The Expression and Prognostic Impact of Immune Cytolytic Activity-Related Markers in Human Malignancies: A Comprehensive Meta-analysis

Differential role of glucocorticoid receptor based on its cell type specific expression on tumor cells and infiltrating lymphocytes

BACKGROUND

The glucocorticoid receptor (GR) is frequently expressed in breast cancer (BC), and its prognostic implications are contingent on estrogen receptor (ER) status. To address conflicting reports and explore therapeutic potential, a GR signature (GRsig) independent of ER status was developed. We also investigated cell type-specific GR protein expression in BC tumor epithelial cells and infiltrating lymphocytes.

METHODS

GRsig was derived from Dexamethasone treated cell lines through a bioinformatic pipeline. Immunohistochemistry assessed GR protein expression. Associations between GRsig and tumor phenotypes (proliferation, cytolytic activity (CYT), immune cell distribution, and epithelial-to-mesenchymal transition (EMT) were explored in public datasets. Single-cell RNA sequencing data evaluated context-dependent GR roles, and a cell type-specific prognostic role was assessed in an independent BC cohort.

RESULTS

High GRsig levels were associated with a favorable prognosis across BC subtypes. Tumor-specific high GRsig correlated with lower proliferation, increased CYT, and anti-tumorigenic immune cells. Single-cell data analysis revealed higher GRsig expression in immune cells, negatively correlating with EMT while a positive correlation was observed with EMT primarily in tumor and stromal cells. Univariate and multivariate analyses demonstrated the robust and independent predictive capability of GRsig for favorable prognosis. GR protein expression on immune cells in triple-negative tumors indicated a favorable prognosis.

CONCLUSION

This study underscores the cell type-specific role of GR, where its expression on tumor cells is associated with aggressive features like EMT, while in infiltrating lymphocytes, it predicts a better prognosis, particularly within TNBC tumors. The GRsig emerges as a promising independent prognostic indicator across diverse BC subtypes.

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.

Unlocking the Potential of Therapy-Induced Cytokine Responses: Illuminating New Pathways in Cancer Precision Medicine

Precision cancer medicine primarily aims to identify individual patient genomic variations and exploit vulnerabilities in cancer cells to select suitable patients for specific drugs. These genomic features are commonly determined by gene sequencing prior to therapy, to identify individuals who would be most responsive. This precision approach in cancer therapeutics remains a powerful tool that benefits a smaller pool of patients, sparing others from unnecessary treatments. A limitation of this approach is that proteins, not genes, are the ultimate effectors of biological functions, and therefore the targets of therapeutics. An additional dimension in precision medicine that considers an individual's cytokine response to cancer therapeutics is proposed. Cytokine responses to therapy are multifactorial and vary among individuals. Thus, precision is dictated by the nature and magnitude of cytokine responses in the tumor microenvironment exposed to therapy. This review highlights cytokine responses as modules for precision medicine in cancer therapy, including potential challenges. For solid tumors, both detectability of cytokines in tissue fluids and their being amenable to routine sensitive analyses could address the difficulty of specimen collection for diagnosis and monitoring. Therefore, in precision cancer medicine, cytokines offer rational targets that can be utilized to enhance the efficacy of cancer therapy.

Identification and validation of a dysregulated TME-related gene signature for predicting prognosis, and immunological properties in bladder cancer

Background

During tumor growth, tumor cells interact with their tumor microenvironment (TME) resulting in the development of heterogeneous tumors that promote tumor occurrence and progression. Recently, there has been extensive attention on TME as a possible therapeutic target for cancers. However, an accurate TME-related prediction model is urgently needed to aid in the assessment of patients' prognoses and therapeutic value, and to assist in clinical decision-making. As such, this study aimed to develop and validate a new prognostic model based on TME-associated genes for BC patients.

Methods

Transcriptome data and clinical information for BC patients were extracted from The Cancer Genome Atlas (TCGA) database. Gene Expression Omnibus (GEO) and IMvigor210 databases, along with the MSigDB, were utilized to identify genes associated with TMEs (TMRGs). A consensus clustering approach was used to identify molecular clusters associated with TMEs. LASSO Cox regression analysis was conducted to establish a prognostic TMRG-related signature, with verifications being successfully conducted internally and externally. Gene ontology (GO), KEGG, and single-sample gene set enrichment analyses (ssGSEA) were performed to investigate the underlying mechanisms. The potential response to ICB therapy was estimated using the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and Immunophenoscore (IPS). Additionally, it was found that the expression level of certain genes in the model was significantly correlated with objective responses to anti-PD-1 or anti-PD-L1 treatment in the IMvigor210, GSE111636, GSE176307, or Truce01 (registration number NCT04730219) cohorts. Finally, real-time PCR validation was performed on 10 paired tissue samples, and in vitro cytological experiments were also conducted on BC cell lines.

Results

In BC patients, 133 genes differentially expressed that were associated with prognosis in TME. Consensus clustering analysis revealed three distinct clinicopathological characteristics and survival outcomes. A novel prognostic model based on nine TMRGs (including C3orf62, DPYSL2, GZMA, SERPINB3, RHCG, PTPRR, STMN3, TMPRSS4, COMP) was identified, and a TMEscore for OS prediction was constructed, with its reliable predictive performance in BC patients being validated. MultiCox analysis showed that the risk score was an independent prognostic factor. A nomogram was developed to facilitate the clinical viability of TMEscore. Based on GO and KEGG enrichment analyses, biological processes related to ECM and collagen binding were significantly enriched among high-risk individuals. In addition, the low-risk group, characterized by a higher number of infiltrating CD8+ T cells and a lower burden of tumor mutations, demonstrated a longer survival time. Our study also found that TMEscore correlated with drug susceptibility, immune cell infiltration, and the prediction of immunotherapy efficacy. Lastly, we identified SERPINB3 as significantly promoting BC cells migration and invasion through differential expression validation and in vitro phenotypic experiments.

Conclusion

Our study developed a prognostic model based on nine TMRGs that accurately and stably predicted survival, guiding individual treatment for patients with BC, and providing new therapeutic strategies for the disease.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and immunotherapy response in bladder cancer

BACKGROUND

T cells have been proven to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in bladder cancer (BLCA).

METHODS

Single-cell RNA-sequencing (scRNA-seq) data were downloaded from the gene expression omnibus (GEO) database to screen T-cell marker genes. Bulk RNA-sequencing data and clinical information from BLCA patients were downloaded from the cancer genome atlas (TCGA) database to develop a prognosis signature. We analyzed the association of different risk groups with survival analysis, gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and immunotherapy response.

RESULTS

Based on 192 T-cell marker genes identified by scRNA-seq analysis, we constructed a prognostic signature containing 7 genes in the training cohort, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5 years were 0.734, 0.742 and 0.726 in the training cohort, 0.697, 0.671 and 0.670 in the testing cohort, 0.702, 0.665 and 0.629 in the GEO cohort, respectively. In addition, we constructed a nomogram based on clinical factors and the risk score of the signature. The low-risk group exhibited higher immune-related pathways, immune cell infiltration and TMB levels. Importantly, immunophenotype score and immunotherapy cohort (IMvigor210) analyses showed that the low-risk group had better immunotherapy response and prognosis.

CONCLUSIONS

Our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for BLCA patients.

Human lymphocytes mobilized with exercise have an anti-tumor transcriptomic profile and exert enhanced graft-versus-leukemia effects in xenogeneic mice

Background

Every bout of exercise mobilizes and redistributes large numbers of effector lymphocytes with a cytotoxic and tissue migration phenotype. The frequent redistribution of these cells is purported to increase immune surveillance and play a mechanistic role in reducing cancer risk and slowing tumor progression in physically active cancer survivors. Our aim was to provide the first detailed single cell transcriptomic analysis of exercise-mobilized lymphocytes and test their effectiveness as a donor lymphocyte infusion (DLI) in xenogeneic mice engrafted with human leukemia.

Methods

Peripheral blood mononuclear cells (PBMCs) were collected from healthy volunteers at rest and at the end of an acute bout of cycling exercise. Flow cytometry and single-cell RNA sequencing was performed to identify phenotypic and transcriptomic differences between resting and exercise-mobilized cells using a targeted gene expression panel curated for human immunology. PBMCs were injected into the tail vein of xenogeneic NSG-IL-15 mice and subsequently challenged with a luciferase tagged chronic myelogenous leukemia cell line (K562). Tumor growth (bioluminescence) and xenogeneic graft-versus-host disease (GvHD) were monitored bi-weekly for 40-days.

