysis. Receiver Operating and Kaplan‒Meier curves were utilized to evaluate the prognostic value. Finally, four genes' expression in the colon cancer cell line was confirmed by qRT-PCR.

RESULTS

From The Cancer Genome Atlas database, we found that the expression levels of 25 out of the 31 key N7-methylguanosine RNA modification regulators were significantly different in colon adenocarcinoma. According to 25 methylation regulators' expression, we identified two subgroups by consensus clustering, in which the prognosis was worse in Group 2 than in Group 1 and was significantly correlated with age. Cluster 2 was significantly enriched in tumor-associated pathways, and immune cells were highly infiltrated in Cluster 1 but weakly infiltrated in Cluster 2. Further results indicated that this risk profile may serve as a standalone predictive factor for colon adenocarcinoma, and the four genetic risk profiles' prognostic relatedness was successfully verified through Gene Expression Omnibus dataset. At last, A nomogram for prognosis was created according to age, sex, histological grading, clinicopathological staging, and hazard score to accurately predict patient prognosis in colon adenocarcinoma. We successfully validated the differential expression of four genes using qRT-PCR.

CONCLUSIONS

In the present study, we revealed the important contribution of key regulators associated with m7G RNA modifications based on all gene expression in colon adenocarcinoma and developed a signature of risk that serves as a promising prognostic marker for patients with colon adenocarcinoma.

Autophagy-related IFNG is a prognostic and immunochemotherapeutic biomarker of COAD patients

Background

Numerous studies have shown autophagy affects cellular immune responses. This study aims to explore prognosis and immunotherapeutic biomarkers related to autophagy in colon adenocarcinoma (COAD).

Methods

Based on R software, we performed the ssGSEA, differential expression analysis, Kaplan-Meier survival analysis, correlation analysis, and enrichment analysis. For wet experiment, we did qRT-PCR, immunohistochemistry and CCK-8 experiments.

Results

Using autophagy-related genes (ARGs) and the ssGSEA, COAD patients were divided into low and high autophagy groups. For immune score, stromal score, tumor purity, tumor infiltrating immune cells, co-signaling molecules, tumor mutational burden, microsatellite instability, mismatch repair, immune-related pathways, immune signatures, somatic mutations and subtype analysis, high autophagy group might benefit more from immunotherapy. Among 232 ARGs, IFNG was generally significantly correlated with tumor immunotherapy biomarkers (PD-L1, CD8A and cytotoxic T lymphocytes (CTL)). The disease-free survival of high IFNG group was significantly longer than that of low group. On above-mentioned immune-related research, the high IFNG group reached the same conclusion. The qRT-PCR and IHC analysis confirmed that IFNG was significantly higher expressed in dMMR samples compared to pMMR samples. For chemotherapy, the autophagy and IFNG were significantly negatively related to the chemosensitivity to cisplatin; IFNG inhibitor glucosamine increased cisplatin chemoresistance while IFNG increased cisplatin chemosensitivity; IFNG could reverse glucosamine induced chemoresistance. The functional enrichment analysis of IFNG, PD-L1, CD8A and 20 similar proteins were related to the activation of the immune system. The GSEA and ceRNA network partly described interaction mechanisms of IFNG with PD-L1 and CD8A.

Conclusion

Autophagy score and IFNG expression were novel immunotherapy predictive biomarkers, which might play predictive effects through the JAK-STAT signaling pathway. IFNG might be a potential targeted therapy for cisplatin resistant colon cancer. Besides, IFNG was also a prognostic indicator.

