Immune Subtypes Research Articles

Pan-cancer analysis reveals the characteristics and roles of tooth agenesis mutant genes.

Tooth development is regulated by numerous genes and signaling pathways. Some studies suggest that mutations in these genes may be associated with several cancer types. However, the tooth agenesis mutated genes role in the prognosis and their clinical therapeutic potentials in pan-cancer have not been elaborately explored. Moreover, the intrinsic correlation between tooth agenesis and cancers also needs to be further verified. We preliminarily analyzed expression levels and prognostic values of causative genes of tooth agenesis, and explored the correlation between the expression of tooth agenesis mutated genes and TME, Stemness score, clinical characteristic, immune subtype, and drug sensitivity in pan-cancer, which based on updated public databases and integrated some bioinformatics analysis methods. In addition, we conducted the enrichment analysis of tooth agenesis mutant genes from KOBAS database. We observed that TA mutant genes had significant gene expression differences in multiple cancer types compared with normal tissues. The expression of causative genes of TA is associated with the prognosis in several cancers from different databases. For example, AXIN2 and MSX1 were correlated to the overall survival (OS) of uterine corpus endometrial carcinoma. PAX9 and TP63 were related to OS of lung squamous cell carcinoma. And TP63 was associated with OS in breast invasive carcinoma and pancreatic adenocarcinoma. Furthermore, the expression of TA mutant genes also has a significant correlation with stromal and immune scores, and RNA stemness score and DNA stemness score in pan-cancer. Besides, we observed that all causative genes of TA were significantly correlated with immune subtypes. Moreover, KEGG pathway analysis showed that causative genes of TA were associated with the development and progression of breast cancer, basal cell carcinoma, gastric cancer, and hepatocellular carcinoma. Finally, AXIN2 expression has a significantly positive or negative correlation with drug sensitivity. Our study indicates the great potential of TA mutant genes as biomarkers for prognosis and provides valuable strategies for further investigation of TA mutant genes as potential therapeutic targets in cancers. Our study can further verify that there may be an intrinsic correlation between tooth agenesis and the occurrence of multiple cancers.

Identification of ACBD3 as a new molecular biomarker in pan-cancers through bioinformatic analysis: a preclinical study

BackgroundAcyl-CoA-binding domain-containing 3 (ACBD3) is a multifunctional protein, that plays essential roles in cellular signaling and membrane domain organization. Although the precise roles of ACBD3 in various cancers remain unclear. Thus, we aimed to determine the diverse roles of ACBD3 in pan-cancers.MethodsRelevant clinical and RNA-sequencing data for normal tissues and 33 tumors from The Cancer Genome Atlas (TCGA) database, the Human Protein Atlas, and other databases were applied to investigate ACBD3 expression in various cancers. ACBD3-binding and ACBD3-related target genes were obtained from the STRING and GEPIA2 databases. The possible functions of ACBD3-binding genes were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also applied the diagnostic value and survival prognosis analysis of ACBD3 in pan-cancers using R language. The mutational features of ACBD3 in various TCGA cancers were obtained from the cBioPortal database.ResultsWhen compared with normal tissues, ACBD3 expression was statistically upregulated in eleven cancers and downregulated in three cancers. ACBD3 expression was remarkably different among various pathological stages of tumors, immune and molecular subtypes of cancers, cancer phosphorylation levels, and immune cell infiltration. The survival of four tumors was correlated with the expression level of ACBD3, including pancreatic adenocarcinoma, adrenocortical carcinoma, sarcoma, and glioma. The high accuracy in diagnosing multiple tumors and its correlation with prognosis indicated that ACBD3 may be a potential biomarker of pan-cancers.ConclusionAccording to our pan-cancer analysis, ACBD3 may serve as a remarkable prognostic and diagnostic biomarker of pan-cancers as well as contribute to tumor development. ACBD3 may also provide new directions for cancer treatment targets in the future.