Results

Exercise preferentially mobilized NK-cell, CD8+ T-cell and monocyte subtypes with a differentiated and effector phenotype, without significantly mobilizing CD4+ regulatory T-cells. Mobilized effector lymphocytes, particularly effector-memory CD8+ T-cells and NK-cells, displayed differentially expressed genes and enriched gene sets associated with anti-tumor activity, including cytotoxicity, migration/chemotaxis, antigen binding, cytokine responsiveness and alloreactivity (e.g. graft-versus-host/leukemia). Mice receiving exercise-mobilized PBMCs had lower tumor burden and higher overall survival (4.14E+08 photons/s and 47%, respectively) at day 40 compared to mice receiving resting PBMCs (12.1E+08 photons/s and 22%, respectively) from the same donors (p<0.05). Human immune cell engraftment was similar for resting and exercise-mobilized DLI. However, when compared to non-tumor bearing mice, K562 increased the expansion of NK-cell and CD3+/CD4-/CD8- T-cells in mice receiving exercise-mobilized but not resting lymphocytes, 1-2 weeks after DLI. No differences in GvHD or GvHD-free survival was observed between groups either with or without K562 challenge.

Conclusion

Exercise in humans mobilizes effector lymphocytes with an anti-tumor transcriptomic profile and their use as DLI extends survival and enhances the graft-versus-leukemia (GvL) effect without exacerbating GvHD in human leukemia bearing xenogeneic mice. Exercise may serve as an effective and economical adjuvant to increase the GvL effects of allogeneic cell therapies without intensifying GvHD.

Mass Spectrometry-Based Biomarkers to Detect Prostate Cancer: A Multicentric Study Based on Non-Invasive Urine Collection without Prior Digital Rectal Examination

(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.

Genome-Wide Analysis of lncRNA-mRNA Co-Expression Networks in CD133+/CD44+ Stem-like PDAC Cells

Pancreatic ductal adenocarcinoma (PDAC), the second most prevalent gastrointestinal malignancy and the most common type of pancreatic cancer is linked with poor prognosis and, eventually, with high mortality rates. Early detection is seldom, while tumor heterogeneity and microarchitectural alterations benefit PDAC resistance to conventional therapeutics. Although emerging evidence suggest the core role of cancer stem cells (CSCs) in PDAC aggressiveness, unique stem signatures are poorly available, thus limiting the efforts of anti-CSC-targeted therapy. Herein, we report the findings of the first genome-wide analyses of mRNA/lncRNA transcriptome profiling and co-expression networks in PDAC cell line-derived CD133+/CD44+ cells, which were shown to bear a CSC-like phenotype in vitro and in vivo. Compared to CD133-/CD44- cells, the CD133+/CD44+ population demonstrated significant expression differences in both transcript pools. Using emerging bioinformatic tools, we performed lncRNA target coding gene prediction analysis, which revealed significant Gene Ontology (GO), pathway, and network enrichments in many dyregulated lncRNA nearby (cis or trans) mRNAs, with reported involvement in the regulation of CSC phenotype and functions. In this context, the construction of lncRNA/mRNA networks by ingenuity platforms identified the lncRNAs ATF2, CHEK1, DCAF8, and PAX8 to interact with "hub" SC-associated mRNAs. In addition, the expressions of the above lncRNAs retrieved by TCGA-normalized RNAseq gene expression data of PAAD were significantly correlated with clinicopathological features of PDAC, including tumor grade and stage, nodal metastasis, and overall survival. Overall, our findings shed light on the identification of CSC-specific lncRNA signatures with potential prognostic and therapeutic significance in PDAC.

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas

Background

Immunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG).

Materials and methods

We identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation.

Results

32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells.

Conclusion

We established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy.

Ras suppressor 1 long form (RSU1L) silencing promotes apoptosis in invasive breast cancer cells

Ras Suppressor-1 (RSU1) is a cell-extracellular matrix (ECM) adhesion protein implicated in breast cancer (BC) cell metastasis. Nevertheless, its role in apoptosis is yet unknown. In the present study, we used bioinformatics tools to evaluate the association of RSU1 expression and BC patient survival, the expression of basic pro- and anti-apoptotic genes in metastatic BC samples and their correlation with the expression of RSU1. Then, we specifically depleted RSU1 long form (RSU1L) using a short hairpin RNA (shRNA) silencing approach in two BC cell lines, the non-invasive MCF-7 and the highly invasive MDA-MB-231-LM2 cells and assessed gene expression of pro-and anti-apoptotic genes, as well as cell survival and apoptosis. Our results showed that high RSU1 expression was correlated with poor survival and significant changes were found in the expression of apoptosis-related genes (PUMA, TP53, BCL-2 and BCL-XL) in metastatic BC. Moreover, silencing of the long and most common isoform of RSU1 (RSU1L) resulted in the upregulation of PUMA and TP53 and concomitant downregulation of anti-apoptotic BCL-2 and BCL-XL, with the effect being more prominent in invasive MDA-MB-231-LM2 cells. Finally, RSU1L depletion leads to a dramatic increase in apoptosis of MDA-MB-231-LM2 cells, while no change was observed in the apoptotic rate of MCF-7 cells. This is the first study linking RSU1L with apoptosis and provides evidence for its differential role in cell lines of different invasive potential. This indicates that RSU1L represses apoptosis in aggressive BC cells helping them evade cell death and survive.

TCR CDR3-antigen chemical complementarity associated with poor ovarian cancer outcomes: A vestigial immune response to early cancer antigens?

Ovarian cancer continues to present significant challenges for early detection and treatment, indicating a need for novel approaches to improve disease outcomes. In this report, we applied a previously described algorithm for detecting chemical complementarity between candidate cancer antigens and complementarity determining region-3 (CDR3) amino acid sequences from tumor resident T-cell receptors. Current literature indicates an association between high CDR3-cancer antigen complementarity and improved survival outcomes. For example, high CDR3-BRAF electrostatic complementarity is associated with a better melanoma outcome. However, such CDR3-cancer antigen chemical complementarity in ovarian cancer was largely associated with worse outcomes. Specifically, high CDR3-MAGEB4 and CDR3-TDRD1 electrostatic complementarity was associated with lower ovarian cancer disease free survival (DFS). Additionally, high CDR3-MAGEB4 and CDR3-TDRD1 electrostatic complementarity was associated with decreased MAGEB4/TDRD1 gene expression and gene copy numbers, consistent with a selection against ovarian cancer cells expressing these antigens. However, when TDRD1 was split into fragments, high CDR3-TDRD1 hydrophobicity complementarity, for a specific TDRD1 fragment, was associated with increased DFS and higher immune marker expression levels. This dichotomy highlights the myriad of opportunities to establish risk stratifications and to identify potential, actionable cancer antigens using immunogenomic parameters.

Genomic landscape of the immunogenicity regulation in skin melanomas with diverse tumor mutation burden

Skin melanoma cells are tightly interconnected with their tumor microenvironment (TME), which influences their initiation, progression, and sensitivity/resistance to therapeutic interventions. An immune-active TME favors patient response to immune checkpoint inhibition (ICI), but not all patients respond to therapy. Here, we assessed differential gene expression in primary and metastatic tumors from the TCGA-SKCM dataset, compared to normal skin samples from the GTEx project and validated key findings across 4 independent GEO datasets, as well as using immunohistochemistry in independent patient cohorts. We focused our attention on examining the expression of various immune receptors, immune-cell fractions, immune-related signatures and mutational signatures across cutaneous melanomas with diverse tumor mutation burdens (TMB). Globally, the expression of most immunoreceptors correlated with patient survival, but did not differ between TMBhigh and TMBlow tumors. Melanomas were enriched in "naive T-cell", "effector memory T-cell", "exhausted T-cell", "resting Treg T-cell" and "Th1-like" signatures, irrespective of their BRAF, NF1 or RAS mutational status. Somatic mutations in IDO1 and HLA-DRA were frequent and could be involved in hindering patient response to ICI therapies. We finally analyzed transcriptome profiles of ICI-treated patients and associated their response with high levels of IFNγ, Merck18, CD274, CD8, and low levels of myeloid-derived suppressor cells (MDSCs), cancer-associated fibroblasts (CAFs) and M2 macrophages, irrespective of their TMB status. Overall, our findings highlight the importance of pre-existing T-cell immunity in ICI therapeutic outcomes in skin melanoma and suggest that TMBlow patients could also benefit from such therapies.

Heterogeneity and Differentiation Trajectories of Infiltrating CD8+ T Cells in Lung Adenocarcinoma

Simple Summary

CD8+ T cells infiltrating the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) play a crucial role in establishing anti-tumor immunotherapy. The number of CD8+ T cells affects the treatment response, but their functional status plays a more critical role, and this global landscape is still unclear. We divided CD8+ T cells into ten subsets by analyzing a LUAD single-cell dataset. The dynamic process of cell differentiation and functional exhaustion of CD8+ T cells was further discussed, and potential biomarkers in this process were screened. This study deepens the understanding of the heterogeneity of infiltrating CD8+ T cells in LUAD, and the prognostic marker provides a new target for targeted therapy and immunotherapy in LUAD patients.