Analysis of scRNA-seq and bulk RNA-seq demonstrates the effects of EVI2B or CD361 on CD8+ T cells in osteosarcoma

Osteosarcoma (OS) is a common primary malignant tumor of the bone in children and adolescents. The five-year survival rate is estimated to be ~70% based on the currently available treatment modalities. It is well known that tumor-infiltrating immune cells (TIICs) that are the most important components in the tumor microenvironment can exert a killing effect on tumor cells. Therefore, in the present study, 85 RNA-sequencing OS samples were categorized into high- and low-immune score groups with ESTIAMATE. Based on the immune score groups, 474 differentially expressed genes (DEGs) were acquired using the LIMMA package of R language. Subsequently, 86 DEGs were taken through univariate COX regression analysis, of which 14 were screened out by least absolute shrinkage and selection operator regression analysis. Furthermore, multivariate COX regression analysis was performed to obtain 4 DEGs. Finally, ecotropic virus integration site 2B (EVI2B) or CD361 gene was screened out via Kaplan-Meier analysis. In addition, CIBERSORT algorithm was used to evaluate the proportion of 22 kinds of TIICs in OS. Correlation analysis revealed that the high expression level of EVI2B can elevate the infiltrated proportion of CD8⁺ T cells. Moreover, analysis of single cell RNA-sequencing transcriptome datasets and immunohistochemical staining uncovered that EVI2B was mainly expressed on CD8⁺ T cells and that EVI2B could promote the expression of granzyme A and K of CD8⁺ T cells to exhibit a potent killing effect on tumor cells. Therefore, EVI2B was identified as a protective immune-related gene and contributed to good prognosis in OS patients.

PRC2-Mediated Epigenetic Suppression of Type I IFN-STAT2 Signaling Impairs Antitumor Immunity in Luminal Breast Cancer

The immunosuppressive tumor microenvironment in some cancer types, such as luminal breast cancer, supports tumor growth and limits therapeutic efficacy. Identifying approaches to induce an immunostimulatory environment could help improve cancer treatment. Here, we demonstrate that inhibition of cancer-intrinsic EZH2 promotes antitumor immunity in estrogen receptor α-positive (ERα+) breast cancer. EZH2 is a component of the polycomb-repressive complex 2 (PRC2) complex, which catalyzes trimethylation of histone H3 at lysine 27 (H3K27me3). A 53-gene PRC2 activity signature was closely associated with the immune responses of ERα+ breast cancer cells. The stimulatory effects of EZH2 inhibition on immune surveillance required specific activation of type I IFN signaling. Integrative analysis of PRC2-repressed genes and genome-wide H3K27me3 landscape revealed that type I IFN ligands are epigenetically silenced by H3K27me3. Notably, the transcription factor STAT2, but not STAT1, mediated the immunostimulatory functions of type I IFN signaling. Following EZH2 inhibition, STAT2 was recruited to the promoters of IFN-stimulated genes even in the absence of the cytokines, suggesting the formation of an autocrine IFN-STAT2 axis. In patients with luminal breast cancer, high levels of EZH2 and low levels of STAT2 were associated with the worst antitumor immune responses. Collectively, this work paves the way for the development of an effective therapeutic strategy that may reverse immunosuppression in cancer.

SIGNIFICANCE

Inhibition of EZH2 activates a type I IFN-STAT2 signaling axis and provides a therapeutic strategy to stimulate antitumor immunity and therapy responsiveness in immunologically cold luminal breast cancer.

Systematic Analysis of Molecular Subtypes Based on the Expression Profile of Immune-Related Genes in Pancreatic Cancer