A pan-cancer analysis of anti-proliferative protein family genes for therapeutic targets in cancer

The recently discovered APRO (anti-proliferative protein) family encodes a group of trans-membrane glycoproteins and includes 6 members: TOB1, TOB2, BTG1, BTG2, BTG3 and BTG4. The APRO family is reportedly associated with the initiation and progression of cancers. This study aims to undertake a comprehensive investigation of the APRO family of proteins as a prognostic biomarker in various human tumors. We performed a pan-cancer analysis of the APRO family based on The Cancer Genome Atlas (TCGA). With the bioinformatics methods, we explored the prognostic value of the APRO family and the correlation between APRO family expression and tumor mutation burden (TMB), microsatellite instability (MSI), drug sensitivity, and immunotherapy in numerous cancers. Our results show that the APRO family was primarily down-regulated in cancer samples. The expression of APRO family members was linked with patient prognosis. In addition, APRO family genes showed significant association with immune infiltrate subtypes, tumor microenvironment, and tumor cell stemness. Finally, our study also demonstrated the relationship between APRO family genes and drug sensitivity. This study provides comprehensive information to understand the APRO family’s role as an oncogene and predictor of survival in some tumor types.

RNA Expression-Based Analysis to Predict Response in Patients with Metastatic Mismatch Repair Proficient Colorectal Cancer Treated with Regorafenib and Nivolumab

Introduction: We previously conducted a phase I/Ib study (NCT03712943) with regorafenib and nivolumab in patients with refractory metastatic mismatch repair proficient (pMMR) colorectal cancer (CRC). This study aimed to investigate the role of Xerna™ TME Panel in predicting the treatment response. Methods: Twenty-two archival pretreatment tumor samples were subjected to the Xerna™ TME Panel, a machine learning-based RNA-sequencing biomarker assay. The Xerna tumor microenvironment (TME) subtypes were evaluated for correlation with overall survival (OS), progression-free survival (PFS), disease control rate (DCR), and other biomarkers including KRAS, PD-L1, CD8 expression, and Treg cells in TME. Results: Based on Xerna™ TME Panel, 4 patients with immune-active (IA) subtype and 6 patients with immune-suppressed subtype were classified as biomarker-positive, and five with angiogenic (A) subtype and seven with immune desert subtype were biomarker-negative. While not reaching statistical significance, Xerna TME biomarker-positive patients seemed to have longer median PFS (7.9 vs. 4.1 months, p = 0.254), median OS (15.75 vs. 11.9 months, p = 0.378), and higher DCR (70% vs. 58%, p = 0.675). The IA subtype in our cohort had higher levels of CD4+ FOXP3+ Treg cells, whereas the A subtype showed lower levels of Treg cells. Conclusion: Xerna™ TME Panel analysis in patients with refractory metastatic pMMR CRC who were treated with regorafenib plus nivolumab might be of value for predictive clinical benefit. Further studies are needed to evaluate the predictive role of Xerna™ TME Panel analysis in patients with refractory metastatic pMMR CRC.

Prognostic significance and immune characteristics of APOE in gastric cancer.

Gastric cancer (GC) is a prevalent malignancy affecting the digestive system, and it is the second leading cause of cancer-related mortality worldwide. Immunotherapy presents a potential lifeline for patients with advanced gastric cancer, emphasizing the need to find new molecular targets that improve the response to immunotherapy. In our research, we conducted a comprehensive bioinformatic analysis to investigate the expression profiles of apolipoprotein E (APOE) transcription. Subsequently, we examined the correlation between APOE transcription and the prognosis of GC patients. Additionally, we evaluated the connection between APOE transcription and immune cells abundance. To validate our findings, we conducted immunohistochemistry experiment to ascertain the level of APOE protein in GC patients and assessed its prognostic role in a cohort of 97 GC individuals. Our results revealed that APOE is increased in GC tissues, and APOE displays diagnostic potential in distinguishing GC from normal tissues. Notably, upregulated APOE expression in GC patients is associated with unfavorable overall survival. Differential APOE expression was further observed across different immune subtypes of GC, indicating its involvement in immune cell activation and infiltration. Moreover, we detected increased APOE protein expression in GC tissues, which exhibited a strong correlation with poor survival outcomes. In light of these findings, APOE has become a crucial prognostic molecular with immunomodulatory function in GC. These results underscore the significance of APOE across various cancer types, including GC, and provide valuable insights into its role from both a bioinformatics and clinical perspective.