Abstract

CD8+ T cells infiltrating the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) are critical for establishing antitumor immunity. Nevertheless, the global landscape of their numbers, functional status, and differentiation trajectories remains unclear. In the single-cell RNA-sequencing (scRNA-seq) dataset GSE131907 of LUAD, the CD8+T cells were selected for TSNE clustering, and the results showed that they could be divided into ten subsets. The cell differentiation trajectory showed the presence of abundant transition-state CD8+ T cells during the differentiation of naive-like CD8+ T cells into cytotoxic CD8+ T cells and exhausted CD8+ T cells. The differentially expressed marker genes among subsets were used to construct the gene signature matrix, and the proportion of each subset was identified and calculated in The Cancer Genome Atlas (TCGA) samples. Survival analysis showed that the higher the proportion of the exhausted CD8+ T lymphocyte (ETL) subset, the shorter the overall survival (OS) time of LUAD patients (p = 0.0098). A total of 61 genes were obtained by intersecting the differentially expressed genes (DEGs) of the ETL subset, and the DEGs of the TCGA samples were divided into a high and a low group according to the proportion of the ETL subset. Through protein interaction network analysis and survival analysis, four hub genes that can significantly affect the prognosis of LUAD patients were finally screened, and RT-qPCR and Western blot verified the differential expression of the above four genes. Our study further deepens the understanding of the heterogeneity and functional exhaustion of infiltrating CD8+ T cells in LUAD. The screened prognostic marker genes provide potential targets for targeted therapy and immunotherapy in LUAD patients.

The Role of RKIP in the Regulation of EMT in the Tumor Microenvironment

Simple Summary

Raf kinase inhibitor protein (RKIP) expression in cancer cells is significantly reduced and promoting cancer cells growth and invasiveness. Overexpresssion of RKIP has been reported to mediate pleiotropic anti-cancer activities including the inhibition of survival signaling pathways, sensitization to cell death by cytotoxic drugs, inhibition of invasion, EMT and metastasis. The molecular mechanism by which RKIP inhibits EMT is not clear. In this review, we have examined how RKIP inhibits the selected EMT gene products (Snail, vimentin, N-cadherin, laminin alpha) and found that it involves signaling cross-talks between RKIP and each of the EMT gene products. These findings were validated by bioinformatic analyses demonstrating in various human cancers a negative correlation between the expression of RKIP and the expression of the EMT gene products. These findings suggest that targeting RKIP induction in cancer cells will result in multiple hits by inhibiting tumor growth, metastasis and reversal of chemo-immuno resistance.

Abstract

The Raf Kinase Inhibitor Protein (RKIP) is a unique gene product that directly inhibits the Raf/Mek/Erk and NF-kB pathways in cancer cells and resulting in the inhibition of cell proliferation, viability, EMT, and metastasis. Additionally, RKIP is involved in the regulation of cancer cell resistance to both chemotherapy and immunotherapy. The low expression of RKIP expression in many cancer types is responsible, in part, for the pathogenesis of cancer and its multiple properties. The inhibition of EMT and metastasis by RKIP led to its classification as a tumor suppressor. However, the mechanism by which RKIP mediates its inhibitory effects on EMT and metastases was not clear. We have proposed that one mechanism involves the negative regulation by RKIP of the expression of various gene products that mediate the mesenchymal phenotype as well as the positive regulation of gene products that mediate the epithelial phenotype via signaling cross talks between RKIP and each gene product. We examined several EMT mesenchymal gene products such as Snail, vimentin, N-cadherin, laminin and EPCAM and epithelial gene products such as E-cadherin and laminin. We have found that indeed these negative and positive correlations were detected in the signaling cross-talks. In addition, we have also examined bioinformatic data sets on different human cancers and the findings corroborated, in large part, the findings observed in the signaling cross-talks with few exceptions in some cancer types. The overall findings support the underlying mechanism by which the tumor suppressor RKIP regulates the expression of gene products involved in EMT and metastasis. Hence, the development of agent that can selectively induce RKIP expression in cancers with low expressions should result in the activation of the pleiotropic anti-cancer activities of RKIP and resulting in multiple effects including inhibition of tumor cell proliferation, EMT, metastasis and sensitization of resistant tumor cells to respond to both chemotherapeutics and immunotherapeutics.

Immunomodulatory Factor TIM3 of Cytolytic Active Genes Affected the Survival and Prognosis of Lung Adenocarcinoma Patients by Multi-Omics Analysis

[Objective] Using multi-omics research methods to explore cytolytic activity-related genes through the immunoregulatory factors HAVCR2 (TIM3) affecting the survival and prognosis of lung adenocarcinoma. [Methods] We combined Cox single factor regression and lasso regression feature selection algorithm to screen out the key genes of cytolytic activity in lung adenocarcinoma, and applied multi-omics research to explore the clinical predictive value of the model, including onset risk, independent prognosis, clinical relevance, signal transduction pathways, drug sensitivity, and the correlation of immune regulatory factors, etc. TCGA data are used as the experimental group, and GEO data is used as the external data control group to verify the stability of the model. The survival curve was generated by the Kaplan–Meier method and compared by log-rank, and the Cox proportional hazard model was used for multivariate analysis. In this study, 10 fresh tissue samples of lung adenocarcinoma were collected for cellular immunohistochemical experiments to analyze the expression of immunoregulatory factors in cancer tissues, and the key immunoregulatory factors were verified and screened out. [Results] A total of 450 genes related to cytolytic activity were differentially expressed, of which 273 genes were up-regulated and 177 genes were down-regulated. A total of 91 key genes related to cytolytic activity related to the prognosis of lung adenocarcinoma were screened through Cox single factor regression. The ROC curve results showed that the AUC values of 1, 3, and 5 years in the training set and test set were all greater than 0.7, indicating that the model has a valid verification. The level of risk score is significantly related to the sensitivity of patients to AKT inhibitor VIII, Lenalidomide, and Tipifarnib. In addition, our study also found that receptor and MHC genes related to immunomodulatory, and chemokines, including HAVCR2, are more highly expressed in the low-risk group. [Conclusions] HAVCR2 (TIM3) immunoregulatory factors affect the expression of key genes that affect cytolytic activity in lung adenocarcinoma cells, and to some extent indirectly affect the survival and prognosis of patients with lung adenocarcinoma.

Novel amino acid metabolism‐related gene signature to predict prognosis in clear cell renal cell carcinoma

Background: Amino acid metabolism (AAM) deregulation, an emerging metabolic hallmark of malignancy, plays an essential role in tumour proliferation, invasion, and metastasis. However, the expression of AAM-related genes and their correlation with prognosis in clear cell renal cell carcinoma (ccRCC) remain elusive. This study aims to develop a novel consensus signature based on the AAM-related genes.

Methods: The RNA-seq expression data and clinical information for ccRCC were downloaded from the TCGA (KIRC as training dataset) and ArrayExpress (E-MTAB-1980 as validation dataset) databases. The AAM‐related differentially expressed genes were screened via the “limma” package in TCGA cohorts for further analysis. The machine learning algorithms (Lasso and stepwise Cox (direction = both)) were then utilised to establish a novel consensus signature in TCGA cohorts, which was validated by the E-MTAB-1980 cohorts. The optimal cutoff value determined by the “survminer” package was used to categorise patients into two risk categories. The Kaplan-Meier curve, the receiver operating characteristic (ROC) curve, and multivariate Cox regression were utilised to evaluate the prognostic value. The nomogram based on the gene signature was constructed, and its performance was analysed using ROC and calibration curves. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted on its potential mechanisms. The relationship between the gene signature and key immune checkpoint, N6-methyladenosine (m⁶A)-related genes, and sensitivity to chemotherapy was assessed.

Results: A novel consensus AMM‐related gene signature consisting of IYD, NNMT, ACADSB, GLDC, and PSAT1 is developed to predict prognosis in TCGA cohorts. Kaplan-Meier survival shows that overall survival in the high-risk group was more dismal than in the low-risk group in the TCGA cohort, validated by the E-MTAB-1980 cohort. Multivariate regression analysis also demonstrates that the gene signature is an independent predictor of ccRCC. Immune infiltration analysis highlighted that the high-risk group indicates an immunosuppressive microenvironment. It is also closely related to the level of key immune checkpoints, m⁶A modification, and sensitivity to chemotherapy drugs.

Conclusion: In this study, a novel consensus AAM-related gene signature is developed and validated as an independent predictor to robustly predict the overall survival from ccRCC, which would further improve the clinical outcomes.

A Novel Computational Framework for Predicting the Survival of Cancer Patients With PD-1/PD-L1 Checkpoint Blockade Therapy

Background

Immune checkpoint inhibitors (ICIs) induce durable responses, but only a minority of patients achieve clinical benefits. The development of gene expression profiling of tumor transcriptomes has enabled identifying prognostic gene expression signatures and patient selection with targeted therapies.