Immunotherapy has a good therapeutic effect and provides a new approach for cancer treatment. However, only limited studies have focused on the use of molecular typing to construct an immune characteristic index for gene expression in pancreatic adenocarcinoma (PAAD) and to assess the effectiveness of immunotherapy in patients with PAAD. Clinical follow-up data and gene expression profile of PAAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Based on 184 immune features, molecular subtypes of pancreatic cancer were found by the "ConsensusClusterPlus" package, and the association between clinical features and immune cell subtype distribution was analysed. In addition, the relationship between the proportion of immune subtypes and the expression of immune checkpoints was analysed. The CIBERSORT algorithm was introduced to evaluate the immune scores of different molecular subtypes. We used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the potential clinical effect of immunotherapy interventions on single-molecule subtypes. In addition, the oxidative stress index was constructed by linear discriminant analysis DNA (LDA), and weighted correlation network analysis was performed to identify the core module of the index and its characteristic genes. Expression of hub genes was verified by immunohistochemical analysis in an independent PAAD cohort. Pancreatic cancer is divided into three molecular subtypes (IS1, IS2, and IS3), with significant differences in prognosis between multiple cohorts. Expression of immune checkpoint-associated genes was significantly reduced in IS3 and higher in IS1 and IS2, suggesting that the three subgroups have different responsiveness to immunotherapy interventions. The results of the CIBERSORT analysis showed that IS1 exhibited the highest levels of immune infiltration, whereas the results of the TIDE analysis showed that the T-cell dysfunction score of IS1 was higher than that of IS2 and IS3. Furthermore, IS3 was found to be more sensitive to 5-FU and to have a higher immune signature index than IS1 and IS2. Based on WGCNA analysis, 10 potential gene markers were identified, and their expression at the protein level was verified by immunohistochemical analysis. Specific molecular expression patterns in pancreatic cancer can predict the efficacy of immunotherapy and influence the prognosis of patients.

Comprehensive Multiomic Analysis Identified TUBA1C as a Potential Prognostic Biological Marker of Immune-Related Therapy in Pan-Cancer

TUBA1C is correlated with an unfavourable prognosis and the infiltration of immune cells in several cancers. However, its function as a significant biomarker for the prognosis of immunotherapy in pan-cancer remains unclear. This study aims at assessing the role of TUBA1C in pan-cancer at multiple levels, including mutations, gene expression, methylation, m6A methylation, and immune cell infiltration levels. Data retrieved from major public databases, such as TCGA, GEO, GTEx, GSCA, CancerSEA, HPA, and RNAactDrugs, revealed that TUBA1C expression was high in 33 cancer types. Survival analysis revealed that TUBA1C was a poor prognostic factor for 12 tumour types, and mutations, CNVs, and methylation affected the prognosis of some cancer types. Furthermore, TUBA1C was found to be related to immune-related genes, immune cell infiltration, and the immune microenvironment. In addition, the sensitivity of 10 anticancer drugs was associated with high TUBA1C expression. Therefore, TUBA1C may serve as a viable prognostic biomarker for immunotherapy of pan-cancer.

Discovery of New Therapeutic Targets for Osteosarcoma Treatment Based on Immune-Related lncRNAs in the Tumor Microenvironment

Background

Long noncoding RNAs (lncRNAs) play an important role in osteosarcoma development, but their role in the tumor microenvironment (TME) is not fully understood. This study associated lncRNAs with immune-related genes and explored the mechanism of lncRNAs in osteosarcoma progression.

Methods

Unsupervised consensus clustering was applied to construct immune subtypes based on immune-related lncRNAs identified by Pearson's correlation analysis. A series of functional analysis was performed to reveal the links among lncRNAs, immune subtypes, TME, and osteosarcoma prognosis.

Results

We identified two immune subtypes C1 and C2 showing distinct overall survival. ECM-receptor interaction pathway was more activated in C2 subtype, while immune response pathways were more enriched in C2 subtype. Differential TME and response to chemotherapeutic drugs were observed between the two subtypes. Four metagenes of costimulation, cytolytic activity (CYT), immune score, and STAT1 were differentially enriched in the two subtypes. Based on 26-paired lncRNAs, we constructed a 4-paired lncRNA prognostic signature for predicting prognosis of osteosarcoma prognosis.

Conclusions

This study focused on immune-related lncRNAs and TME, showing the possible role and mechanisms of lncRNAs in tumor growth and metastasis. ECM may be the new therapeutic target for treating osteosarcoma, and 26-paired lncRNAs could serve as a basis for further studying the mechanisms of CYT and STAT1 in immune response, cancer cell proliferation, and migration. The two subtypes and prognostic signature could promote the design of personalized osteosarcoma treatment.