Comprehensive analysis of m6A reader YTHDF2 prognosis, immune infiltration, and related regulatory networks in hepatocellular carcinoma

BackgroundN6-Methyladenosine (m6A) RNA modification is the most prevalent internal modification pattern in eukaryotic mRNAs and plays critical roles in diverse physiological and pathological processes. However, the expression of m6A regulator YTHDF2, its prognostic value, its biological function, its correlation with tumor microenvironment (TME) immune infiltrates, and related regulatory networks in hepatocellular carcinoma (HCC) remain determined. MethodsTCGA, GTEx, and GEO databases were used to investigate the expression profile of YTHDF2 in HCC. We performed differentially expressed genes (DEGs) analysis and constructed a PPI network to explore the biological processes of YTHDF2 in HCC. Kaplan-Meier curves and Cox regression analysis were used to assess the prognostic value of YTHDF2 and then a clinical prognostic nomogram was constructed. Additionally, ssGSEA was performed to assess the correlation between YTHDF2 and immune infiltration levels. The TISIDB database was applied to explore the expression of YTHDF2 in immune and molecular subtypes of HCC. GSEA identifies the YTHDF2-related signaling pathways. Finally, we utilized miRNet and starBase database to construct regulatory networks for HCC based on lncRNA-miRNA and miRNA-YTHDF2 interactions. ResultsYTHDF2 was significantly upregulated in HCC tumor tissues compared with the adjacent normal tissues. HCC patients in the high YTHDF2 expression group had poorer survival. Multivariate Cox analysis suggested that YTHDF2 may be a new independent prognostic indicator for HCC patients, with the prognostic nomogram exhibiting satisfactory results. YTHDF2 expression was significantly correlated with TME immune cell-infiltrating characteristics. Strong correlations were also shown in immune subtypes, molecular subtypes and immune checkpoints. Further analysis revealed that the combination of YTHDF2 expression and immune cell score was considerably associated with survival outcome in HCC patients. GESA analysis demonstrated that high YTHDF2 expression is associated with multiple biological processes and oncogenic pathways. Moreover, 14 possible regulatory networks were constructed, which are associated with HCC progression. ConclusionOur findings revealed that YTHDF2 may serve as a promising prognostic biomarker for HCC and may regulate the tumor immune microenvironment to provide effective therapeutic strategies.

TREM2‐related Polygenic Risk Score predicts defect Innate Immune Activation in Alzheimer’s Disease

AbstractBackgroundTREM2 plays a central role in immune response which, in turn, is strongly related to Alzheimer’s disease (AD) pathology. We previously found an AD‐subtype with and without innate immune activation based on CSF proteomics. Possibly, genes associated with TREM2 pathways could explain differences between these two subtypes since R47H and R62H mutations are associated with decreased microglial activation. We tested this hypothesis in a large single site cohort, and compared them on PRS including previously reported GWAS genes associated with TREM2 pathways.MethodWe included participants from the Amsterdam Dementia Cohort who had AD subtyping based on CSF proteomics available (n = 466). Based on literature, we labelled 19 of 83 known AD risk genes as belonging to TREM2 pathways and used these to construct a TREM2‐PRS. We studied associations between a standard AD‐PRS with 83 SNPs, TREM2‐PRS with 19 SNPs and non‐TREM2‐PRS with 64 SNPs between two AD‐subtypes being (1) without innate immune activation and (2) with innate immune activation, using logistic regression models (correcting for sex, age and 5 principal components).ResultThe cohort involved 146 controls (mean age 61 years, 34% female) and 195 AD cases: 97 without immune activation subtype (mean age 64 years, 52% female) and 98 with immune activation subtype (mean age 68 years, 54% female). Both subtypes showed comparable increased risk on the standard AD‐PRS compared to controls (OR 1.65, 95%CI 1.2‐2.3, p = 0.002 and OR 1.7, 95%CI 1.1‐2.5, p = 0.006) (Table 1). A higher TREM2‐PRS was associated with no immune activation subtype (OR 1.5, 95%CI 1.1‐2.1, p = 0.008). The PRS of the other 64 risk variants, which were not labelled as belonging to TREM2 pathways, was associated with immune activation subtype (OR 1.5, 95%CI 1.1‐2.1, p = 0.02).ConclusionAD individuals with a CSF proteomic‐based subtype without immune activation show more genetic variants in TREM2 pathways, whereas these SNPs are not related to the subtype with innate immune activation. These findings provide evidence for genetic differences underlying AD‐subtypes, and suggest that therapies targeting immune functioning may need to tailor therapies to AD‐subtype (i.e., additional activation vs. decreasing activation).