Methods

Immune exclusion score (IES) was built by elastic net-penalized Cox proportional hazards (PHs) model in the discovery cohort and validated via four independent cohorts. The survival differences between the two groups were compared using Kaplan-Meier analysis. Both GO and KEGG analyses were performed for functional annotation. CIBERSORTx was also performed to estimate the relative proportion of immune-cell types.

Results

A fifteen-genes immune exclusion score (IES) was developed in the discovery cohort of 65 patients treated with anti-PD-(L)1 therapy. The ROC efficiencies of 1- and 3- year prognosis were 0.842 and 0.82, respectively. Patients with low IES showed a longer PFS (p=0.003) and better response rate (ORR: 43.8% vs 18.2%, p=0.03). We found that patients with low IES enriched with high expression of immune eliminated cell genes, such as CD8+ T cells, CD4+ T cells, NK cells and B cells. IES was positively correlated with other immune exclusion signatures. Furthermore, IES was successfully validated in four independent cohorts (Riaz’s SKCM, Liu’s SKCM, Nathanson’s SKCM and Braun’s ccRCC, n = 367). IES was also negatively correlated with T cell–inflamed signature and independent of TMB.

Conclusions

This novel IES model encompassing immune-related biomarkers might serve as a promising tool for the prognostic prediction of immunotherapy.

The Role of Cancer-Associated Fibroblasts in Ovarian Cancer

Simple Summary

Ovarian cancer is a lethal gynecologic tumor and is generally resistant to conventional treatments. Stable cancer-associated fibroblasts (CAFs) are important cellular components in the ovarian cancer tumor microenvironment and may provide novel resources for future treatment strategies. Different subtypes of CAFs display specific functions in tumor pathogenesis and various CAF markers suggest potential treatment targets. Several clinical or preclinical trials have targeted stromal fibroblasts and focused on the properties of CAFs to enhance ovarian cancer treatment efficacy. This review concentrates on the origins, subtypes, and activation of CAFs, as well as specific roles of CAFs in regulating tumor development and drug resistance, and aims to provide potential and prospective targets for improving the therapeutic efficacy of ovarian cancer treatment.

Abstract

Ovarian cancer is a lethal gynecologic tumor and is generally resistant to conventional treatments. Stable cancer-associated fibroblasts (CAFs) are important cellular components in the ovarian cancer tumor microenvironment and may provide novel resources for future treatment strategies. Different subtypes of CAFs display specific functions in tumor pathogenesis and various CAF markers suggest potential treatment targets, such as FAP and GPR77. Both autocrine and paracrine cytokines play important roles in the CAF activation process and regulate tumor progression. Downstream mediators and pathways, including IL-6, TGF-β, NF-κB, mitogen-activated protein kinase (MAPK), and AKT/mTOR/(p70S6K), play important roles in the initiation, proliferation, invasiveness, and metastasis of ovarian cancer cells and also participate in angiogenesis, therapeutic resistance, and other biological processes. Several clinical or preclinical trials have targeted stromal fibroblasts and focused on the properties of CAFs to enhance ovarian cancer treatment outcomes. This review concentrates on the origins, subtypes, and activation of CAFs, as well as specific roles of CAFs in regulating tumor development and drug resistance, and aims to provide potential and prospective targets for improving the therapeutic efficacy of ovarian cancer treatment.

An RNA-binding protein-related risk signature can predict the prognosis and tumor immunity of patients with testicular germ cell tumors

BACKGROUND

The functions of RNA-binding proteins (RBPs) in the occurrence and development of tumors remain largely unexplored. We established a risk signature based on RBPs to predict the prognosis, tumor-related immunity, and treatment benefits of patients with testicular germ cell tumors (TGCTs).

METHODS

A risk signature was built based on RBPs closely related to survival obtained from TGCT data in The Cancer Genome Atlas (TCGA) database. The ability of the signature to predict prognosis was analyzed by survival curves and Cox regression. The risk signature was validated using the Gene Expression Omnibus (GEO) database. The connection between tumor immunity and the risk score was evaluated. Risk score-related drug sensitivity and biofunctions were also explored.

RESULTS

A risk signature including four selected RBP genes (PARP12, USB1, POLR2E and EED) was established. The prognosis of high-risk TGCT patients was worse than that of low-risk TGCT patients. The risk score was considered a critical factor closely related to prognosis, as determined via Cox regression, and was also closely associated with multiple characteristics of tumor immunity, chemotherapy drugs and biofunctions.

CONCLUSION

The established risk signature including four selected RBPs in TGCTs could predict the prognosis, tumor-related immunity and treatment benefits of patients with TGCTs. Utilization of this signature could help clinicians make personalized treatment decisions.

APOLLO: An accurate and independently validated prediction model of lower-grade gliomas overall survival and a comparative study of model performance

BACKGROUND

Virtually few accurate and robust prediction models of lower-grade gliomas (LGG) survival exist that may aid physicians in making clinical decisions. We aimed to develop a prognostic prediction model of LGG by incorporating demographic, clinical and transcriptional biomarkers with either main effects or gene-gene interactions.

METHODS

Based on gene expression profiles of 1,420 LGG patients from six independent cohorts comprising both European and Asian populations, we proposed a 3-D analysis strategy to develop and validate an Accurate Prediction mOdel of Lower-grade gLiomas Overall survival (APOLLO). We further conducted decision curve analysis to assess the net benefit (NB) of identifying true positives and the net reduction (NR) of unnecessary interventions. Finally, we compared the performance of APOLLO and the existing prediction models by the first systematic review.

FINDINGS

APOLLO possessed an excellent discriminative ability to identify patients at high mortality risk. Compared to those with less than the 20th percentile of APOLLO risk score, patients with more than the 90th percentile of APOLLO risk score had significantly worse overall survival (HR=54·18, 95% CI: 34·73-84·52, P=2·66 × 10-69). Further, APOLLO can accurately predict both 36- and 60-month survival in six independent cohorts with a pooled AUC36-month=0·901 (95% CI: 0·879-0·923), AUC60-month=0·843 (95% CI: 0·815-0·871) and C-index=0·818 (95% CI: 0·800-0·835). Moreover, APOLLO offered an effective screening strategy for detecting LGG patients susceptible to death (NB36-month=0·166, NR36-month=40·1% and NB60-month=0·258, NR60-month=19·2%). The systematic comparisons revealed APOLLO outperformed the existing models in accuracy and robustness.

INTERPRETATION

APOLLO has the demonstrated feasibility and utility of predicting LGG survival (http://bigdata.njmu.edu.cn/APOLLO).

FUNDING

National Key Research and Development Program of China (2016YFE0204900); Natural Science Foundation of Jiangsu Province (BK20191354); National Natural Science Foundation of China (81973142 and 82103946); China Postdoctoral Science Foundation (2020M681671); National Institutes of Health (CA209414, CA249096, CA092824 and ES000002).

A pancancer analysis of the carcinogenic role of receptor-interacting serine/threonine protein kinase-2 (RIPK2) in human tumours

Background

To explore the expression and carcinogenic mechanism of RIPK2 in human tumours, and to provide the theoretical basis for the further study of RIPK2.

Methods

We used the TCGA, CPTAC, HPA databases to analyse the expression, mutation, and prognosis of RIPK2 in human tumours. Through the Cbioportal, Ualcan, TIMER2.0, and STRING websites, We understand the genetic variation, immune infiltration and enrichment analysis of RIPK2 related genes.

Results

RIPK2 was highly expressed in most tumours (such as BRCA, COAD and LUSC, etc.), and the high expression of RIPK2 was correlated with tumour stage and prognosis. In addition, Amplification was the main type of RIPK2 in tumour mutation state, and the amplification rate was about 8.5%. In addition, RIPK2 was positively associated with tumour-infiltrating immune cells (such as CD8+ T, Tregs, and cancer-associated fibroblasts). According to the KEGG analysis, RIPK2 may play a role in tumour mainly through NOD-like signaling pathway and NF-kappaB signaling pathway. GO enrichment analysis showed that the RIPK2 is mainly related to I-kappaB kinase/NF-kappaB signaling, Ribonucleoprotein granule and Ubiquitin-like protein ligase binding.

Conclusion

RIPK2 plays an important role in the occurrence, development and prognosis of malignant tumours. Our pancancer study provided a relatively comprehensive description of the carcinogenic effects of RIPK2 in different tumours, and provided useful information for further study of RIPK2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01239-3.

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.

Survival Genie, a web platform for survival analysis across pediatric and adult cancers

The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan–Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile. The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/.

Omics analysis of uveal melanoma: Leukocyte gene signatures reveal novel survival distinctions and indicate a prognostic role for cytolytic activity scoring

Objective

The significant metastatic potential of uveal melanoma (UVM) lends to high mortality. Even with successful local tumor treatment, many patients will develop metastatic disease. The present study aims to elucidate the relationship between tumor-infiltrating immune cell (TIIC) diversity and survival to identify potential therapeutic targets and improve UVM prognosis.