Prognostic Ferroptosis-Related lncRNA Signatures Associated With Immunotherapy and Chemotherapy Responses in Patients With Stomach Cancer

Ferroptosis is associated with the prognosis and therapeutic responses of patients with various cancers. LncRNAs are reported to exhibit antitumor or oncogenic functions. Currently, few studies have assessed the combined effects of ferroptosis and lncRNAs on the prognosis and therapy of stomach cancer. In this study, transcriptomic and clinical data were downloaded from TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the Lasso algorithm, 10 prognostic ferroptosis-related lncRNAs (AC009299.2, AC012020.1, AC092723.2, AC093642.1, AC243829.4, AL121748.1, FLNB-AS1, LINC01614, LINC02485, LINC02728) were screened to construct a prognostic model, which was verified in two test cohorts. Risk scores for patients with stomach cancer were calculated, and patients were divided into two risk groups. The low-risk group, based on the median value, had a longer overall survival time in the KM curve, and a lower proportion of dead patients in the survival distribution curve. Potential mechanisms and possible functions were revealed using GSEA and the ceRNA network. By integrating clinical information, the association between lncRNAs and clinical features was analyzed and several features affecting prognosis were identified. Then, a nomogram was developed to predict survival rates, and its good predictive performance was indicated by a relatively high C-index (0.67118161) and a good match in calibration curves. Next, the association between these lncRNAs and therapy was explored. Patients in the low-risk group had an immune-activating environment, higher immune scores, higher TMB, lower TIDE scores, and higher expression of immune checkpoints, suggesting they might receive a greater benefit from immune checkpoint inhibitor therapy. In addition, a significant difference in the sensitivity to mitomycin. C, cisplatin, and docetaxel, but not etoposide and paclitaxel, was observed. In summary, this model had guiding significance for prognosis and personalized therapy. It helped screen patients with stomach cancer who might benefit from immunotherapy and guided the selection of personalized chemotherapeutic drugs.

Immunological Classification of Pancreatic Carcinomas to Identify Immune Index and Provide a Strategy for Patient Stratification

Background

Cancer immunotherapy has produced significant positive clinical effects in a variety of tumor types. However, pancreatic ductal adenocarcinoma (PDAC) is widely considered to be a "cold" cancer with poor immunogenicity. Our aim is to determine the detailed immune features of PDAC to seek new treatment strategies.

Methods

The immune cell abundance of PDAC patients was evaluated with the single-sample gene set enrichment analysis (ssGSEA) using 119 immune gene signatures. Based on these data, patients were classified into different immune subtypes (ISs) according to immune gene signatures. We analyzed their response patterns to immunotherapy in the datasets, then established an immune index to reflect the different degrees of immune infiltration through linear discriminant analysis (LDA). Finally, potential prognostic markers associated with the immune index were identified based on weighted correlation network analysis (WGCNA) that was functionally validated in vitro.

Results

Three ISs were identified in PDAC, of which IS3 had the best prognosis across all three cohorts. The different expressions of immune profiles among the three ISs indicated a distinct responsiveness to immunotherapies in PDAC subtypes. By calculating the immune index, we found that the IS3 represented higher immune infiltration, while IS1 represented lower immune infiltration. Among the investigated signatures, we identified ZNF185, FANCG, and CSTF2 as risk factors associated with immune index that could potentially facilitate diagnosis and could be therapeutic target markers in PDAC patients.

Conclusions

Our findings identified immunologic subtypes of PDAC with distinct prognostic implications, which allowed us to establish an immune index to represent the immune infiltration in each subtype. These results show the importance of continuing investigation of immunotherapy and will allow clinical workers to personalized treatment more effectively in PDAC patients.