Comprehensive bioinformatics analysis of FXR1 across pan-cancer: Unraveling its diagnostic, prognostic, and immunological significance.

Fragile X-related protein 1 (FXR1) is an RNA-binding protein that belongs to the fragile X-related (FXR) family. Studies have shown that FXR1 plays an important role in cancer cell proliferation, invasion and migration and is differentially expressed in cancers. This study aimed to gain a comprehensive and systematic understanding of the analysis of FXR1's role in cancers. This would lead to a better understanding of how it contributes to the development and progression of various malignancies. this study conducted through The Cancer Genome Atlas (TCGA), GTEx, cBioPortal, TISIDB, GEPIA2 and HPA databases to investigated FXR1's role in cancers. For data analysis, various software platforms and web platforms were used, such as R, Cytoscape, hiplot plateform. A significant difference in FXR1 expression was observed across molecular and immune subtypes and across types of cancer. FXR1 expression correlates with disease-specific survival (DSS), and overall survival (OS) in several cancer pathways, further in progression-free interval (PFI) in most cancers. Additionally, FXR1 showed a correlation with genetic markers of immunomodulators in different cancer types. Our study provides insights into the role of FXR1 in promoting, inhibiting, and treating diverse cancers. FXR1 has the potential to serve as a diagnostic and prognostic biomarker for cancer, with therapeutic value in immune-based, targeted, or cytotoxic treatments. Further clinical validation and exploration of FXR1 in cancer treatment is necessary.

Identification of enhancer RNA AC005515.1 as a novel biomarker for prognosis in esophageal cancer and predictors of immunotherapy response.

The enhancer RNA (eRNA) signature shows excellent promise in the prognostic role of many malignancies, but its value has not been fully explored in esophageal cancer (ESCA). We comprehensively analyzed 33 oncogene expression matrices and clinical data from The Cancer Genome Atlas (TCGA) and identified ESCA prognostic-related key eRNAs by Kaplan-Meier and co-expression analysis. We also investigated the prognostic role of the key eRNA using a series of bioinformatics approaches, including immune infiltration, immune function, immune subtypes, and the tumor microenvironment. Finally, the tumor immune dysfunction and exclusion (TIDE) score was used to predict the immune response to immune checkpoint blockade (ICB) therapy. We identified eRNA AC005515.1, AC012368.1, AP003469.2, Clorf61, and WDFY3-AS2 were associated with the prognosis of ESCA. AC005515.1 is a critical prognostic-related eRNA in ESCA and was significantly co-expressed with immune checkpoint genes (CTLA4, CD274, etc.). In the pan-cancer analysis, AC005515.1 was also associated with the prognosis of seven cancers, including kidney renal papillary cell carcinoma and low-grade brain glioma. It was also found to be co-expressed with immune checkpoint genes in these tumors. Moreover, high expression of AC005515.1 was associated with CD8+ T cells and M1 macrophages infiltration, and the AC005515.1 high-expression group had a higher TIDE score in ESCA. Overall, eRNA AC005515.1 is associated with the local immune environment of ESCA and may become a new biomarker of ESCA prognosis and immunotherapy response.