Methods

Bulk deconvolution was used to determine the relative proportions of 22 hematopoietic TIIC from 80 UVM tumor samples. Cytolytic activity (CYT) was determined, and associated survival probabilities were mined using time-to-event data. Nominal P-values were subjected to FDR correction.

Results

High relative abundance of tumor-infiltrating naïve B cells, resting memory CD4+ T cells, and monocytes correlated with better overall and disease-free survival probability. Low relative abundance of CD8+ T cells correlated with better overall survival and disease-free survival probability. CYT correlated positively with relative abundance of naïve B cells, resting memory CD4+ T cells, and monocytes. CYT correlated negatively with relative abundance of CD8+ T cells.

Conclusion

Infiltrating naïve B cells, resting memory CD4+ T cells, monocytes, and CD8+ T cells are potential therapeutic targets in UVM that warrant further investigation. High CYT estimates associate with worse UVM survival outcomes.

RNA sequencing of glioblastoma tissue slice cultures reveals the effects of treatment at the transcriptional level

One of the major challenges in cancer research is finding models that closely resemble tumors within patients. Human tissue slice cultures are a promising approach to provide a model of the patient's tumor biology ex vivo. Recently, it was shown that these slices can be successfully analyzed by whole transcriptome sequencing as well as automated histochemistry, increasing their usability as preclinical model. Glioblastoma multiforme (GBM) is a highly malignant brain tumor with poor prognosis and little is known about its genetic background and heterogeneity regarding therapy success. In this study, tissue from the tumors of 25 patients with primary GBM was processed into slice cultures and treated with standard therapy (irradiation and temozolomide). Total RNA sequencing and automated histochemistry were performed to enable analysis of treatment effects at a transcriptional and histological level. Slice cultures from long‐term survivors (overall survival [OS] > 24 months) exhibited more apoptosis than cultures from patients with shorter OS. Proliferation within these slices was slightly increased in contrast to other groups, but not significantly. Among all samples, 58 protein‐coding genes were upregulated and 32 downregulated in treated vs. untreated slice cultures. In general, an upregulation of DNA damage‐related and cell cycle checkpoint genes as well as enrichment of genotoxicity pathways and p53‐dependent signaling was found after treatment. Overall, the current study reproduces knowledge from former studies regarding the feasibility of transcriptomic analyses and automated histology in tissue slice cultures. We further demonstrate that the experimental data merge with the clinical follow‐up of the patients, which improves the applicability of our model system.

M2 subtype tumor associated macrophages (M2-TAMs) infiltration predicts poor response rate of immune checkpoint inhibitors treatment for prostate cancer

BACKGROUND

Prostate cancer (PCa) is poor response to the immunotherapy for its high heterogeneity of immune microenvironment. In this study, we aim to introduce a new immune subtype for PCa involving M2 tumour associated macrophages (M2-TAMs).

METHODS

Three hundred and sixty-two PCa patients and matched normal prostate tissues were selected from the Cancer Genome Atlas and Gene Expression Omnibus databases. Patients' immune infiltration characters were then analyzed based on the gene expressions. The immune subtypes were identified by the method of unsupervised hierarchical clustering. Finally, the relationship between the M2-TAMs infiltration and anti-programmed death-ligand-1 (PD-L1) therapy was investigated in the IMvigor210 cohort.

RESULTS

PCa expressed lower immune-related genes levels compared with the adjacent normal tissues. Based on the proved immunosuppressive mechanisms in PCa, tumour patients were classified into three independent subclasses with high infiltrated cytolytic activity (CYT), M2-TAMs and regulatory T cell (Tregs), respectively. Among these subtypes, M2-TAMs infiltration subtype showed the worst clinicopathological features and prognosis compared with the other two subtypes. The results of the IMvigor210 cohort demonstrated poor response of anti-PD-L1 therapy for patients with high M2-TAMs infiltration.

CONCLUSION

Prostate tumours involved in significant immunosuppression, and high infiltration of M2-TAMs can be applied to predict the effect of anti-PD-L1 therapy.Key MessagesPCa patients can be classified into three immunotypes of high infiltrated CYT, M2-TAMS, and Tregs according to the immunosuppressive mechanisms.High M2-TAMs infiltration subtype reflected the worst clinical characters, immune infiltration, and lowest expression of immune checkpoint inhibitors among the three subclasses in PCa.High M2-TAMs infiltration predicts the low response rate of anti-PD-L1 therapy.

Differential genes and scoring criteria among immunogenomic clusters of lower-grade gliomas

High incidence of recurrency had been a significant threat among glioma patients. Moreover, the performance of traditional therapies among recurrent gliomas was far from satisfying. Advances in the tumor microenvironment (TME) and immune responses on the brain inspired immunotherapy researches. Nevertheless, verification of classic PD-1/PD-L1 inhibitors failed in phase III clinical trials. Additional gene targets were required for future studies among glioma patients. Immune cell infiltration (ICI) scores, defined based on multiple prognostic genes, were proved as the marker for the sensitivity of immunotherapies in many tumors. However, relevant results were not reported in gliomas. In the study, a retrospective cohort of 495 patients was classified into two ICI score subgroups. High ICI scores were closely related to high tumor mutation burden (TMB) values, indicating a high instability of genes. Furthermore, ICI scores were proved as reliable prognostic predictors. And a predictive model was built based on the ICI scores and multiple clinical features. The model showed its superiority through both internal validation and external validation. The ICI scores and the predictive model showed significant clinical values through decision curve analysis (DCA) since high ICI scores were related to high sensitivity for treatment. The prognostic immune-related gene list provided targets for immunotherapy researches.

Distinct genomic features across cytolytic subgroups in skin melanoma

BACKGROUND

Skin melanoma is a highly immunogenic cancer. The intratumoral immune cytolytic activity (CYT) reflects the ability of cytotoxic T and NK cells to eliminate cancer cells, and is associated with improved patient survival. Despite the enthusiastic clinical results seen in advanced-stage metastatic melanoma patients treated with immune checkpoint inhibitors, a subgroup of them will later relapse and develop acquired resistance. We questioned whether CYT associates with different genomic profiles and thus, patient outcome, in skin melanoma.

METHODS

We explored the TCGA-SKCM dataset and stratified patients to distinct subgroups of cytolytic activity. The tumor immune contexture, somatic mutations and recurrent copy number aberrations were calculated using quanTIseq, MutSigCV and GISTIC2. Chromothriptic events were explored using CTLPScanner and cancer neoepitopes were predicted with antigen garnish. Each tumor's immunophenoscore was calculated using Immunophenogram. Mutational signatures and kataegis were explored using SigProfiler and compared to the known single or doublet base substitution signatures from COSMIC.

RESULTS

Metastatic skin melanomas had significantly higher CYT levels compared to primary tumors. We assessed enrichment for immune-related gene sets within CYT-high tumors, whereas, CYT-low tumors were enriched for non-immune related gene sets. In addition, distinct mutational and neoantigen loads, primarily composed of C > T transitions, along with specific types of copy number aberrations, characterized each cytolytic subgroup. We found a broader pattern of chromothripsis across CYT-low tumors, where chromosomal regions harboring chromothriptic events, contained a higher number of cancer genes. SBS7a/b, SBS5 and SBS1 were the most prevalent mutational signatures across both cytolytic subgroups, but SBS1 differed significantly between them. SBS7a/b was mutually exclusive with SBS5 and SBS1 in both CYT subgroups. CYT-high patients had markedly higher immunophenoscore, suggesting that they should display a clinical benefit upon treatment with immune checkpoint inhibition therapy, compared to CYT-low patients.

CONCLUSIONS

Overall, our data highlight the existence of distinct genomic features across cytolytic subgroups in skin melanoma, which might affect the patients' relapse rate or their acquisition of resistance to immune checkpoint inhibition therapies.

Efficacy of Immune Checkpoint Inhibitors in Rare Tumours: A Systematic Review

Background

Rare cancers, as defined by the European Union, occur in fewer than 15 out of 100,000 people each year. The International Rare Cancer Consortium defines rare cancer incidence as less than six per 100,000 per year. There is a growing number of reports of the efficacy of immune checkpoint inhibitor (ICI) therapy in patients with rare tumours, and hence, we conducted a comprehensive review to summarise and analyse the available literature.

Methods

A literature search of PubMed was performed on January 31, 2021, using the following ICI names as keywords: ipilimumab, tremelimumab, cemiplimab, nivolumab, pembrolizumab, avelumab, atezolizumab, and durvalumab. Studies on patients with rare tumours who were being treated with ICIs were included. We plotted the overall response rate against the corresponding median survival across a variety of cancer types using linear regression.

Results

From 1,255 publications retrieved during the primary search, 62 publications were selected (with a total of 4,620 patients). Only four were randomised trials. A minority were first-line studies, while the remaining were studies in which ICIs were delivered as salvage therapy in pretreated patients. There was a good correlation between response rate and overall survival (Spearman R2 >0.9) in skin cancers, mesothelioma, and sarcomas.