Blood proteomics to identify AD CSF molecular subtypes

AbstractBackgroundWe identified three distinct molecular subtypes in Alzheimer’s disease (AD) using cerebrospinal fluid (CSF) proteomics: one subtype was characterised by neuronal hyperplasticity with increased amyloid metabolism, the second subtype was characterised by innate immune activation and the third subtype by a disrupted blood‐brain barrier. Each subtype will likely need specific treatment, but for patient selection CSF proteomics might be impractical. Here we investigated if AD molecular subtypes can also be detected in blood.MethodWe selected from EMIF‐AD MBD 149 individuals with AD across the clinical spectrum who had plasma proteomics as well as a CSF subtype definition available. We compared CSF subtypes on plasma levels using general linear models. We selected a subset of proteins that best predicted AD subtype by trying a random forest classifier on 70% of the patient sample, and computed prediction accuracy statistics on patients that were left out.ResultPlasma levels of 407 (13%) proteins differed between AD subtypes (figure). The plasma profiles specific to AD subtype showed altered levels for corresponding molecular processes: The CSF hyperplasticity subtype (n = 53) showed low plasma levels of 76 proteins associated with neuron development and axon guidance. The CSF innate immune activation subtype (n = 48) showed low plasma levels of 142 proteins related to regulation of immune response. The CSF blood‐brain barrier subtype (n = 48) showed the low plasma levels of 189 proteins associated with blood vessel morphogenesis. The random forest could classify subtypes with an overall accuracy of 77% (range 70%‐85%), and the top 5 contributing proteins were FGF10, CTCF, TCN2, PLXNA1, and EMILIN3.ConclusionIt is possible to detect distinct AD CSF molecular subtypes in blood. The next step is to validate this in independent cohorts, and to test if subtypes are related to different treatment responses.

Classification of distinct osteoarthritis subtypes with different knee joint tissues by gene expression profiles.

Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA. First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the effectiveness of markers. C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients. This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the diagnosis and treatment of OA.

Elucidating Cell Diversity and Functions of Human Brain Borders in Alzheimer’s Disease

AbstractBackgroundEmerging evidence shows that the brain border regions act as a functional neuro‐immune interface to conduct essential immune surveillance and immune defense1. The dysfunction of border immunity contributes to aging, microglial inflammatory response, and neurodegeneration2‐3.MethodWe conducted single nuclei multiome to simultaneously profile gene expression and open chromatin of dissected postmortem human brain borders from aged individuals with and without Alzheimer’s Disease (AD) (n = 32). We further generated border cell models from iPSCs and postmortem leptomeningeal cells to understand the effects of genetic and environmental factors on border cells.ResultWe detect diverse cell types at the brain borders, including unique endothelial, mural, immune, and fibroblast subtypes. Border‐associated macrophages (BAMs) display differential gene expressions from microglia and express AD risk genes, as nominated by genome‐wide association studies (GWAS). We discover cell‐type‐specific differentially expressed genes in AD individuals, particularly fibroblasts and BAMs. We identify gene regulatory networks and master regulators of specific border cell states. Human cell models of leptomeningeal cells display the signature of ex vivo AD fibroblasts upon amyloid‐β treatment, and iPSC‐derived choroid plexus models carrying the APOE4 risk alleles demonstrate differentially expressed genes related to immune and fibrotic response. Lastly, we explore ligand‐receptor interactions within the border niche and observe increased intercellular activities and altered communication patterns at AD brain borders.ConclusionOur study establishes a molecular map of human border cell types and reveals the functional effects of AD risk factors on brain border cells, providing significant insight into the border immune and fibrotic responses in AD pathogenesis.

Tumor-infiltrating immune cell score as an independent prognostic predictor for endometrial carcinoma: Insights from a comprehensive analysis of the immune landscape.

Immune cells are crucial components in the tumor microenvironment and have a significant impact on the outcomes of patients. Here, we aimed to establish a prognostic score based on different types of tumor-infiltrating immune cells for Endometrial Carcinoma (EC). We enrolled and analyzed 516 EC patients from The Cancer Genome Atlas. The relative abundance of 22 immune cells were estimated by using the CIBERSORTx algorithm. Cox regression was performed to identify potential prognostic immune cells, which were used to develop a Tumor-infiltrating Immune Cell Score (TICS). The prognostic and incremental value of TICS for overall survival were compared with traditional prognostic factors using the C-index and decision curves. Clustering analysis using all immune cells identified three immune landscape subtypes, which had weak correlation with survival. A TICS was constructed using CD8T cells, resting memory CD4 T cells, activated NK and activated DCs, and classified patients as low-, moderate- and high-risk subgroups. The low-risk subgroup had higher tumor mutation burden and activation of IL2/STAT5, IL2/STAT3 and IFN-gamma response pathways. Conversely, the high-risk subgroup was associated with DNA copy number variation, hypoxia and EMT process. The TICS subgroups significantly predicted overall survival, which was independent of patient age, tumor stage, grade and molecular classification. Moreover, we developed a nomogram incorporating TICS and clinicopathologic factors, which significantly improved the predictive accuracy compared to the clinicopathologic model alone. The TICS is an effective and independent prognostic predictor for EC patients and may serve as a useful supplement to clinicopathological factors and molecular subtyping.

Identification of Proteome-Based Immune Subtypes of Early Hepatocellular Carcinoma and Analysis of Potential Metabolic Drivers

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, ranking fourth in frequency. The relationship between metabolic reprogramming and immune infiltration has been identified as having a crucial impact on HCC progression. However, a deeper understanding of the interplay between the immune system and metabolism in the HCC microenvironment is required. In this study, we used a proteomic dataset to identify three immune subtypes (IM1-IM3) in HCC, each of which has distinctive clinical, immune, and metabolic characteristics. Among these subtypes, IM3 was found to have the poorest prognosis, with the highest levels of immune infiltration and T-cell exhaustion. Furthermore, IM3 showed elevated glycolysis and reduced bile acid metabolism, which was strongly correlated with CD8 T cell exhaustion and regulatory T cell accumulation. Our study presents the proteomic immune stratification of HCC, revealing the possible link between immune cells and reprogramming of HCC glycolysis and bile acid metabolism, which may be a viable therapeutic strategy to improve HCC immunotherapy.

Treatment-related adverse events, including fatal toxicities, in patients with solid tumours receiving neoadjuvant and adjuvant immune checkpoint blockade: a systematic review and meta-analysis of randomised controlled trials

Incorporating immune checkpoint blockade into perioperative cancer therapy has improved clinical outcomes. However, the safety of immune checkpoint blockade needs better evaluation, given the chances of more prolonged disease-free survival. We aimed to assess how adding immune checkpoint blockade to perioperative therapy affects treatment-related adverse events. For this systematic review and meta-analysis, we searched PubMed/MEDLINE, Embase, Web of Science, and the Cochrane Library from database inception until Aug 8, 2023, for randomised controlled trials that assessed the addition of immune checkpoint blockade to neoadjuvant or adjuvant therapy for cancer, reported treatment-related deaths, and had a design in which the experimental group assessed immune checkpoint blockade in combination with the therapy used in the control group. Meta-analysis was done to pool odds ratios (ORs) of treatment-related deaths, any grade and grade 3-4 treatment-related adverse events, serious adverse events, and adverse events leading to treatment discontinuation. The protocol is registered with PROSPERO, CRD42022343741. 28 randomised controlled trials with 16 976 patients were included. The addition of immune checkpoint blockade was not significantly associated with increased treatment-related deaths (OR 1·76, 95% CI 0·95-3·25; p=0·073), consistent across immune checkpoint blockade subtype (I2=0%). 40 fatal toxicities were identified across 9864 patients treated with immune checkpoint blockade, with pneumonitis being the most common (six [15·0%]); 13 fatal toxicities occurred among 7112 patients who were not treated with immune checkpoint blockade. The addition of immune checkpoint blockade increased the incidence of grade 3-4 treatment-related adverse events (OR 2·73, 95% CI 1·98-3·76; p<0·0001), adverse events leading to treatment discontinuation (3·67, 2·45-5·51; p<0·0001), and treatment-related adverse events of any grade (2·60 [1·88-3·61], p<0·0001). The immune checkpoint blockade versus placebo design primarily used as adjuvant therapy was associated with increased incidence of treatment-related deaths (4·02, 1·04-15·63; p=0·044) and grade 3-4 adverse events (5·31, 3·08-9·15; p<0·0001), whereas the addition of immune checkpoint blockade in the neoadjuvant setting was not associated with increased incidence of treatment-related death (1·11, 95% CI 0·38-3·29; p=0·84) or grade 3-4 adverse events (1·17, 0·90-1·51; p=0·23). The addition of immune checkpoint blockade to perioperative therapy was associated with an increase in grade 3-4 treatment-related adverse events and adverse events leading to treatment discontinuation. These findings provide safety insights for further clinical trials assessing neoadjuvant or adjuvant immune checkpoint blockade therapy. Clinicians should closely monitor patients for treatment-related adverse events to prevent treatment discontinuations and morbidity from these therapies in earlier-stage settings. None.