Conclusions

Treatment of advanced-stage rare tumours with ICI therapy was found to be associated with significant activity in some orphan diseases (e.g., Merkel cell carcinoma) and hepatocellular carcinoma. Several ongoing prospective clinical trials will expand the knowledge on the safety and efficacy of ICI therapy in patients with these rare cancers.

Immune and stromal scoring system associated with tumor microenvironment and prognosis: a gene-based multi-cancer analysis

Background

Tumor microenvironment (TME) is associated with tumor progression and prognosis. Previous studies provided tools to estimate immune and stromal cell infiltration in TME. However, there is still a lack of single index to reflect both immune and stromal status associated with prognosis and immunotherapy responses.

Methods

A novel immune and stromal scoring system named ISTMEscore was developed. A total of 15 datasets were used to train and validate this system, containing 2965 samples from lung adenocarcinoma, skin cutaneous melanoma and head and neck squamous cell carcinoma.

Results

The patients with high immune and low stromal scores (HL) were associated with low ratio of T cell co-inhibitory/stimulatory molecules and low levels of angiogenesis markers, while the patients with low immune and high stromal scores (LH) had the opposite characteristics. The HL patients had immune-centered networks, while the patients with low immune and low stromal scores (LL) had desert-like networks. Moreover, copy number alteration burden was decreased in the HL patients. For the clinical characteristics, our TME classification was an independent prognostic factor. In the 5 cohorts with immunotherapy, the LH patients were linked to the lowest response rate.

Conclusions

ISTMEscore system could reflect the TME status and predict the prognosis. Compared to previous TME scores, our ISTMEscore was superior in the prediction of prognosis and immunotherapy response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03002-1.

A novel immune-related gene pair prognostic signature for predicting overall survival in bladder cancer

Background

Bladder cancer (BC) is the ninth most common malignant tumor. We constructed a risk signature using immune-related gene pairs (IRGPs) to predict the prognosis of BC patients.

Methods

The mRNA transcriptome, simple nucleotide variation and clinical data of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database (TCGA-BLCA). The mRNA transcriptome and clinical data were also extracted from Gene Expression Omnibus (GEO) datasets (GSE31684). A risk signature was built based on the IRGPs. The ability of the signature to predict prognosis was analyzed with survival curves and Cox regression. The relationships between immunological parameters [immune cell infiltration, immune checkpoints, tumor microenvironment (TME) and tumor mutation burden (TMB)] and the risk score were investigated. Finally, gene set enrichment analysis (GSEA) was used to explore molecular mechanisms underlying the risk score.

Results

The risk signature utilized 30 selected IRGPs. The prognosis of the high-risk group was significantly worse than that of the low-risk group. We used the GSE31684 dataset to validate the signature. Close relationships were found between the risk score and immunological parameters. Finally, GSEA showed that gene sets related to the extracellular matrix (ECM), stromal cells and epithelial-mesenchymal transition (EMT) were enriched in the high-risk group. In the low-risk group, we found a number of immune-related pathways in the enriched pathways and biofunctions.

Conclusions

We used a new tool, IRGPs, to build a risk signature to predict the prognosis of BC. By evaluating immune parameters and molecular mechanisms, we gained a better understanding of the mechanisms underlying the risk signature. This signature can also be used as a tool to predict the effect of immunotherapy in patients with BC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08486-0.

Morphologic and molecular correlates of EZH2 as a predictor of platinum resistance in high-grade ovarian serous carcinoma

BACKGROUND

Enhancer of zesta homologue 2 (EZH2) is an essential component of polycomb repressive complex 2 (PRC2) that contributes to tumor progression and chemo-resistance. The aim of this study was to comprehensively assess the prognostic value of EZH2 across the morphologic and molecular spectra of high-grade serous ovarian carcinoma (HGSOC) by utilizing both immunohistochemistry (IHC) and proteogenomic technologies.

METHODS

IHC of EZH2 was performed using a tissue microarray of 79 HGSOC scored (+/-) for lymphovascular invasion (LVI), tumor-infiltrating lymphocytic aggregates ≥1 mm (TIL) and architectural growth patterns. The association of EZH2 H-score with response to therapy and overall survival was evaluated by tumor features. We also evaluated EZH2 transcriptional (RNA sequencing) and protein (mass spectrometry) expression from bulk tumor samples from 336 HGSOC from The Cancer Genome Atlas (TCGA). EZH2 expression and co-expression networks were compared by clinical outcomes.

RESULTS

For HGSOC without TIL (58%), EZH2 expression was almost 2-fold higher in platinum resistant tumors (P = 0.01). Conversely, EZH2 was not associated with platinum resistance among TIL+ HGSOC (P = 0.41). EZH2 expression was associated with reduced survival for tumors with LVI (P = 0.04). Analysis of TCGA found higher EZH2 expression in immunoreactive and proliferative tumors (P = 6.7 × 10^- 5) although protein levels were similar across molecular subtypes (P = 0.52). Both mRNA and protein levels of EZH2 were lower in platinum resistant tumors although they were not associated with survival. Co-expression analysis revealed EZH2 networks totaling 1049 mRNA and 448 proteins that were exclusive to platinum sensitive or resistant tumors. The EZH2 network in resistant HGSOC included CARM1 which was positively correlated with EZH2 at both mRNA (r = 0.33, p = 0.003) and protein (r = 0.14, P = 0.01) levels. Further, EZH2 co-expression with CARM1 corresponded to a decreased prognostic significance of EZH2 expression in resistant tumors.

CONCLUSIONS

Our findings demonstrate that EZH2 expression varies based on its interactions with immunologic pathways and tumor microenvironment, impacting the prognostic interpretation. The association between high EZH2 expression and platinum resistance in TIL- HGSOC warrants further study of the implications for therapeutic strategies.

Pan-cancer methylation analysis reveals an inverse correlation of tumor immunogenicity with methylation aberrancy

Tumor immunogenicity is driven by various genomic and transcriptomic factors but the association with the overall status of methylation aberrancy is not well established. We analyzed The Cancer Genome Atlas pan-cancer database to investigate whether the overall methylation aberrancy links to the immune evasion of tumor. We created the definitions of hypermethylation burden, hypomethylation burden and methylation burden to establish the values that represent the degree of methylation aberrancy from human methylation 450 K array data. Both hypermethylation burden and hypomethylation burden significantly correlated with global methylation level as well as methylation subtypes defined in previous literatures. Then we evaluated whether methylation burden correlates with tumor immunogenicity and found that methylation burden showed a significant negative correlation with cytolytic activity score, which represent cytotoxic T cell activity, in pan-cancer (Spearman rho = - 0.37, p < 0.001) and 30 of 33 individual cancer types. Furthermore, this correlation was independent of mutation burden and chromosomal instability in multivariate regression analysis. We validated the findings in the external cohorts and outcomes of patients who were treated with immune checkpoint inhibitors, which showed that high methylation burden group had significantly poor progression-free survival (Hazard ratio 1.74, p = 0.038). Overall, the degree of methylation aberrancy negatively correlated with tumor immunogenicity. These findings emphasize the importance of methylation aberrancy for tumors to evade immune surveillance and warrant further development of methylation biomarker.

Gene expression-based immune infiltration analyses of renal cancer and their associations with survival outcome

BACKGROUND

Renal cancer is a common malignant tumor with an increasing incidence rate.

METHODS

In this study, based on the gene expression profiles, we analyzed the compositions of tumor-infiltrating immune cells (TIICs) in renal cancer and paracancerous samples using CIBERSORT. The proportions of 22 TIICs subsets in 122 paired renal carcinoma and paracancerous samples, and 224 Wilms tumor (WT) samples varied between intragroup and intergroup.

RESULTS

After analyzed the difference of TIICs composition between renal cancer and paired paracancerous samples, we found that M0 macrophages and CD8 T cells were significantly elevated, while naive B cells were significantly decreased in renal cancer samples compared with paracancerous samples. Survival analysis showed that high overall TIICs proportion, the low proportion of resting mast cells and the high proportion of activated memory CD4 T cells were associated with poor prognosis of renal cancer patients. In addition, 3 clusters were identified by hierarchical clustering analysis, and they presented a distinct prognosis. Cluster 1 had superior survival outcomes, while cluster 2 had an inferior survival outcome.

CONCLUSIONS

Our study indicated that overall TIICs proportion, certain TIICs subset proportion, including resting mast cells and activated memory CD4 T cells, and distinct cluster patterns were associated with the prognosis of renal cancer, which was significant for the clinical surveillance and treatment of renal cancer.