Revealing Pan-Histology Immunomodulatory Targets in Pediatric Central Nervous System Tumors.

The application of immunotherapy for pediatric CNS malignancies has been limited by the poorly understood immune landscape in this context. The aim of this study was to uncover the mechanisms of immune suppression common among pediatric brain tumors. We apply an immunologic clustering algorithm validated by The Cancer Genome Atlas Project to an independent pediatric CNS transcriptomic dataset. Within the clusters, the mechanisms of immunosuppression are explored via tumor microenvironment deconvolution and survival analyses to identify relevant immunosuppressive genes with translational relevance. High-grade diseases fall predominantly within an immunosuppressive subtype (C4) that independently lowers overall survival time and where common immune checkpoints (e.g., PDL1, CTLA4) are less relevant. Instead, we identify several alternative immunomodulatory targets with relevance across histologic diseases. Specifically, we show how the mechanism of EZH2 inhibition to enhance tumor immunogenicity in vitro via the upregulation of MHC class 1 is applicable to a pediatric CNS oncologic context. Meanwhile, we identify that the C3 (inflammatory) immune subtype is more common in low-grade diseases and find that immune checkpoint inhibition may be an effective way to curb progression for this subset. Three predominant immunologic clusters are identified across pediatric brain tumors. Among high-risk diseases, the predominant immune cluster is associated with recurrent immunomodulatory genes that influence immune infiltrate, including a subset that impacts survival across histologies.

Identification of novel potential homologous repair deficiency-associated genes in pancreatic adenocarcinoma via WGCNA coexpression network analysis and machine learning

ABSTRACT Homologous repair deficiency (HRD) impedes double-strand break repair, which is a common driver of carcinogenesis. Positive HRD status can be used as theranostic markers of response to platinum- and PARP inhibitor-based chemotherapies. Here, we aimed to fully investigate the therapeutic and prognostic potential of HRD in pancreatic adenocarcinoma (PAAD) and identify effective biomarkers related to HRD using comprehensive bioinformatics analysis. The HRD score was defined as the unweighted sum of the LOH, TAI, and LST scores, and it was obtained based on the previous literature. To characterize PAAD immune infiltration subtypes, the “ConsensusClusterPlus” package in R was used to conduct unsupervised clustering. A WGCNA was conducted to elucidate the gene coexpression modules and hub genes in the HRD-related gene module of PAAD. The functional enrichment study was performed using Metascape. LASSO analysis was performed using the “glmnet” package in R, while the random forest algorithm was realized using the “randomForest” package in R. The prognostic variables were evaluated using univariate Cox analysis. The prognostic risk model was built using the LASSO approach. ROC curve and KM survival analyses were performed to assess the prognostic potential of the risk model. The half-maximal inhibitory concentration (IC50) of the PARP inhibitors was estimated using the “pRRophetic” package in R and the Genomics of Drug Sensitivity in Cancer database. The “rms” package in R was used to create the nomogram. A high HRD score indicated a poor prognosis and an advanced clinical process in PAAD patients. PAAD tumors with high HRD levels revealed significant T helper lymphocyte depletion, upregulated levels of cancer stem cells, and increased sensitivity to rucaparib, Olaparib, and veliparib. Using WGCNA, 11 coexpression modules were obtained. The red module and 122 hub genes were identified as the most correlated with HRD in PAAD. Functional enrichment analysis revealed that the 122 hub genes were mainly concentrated in cell cycle pathways. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were screened via LASSO analysis and a random forest algorithm, and they were validated using independent validation sets. No direct association between HRD and CKS1B, HJURP, or TPX2 has not been reported in the literature so far. Thus, these findings indicated that CKS1B, HJURP, and TPX2 have potential as diagnostic and prognostic biomarkers for PAAD. We constructed a novel HRD-related prognostic model that provides new insights into PAAD prognosis and immunotherapy. Based on bioinformatics analysis, we comprehensively explored the therapeutic and prognostic potential of HRD in PAAD. One novel HRD-related gene signature consisting of CKS1B, HJURP, and TPX2 were identified through the combination of WGCNA, LASSO analysis and a random forest algorithm. A novel HRD-related risk model that can predict clinical prognosis and immunotherapeutic response in PAAD patients was constructed.

Pan-cancer analysis of the prognostic significance and oncogenic role of GXYLT2.

Growing evidence supports an oncogenic role for glucoside xylosyltransferase 2 (GXYLT2) in a number of malignancies. To evaluate the prognostic value and oncogenic function of GXYLT2 in diverse cancer types, we analyzed sequencing data from public databases on 33 tumor tissues and their corresponding normal tissues. We found that GXYLT2 was overexpressed in a number of tumors, and that its expression was positively correlated with disease progression and mortality in several major cancer types including stomach adenocarcinoma (STAD). GXYLT2 was also linked to tumor size, grade, and the immune and molecular subtypes of STAD. GO and KEGG pathway analyses of GXYLT2 co-expressed genes in STAD suggested that GXYLT2 possibly plays a role in epithelial-mesenchymal transition, extracellular matrix production and degradation, angiogenesis, apoptosis, as well as in tumor inflammation, such as cytokine production and T cell activation. Finally, prognostic nomograms were created and validated for predicting 1, 3, and 5-year survival of patients with STAD. Our findings indicate that GXYLT2 may play a role in tumorigenesis and tumor immunity, and it may serve as a prognostic marker and potential immunotherapeutic target for STAD and some other types of cancer.

ZNF643/ZFP69B Exerts Oncogenic Properties and Associates with Cell Adhesion and Immune Processes.

The global cancer burden remains high; thus, a better understanding of the molecular mechanisms driving carcinogenesis is needed to improve current prevention and treatment options. We previously detected the ZNF643/ZFP69B gene upregulated in multiple tumors, and we speculated it may play a role in tumor biology. To test this hypothesis, we employed TCGA-centered databases to correlate ZNF643 status with various clinicopathological parameters. We also performed RNA-seq analysis and in vitro studies assessing cancer cell phenotypes, and we searched for ZNF643-bound genomic loci. Our data indicated higher levels of ZNF643 in most analyzed tumors compared to normal samples, possibly due to copy number variations. ZNF643 mRNA correlated with diverse molecular and immune subtypes and clinicopathological features (tumor stage, grade, patient survival). RNA-seq analysis revealed that ZNF643 silencing triggers the deregulation of the genes implicated in various cancer-related processes, such as growth, adhesion, and immune system. Moreover, we observed that ZNF643 positively influences cell cycle, migration, and invasion. Finally, our ChIP-seq analysis indicated that the genes associated with ZNF643 binding are linked to adhesion and immune signaling. In conclusion, our data confirm the oncogenic properties of ZNF643 and pinpoint its impact on cell adhesion and immune processes.

Single cell dynamics of tumor specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer

CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of immunotherapy against microsatellite stable (MSS) CRC is limited. Little is known about the most critical features of CRC CD8+ T cells that together determine the diverse immune landscapes and contrasting ICB responses. Hence, we pursued a deep single cell mapping of CRC CD8+ T cells on transcriptomic and T cell receptor (TCR) repertoire levels in a diverse patient cohort, with additional surface proteome validation. This revealed that CRC CD8+ T cell dynamics are underscored by complex interactions between interferon-γ signaling, tumor reactivity, TCR repertoire, (predicted) TCR antigen-specificities, and environmental cues like gut microbiome or colon tissue-specific ‘self-like’ features. MSI CRC CD8+ T cells showed tumor-specific activation reminiscent of canonical ‘T cell hot’ tumors, whereas the MSS CRC CD8+ T cells exhibited tumor unspecific or bystander-like features. This was accompanied by inflammation reminiscent of ‘pseudo-T cell hot’ tumors. Consequently, MSI and MSS CRC CD8+ T cells showed overlapping phenotypic features that differed dramatically in their TCR antigen-specificities. Given their high discriminating potential for CD8+ T cell features/specificities, we used the single cell tumor-reactive signaling modules in CD8+ T cells to build a bulk tumor transcriptome classification for CRC patients. This “Immune Subtype Classification” (ISC) successfully distinguished various tumoral immune landscapes that showed prognostic value and predicted immunotherapy responses in CRC patients. Thus, we deliver a unique map of CRC CD8+ T cells that drives a novel tumor immune landscape classification, with relevance for immunotherapy decision-making.