Identification and validation of a risk signature based on extracellular matrix-related genes in gliomas

ABSTRACT

Gliomas have the highest incidence among primary brain tumors, and the extracellular matrix (ECM) plays a vital role in tumor progression. We constructed a risk signature using ECM-related genes to predict the prognosis of patients with gliomas.mRNA and clinical data from glioma patients were downloaded from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Chinese Glioma Genome Atlas (CGGA) databases. Differentially expressed ECM-related genes were screened, and a risk signature was built using least absolute shrinkage and selection operator (LASSO) Cox regression. Cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to assess immune infiltration in different risk groups. Gene set enrichment analysis (GSEA) was performed to explore the molecular mechanisms of the genes employed in the risk score.Differentially expressed ECM-related genes were identified, and their associated regulatory mechanisms were predicted via analysis of protein-protein interaction (PPI), transcription factor (TF) regulatory and TF coexpression networks. The established risk signature considered 17 ECM-related genes. The prognosis of the high-risk group was significantly worse than that of the low-risk group. We used the CGGA database to validate the signature. CIBERSORT indicated that the levels of naive B cells, activated memory CD4 T cells, regulatory T cells, gamma delta T cells, activated NK cells, monocytes, activated dendritic cells and activated mast cells were higher in the high-risk group. The levels of plasma cells, CD8 T cells, naive CD4 T cells, resting memory CD4 T cells, M0 macrophages, M1 macrophages, resting mast cells, and neutrophils were lower in the high-risk group. Ultimately, GSEA showed that the terms intestinal immune network for IgA production, primary immunodeficiency, and ECM receptor interaction were the top 3 terms enriched in the high-risk group. The terms Wnt signaling pathway, ErbB signaling pathway, mTOR signaling pathway, and calcium signaling pathway were enriched in the low-risk group.We built a risk signature to predict glioma prognosis using ECM-related genes. By evaluating immune infiltration and biofunctions, we gained a further understanding of this risk signature. This risk signature could be an effective tool for predicting glioma prognosis.This study did not require ethical approval. We will disseminate our findings by publishing results in a peer-reviewed journal.

Prognostic significance of esterase gene expression in multiple myeloma

BACKGROUND

Esterase enzymes differ in substrate specificity and biological function and may display dysregulated expression in cancer. This study evaluated the biological significance of esterase expression in multiple myeloma (MM).

METHODS

For gene expression profiling and evaluation of genomic variants in the Institute for Molecular Medicine Finland (FIMM) cohort, bone marrow aspirates were obtained from patients with newly diagnosed MM (NDMM) or relapsed/refractory MM (RRMM). CD138+ plasma cells were enriched and used for RNA sequencing and analysis, and to evaluate genomic variation. The Multiple Myeloma Research Foundation (MMRF) Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile (CoMMpass) dataset was used for validation of the findings from FIMM.

RESULTS

MM patients (NDMM, n = 56; RRMM, n = 78) provided 171 bone marrow aspirates (NDMM, n = 56; RRMM, n = 115). Specific esterases exhibited relatively high or low expression in MM, and expression of specific esterases (UCHL5, SIAE, ESD, PAFAH1B3, PNPLA4 and PON1) was significantly altered on progression from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, SIAE and USP4, and low expression of PCED1B, were identified as poor prognostic markers (P < 0.05). The MMRF CoMMpass dataset provided validation that higher expression of PAFAH1B3 and SIAE, and lower expression of PCED1B, were associated with poor prognosis.

CONCLUSIONS

Esterase gene expression levels change as patients progress from NDMM to RRMM. High expression of OVCA2, PAFAH1B3, USP4 and SIAE, and low expression of PCED1B, are poor prognostic markers in MM, suggesting a role for these esterases in myeloma biology.

Profiles of immune cell infiltration in head and neck squamous carcinoma

Tumor immune infiltration cells (TIICs) are highly heterogeneous, not only in different cancer subtypes but also within different cancer regions. We conducted the Cell-type Identification using Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method. We assessed the relative proportions of 22 TIICs in HNSC using publicly available TCGA transcriptional datasets, analyzed the proportions of TIICs between HNSC tissues and normal tissues, along with accompanying clinicopathological data, and the impact of TIICs on clinical outcome. After the filter criteria, a total of 395 patients were included in the analysis. We found significant differences in naïve B cells, monocytes, resting mast cells, activated mast cells, CD8⁺ T cells, and M0 macrophages between HNSC tissues and adjacent non-cancer tissues. We also found that some TIIC subgroups were significantly associated with clinical parameters. Moreover, the patients with low Tregs fraction had worse OS and DFS than those with high Tregs fraction. However, low M0 macrophages fraction was associated with better OS and DFS in HNSC patients. Moreover, Tregs and M0 macrophages are likely to be important determinants of prognosis, which may serve as a potential immunotherapy target for HNSC. Then, we screened the immune-related differentially expressed genes (DEGs), performed the GO and KEGG enrichment analysis, constructed the protein–protein interaction network, and screened the prognosis-related hub genes in HNSC. However, further clinical investigation and basic experiments are needed to validate our results, and uncover the molecular mechanisms interlinking TIICs in HNSC and their roles in prognosis and therapy.

Molecular correlates of immune cytolytic subgroups in colorectal cancer by integrated genomics analysis

Although immune checkpoint inhibition (ICI) has shown promising results in metastatic dMMR/MSI-H colorectal cancer (CRC), the majority of pMMR/MSS patients do not respond to such therapies. To systematically evaluate the determinants of immune response in CRC, we explored whether patients with diverse levels of immune cytolytic activity (CYT) have different patterns of chromothripsis and kataegis. Analysis of CRC genomic data from the TCGA, indicated an excess of chromothriptic clusters among CYT-low colon adenocarcinomas, affecting known cancer drivers (APC, KRAS, BRAF, TP53 and FBXW7), immune checkpoints (CD274, PDCD1LG2, IDO1/2 and LAG3) and immune-related genes (ENTPD1, PRF1, NKG7, FAS, GZMA/B/H/K and CD73). CYT-high tumors were characterized by hypermutation, enrichment in APOBEC-associated mutations and kataegis events, as well as APOBEC activation. We also assessed differences in the most prevalent mutational signatures (SBS15, SBS20, SBS54 and DBS2) across cytolytic subgroups. Regarding the composition of immune cells in the tumor milieu, we found enrichment of M1 macrophages, CD8+ T cells and Tregs, as well as higher CD8+ T-cells/Tregs ratio among CYT-high tumors. CYT-high patients had higher immunophenoscores, which is predictive of their responsiveness if they were to be treated with anti-PD-1 alone or in combination with anti-CTLA-4 drugs. These results could have implications for patient responsiveness to immune checkpoint inhibitors.

PRF1 is a prognostic marker and correlated with immune infiltration in head and neck squamous cell carcinoma

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The cytotoxic protein PRF1 is essentially involved in anti-tumour immunity.

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PRF1 is overexpressed in advanced HPV+ HNSCC and correlates with better OS.

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PRF1 expression correlates with tumour infiltrating CD8+ t cells and dendritic cells in HPV+ HNSCC.

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PRF1 expression correlates with gene markers of t cell exhaustion in HNSCC.

Purpose

Head and neck squamous cell carcinoma (HNSCC) is a highly invasive malignancy with poor survival. Perforin (PRF1) plays essential roles in host immunity. Our research intended to identify the correlations of PRF1 with clinical prognosis and tumor immune infiltration in HNSCC.

Methods

We explored PRF1 expression and its associations with the clinical features of HNSCC via the Tumor Immune Estimation Resource (TIMER), Oncomine and The Cancer Genome Atlas (TCGA) databases. The prognostic value of PRF1 for HNSCC was further explored by Kaplan–Meier plotter and TIMER. Finally, the relation between PRF1 and immune infiltration in HNSCC was estimated via CIBERSORT and TIMER.

Results

PRF1 expression was remarkably elevated in HNSCC and associated with clinical stage and HPV infection. High PRF1 expression predicted favorable outcomes in HNSCC, especially in HPV+ HNSCC. Moreover, higher infiltration of CD8+ T cells and CD4+ T cells were found in the PRF1^high group of HNSCC. PRF1 expression in HNSCC was strongly correlated with infiltrating CD8+ T cells and dendritic cells (DCs), with higher relevance in HPV+ HNSCC.

Conclusion

Our findings suggested that PRF1 could be a novel prognostic biomarker in HNSCC and that its expression was related to immune cell infiltration, which was impacted by HPV status.

Benchmarking HLA genotyping and clarifying HLA impact on survival in tumor immunotherapy

Human leukocyte antigen (HLA) genotyping gains intensive attention due to its critical role in cancer immunotherapy. It is still a challenging issue to generate reliable HLA genotyping results through in silico tools. In addition, the survival impact of HLA alleles in tumor prognosis and immunotherapy remains controversial. In this study, the benchmarking of HLA genotyping on TCGA is performed and a ‘Gun‐Bullet’ model which helps to clarify the survival impact of HLA allele is presented. The performance of HLA class I genotyping is generally better than class II. POLYSOLVER, OptiType, and xHLA perform generally better at HLA class I calling with an accuracy of 0.954, 0.949, and 0.937, respectively. HLA‐HD obtained the highest accuracy of 0.904 on HLA class II alleles calling. Each HLA genotyping tool displayed specific error patterns. The ensemble HLA calling from the top‐3 tools is superior to any individual one. HLA alleles show distinct survival impact among cancers. Cytolytic activity (CYT) was proposed as the underlying mechanism to interpret the survival impact of HLA alleles in the ‘Gun‐Bullet’ model for fighting cancer. A strong HLA allele plus a high tumor mutation burden (TMB) could stimulate intensive immune CYT, leading to extended survival. We established an up to now most reliable TCGA HLA benchmark dataset, composing of concordance alleles generated from eight prevalently used HLA genotyping tools. Our findings indicate that reliable HLA genotyping should be performed based on concordance alleles integrating multiple tools and incorporating TMB background with HLA genotype, which helps to improve the survival prediction compared to HLA genotyping alone.

Black Raspberries Suppress Colorectal Cancer by Enhancing Smad4 Expression in Colonic Epithelium and Natural Killer Cells

Innate immune cells in the tumor microenvironment have been proposed to control the transition from benign to malignant stages. In many cancers, increased infiltration of natural killer (NK) cells associates with good prognosis. Although the mechanisms that enable NK cells to restrain colorectal cancer (CRC) are unclear, the current study suggests the involvement of Smad4. We found suppressed Smad4 expression in circulating NK cells of untreated metastatic CRC patients. Moreover, NK cell-specific Smad4 deletion promoted colon adenomas in DSS-treated ApcMin/+ mice and adenocarcinomas in AOM/DSS-treated mice. Other studies have shown that Smad4 loss or weak expression in colonic epithelium associates with poor survival in CRC patients. Therefore, targeting Smad4 in both colonic epithelium and NK cells could provide an excellent opportunity to manage CRC. Toward this end, we showed that dietary intervention with black raspberries (BRBs) increased Smad4 expression in colonic epithelium in patients with FAP or CRC and in the two CRC mouse models. Also, benzoate metabolites of BRBs, such as hippurate, upregulated Smad4 and Gzmb expression that might enhance the cytotoxicity of primary human NK cells. Of note, increased levels of hippurate is a metabolomic marker of a healthy gut microbiota in humans, and hippurate also has antitumor effects. In conclusion, our study suggests a new mechanism for the action of benzoate metabolites derived from plant-based foods. This mechanism could be exploited clinically to upregulate Smad4 in colonic epithelium and NK cells, thereby delaying CRC progression.

Role of Natural Killer Cells in Uveal Melanoma

Simple Summary

Metastatic Uveal Melanoma (MUM) is a lethal malignancy with no durable treatment available to date. A vast majority of patients with MUM present with liver metastasis. The liver harbors metastatic disease with an apparent lack of a cytotoxic T cell response. It is becoming evident that MUM is not an immunologically silent malignancy and the investigation of non-T cell anti-tumor immunity is warranted. In this review, we highlight the relevance of Natural Killer (NK) cells in the biology and treatment of MUM. Potent anti-NK cell immunosuppression employed by uveal melanoma alludes to its vulnerability to NK cell cytotoxicity. On the contrary, micro-metastasis in the liver survive for several years within close vicinity of a plethora of circulating and liver-resident NK cells. This review provides unique perspectives into the potential role of NK cells in control or progression of uveal melanoma.

Abstract

Uveal melanoma has a high mortality rate following metastasis to the liver. Despite advances in systemic immune therapy, treatment of metastatic uveal melanoma (MUM) has failed to achieve long term durable responses. Barriers to success with immune therapy include the immune regulatory nature of uveal melanoma as well as the immune tolerant environment of the liver. To adequately harness the anti-tumor potential of the immune system, non-T cell-based approaches need to be explored. Natural Killer (NK) cells possess potent ability to target tumor cells via innate and adaptive responses. In this review, we discuss evidence that highlights the role of NK cell surveillance and targeting of uveal melanoma. We also discuss the repertoire of intra-hepatic NK cells. The human liver has a vast and diverse lymphoid population and NK cells comprise 50% of the hepatic lymphocytes. Hepatic NK cells share a common niche with uveal melanoma micro-metastasis within the liver sinusoids. It is, therefore, crucial to understand and investigate the role of intra-hepatic NK cells in the control or progression of MUM.

Construction of a risk signature for adrenocortical carcinoma using immune-related genes

Background

Adrenocortical carcinoma (ACC) is considered a rare tumor with a dismal prognosis. Expression of immune-related genes (IRGs) in ACC and correlations between IRGs and ACC prognosis were assessed using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases.

Methods

To preliminarily predict immune cell infiltration, an immune score was calculated using ESTIMATE. Differentially expressed IRGs were screened, and potential biological functions were investigated. We then performed univariate Cox regression to identify IRGs associated with survival, and the regulatory mechanisms of IRGs associated with survival were predicted. We built a risk signature through multivariate Cox regression to evaluate patient overall survival (OS).

Results

A high immune score predicted a good prognosis and an early clinical stage in ACC. We identified 30 IRGs associated with survival and then predicted associated regulatory mechanisms via protein-protein interaction (PPI) and transcription factor (TF) regulatory networks. The risk signature established by multivariate Cox regression correlated significantly with prognosis in ACC.

Conclusions

The vital roles of IRGs in ACC were assessed, and the risk signature obtained based on IRGs associated with survival independently predicted ACC prognosis.

CD36 and CD97 in Pancreatic Cancer versus Other Malignancies

Starting from the recent identification of CD36 and CD97 as a novel marker combination of fibroblast quiescence in lung during fibrosis, we aimed to survey the literature in search for facts about the separate (or concomitant) expression of clusters of differentiation CD36 and CD97 in either tumor- or pancreatic-cancer-associated cells. Here, we provide an account of the current knowledge on the diversity of the cellular functions of CD36 and CD97 and explore their potential (common) contributions to key cellular events in oncogenesis or metastasis development. Emphasis is placed on quiescence as an underexplored mechanism and/or potential target in therapy. Furthermore, we discuss intricate signaling mechanisms and networks involving CD36 and CD97 that may regulate different subpopulations of tumor-associated cells, such as cancer-associated fibroblasts, adipocyte-associated fibroblasts, tumor-associated macrophages, or neutrophils, during aggressive pancreatic cancer. The coexistence of quiescence and activated states in cancer-associated cell subtypes during pancreatic cancer should be better documented, in different histological forms. Remodeling of the local microenvironment may also change the balance between growth and dormant state. Taking advantage of the reported data in different other tissue types, we explore the possibility to induce quiescence (similar to that observed in normal cells), as a therapeutic option to delay the currently observed clinical outcome.

Signatures of co-deregulated genes and their transcriptional regulators in colorectal cancer

The deregulated genes in colorectal cancer (CRC) vary significantly across different studies. Thus, a systems biology approach is needed to identify the co-deregulated genes (co-DEGs), explore their molecular networks, and spot the major hub proteins within these networks. We reanalyzed 19 GEO gene expression profiles to identify and annotate CRC versus normal signatures, single-gene perturbation, and single-drug perturbation signatures. We identified the co-DEGs across different studies, their upstream regulating kinases and transcription factors (TFs). Connectivity Map was used to identify likely repurposing drugs against CRC within each group. The functional changes of the co-upregulated genes in the first category were mainly associated with negative regulation of transforming growth factor β production and glomerular epithelial cell differentiation; whereas the co-downregulated genes were enriched in cotranslational protein targeting to the membrane. We identified 17 hub proteins across the co-upregulated genes and 18 hub proteins across the co-downregulated genes, composed of well-known TFs (MYC, TCF3, PML) and kinases (CSNK2A1, CDK1/4, MAPK14), and validated most of them using GEPIA2 and HPA, but also through two signature gene lists composed of the co-up and co-downregulated genes. We further identified a list of repurposing drugs that can potentially target the co-DEGs in CRC, including camptothecin, neostigmine bromide, emetine, remoxipride, cephaeline, thioridazine, and omeprazole. Similar analyses were performed in the co-DEG signatures in single-gene or drug perturbation experiments in CRC. MYC, PML, CDKs, CSNK2A1, and MAPKs were common hub proteins among all studies. Overall, we identified the critical genes in CRC and we propose repurposing drugs that could be used against them.

Inflammation and lymphocyte infiltration are associated with shorter survival in patients with high-grade glioma

Glioma represents a serious health burden in terms of morbidity and mortality. The prognostic significance of the lymphoid and myeloid infiltrates in glioma is not clearly determined. Moreover, the characterization of different leukocyte subsets in the tumor microenvironment relies mainly on immunohistochemistry observations, and data about their association with prognosis are contradictory. Here, we performed acomprehensive study of both the tumor-infiltrating and circulating immune compartments of patients with high-grade glioma. Nineteen tumor biopsies and 30 PBMC samples were analyzed by RNA sequencing. Validation was performed on The Cancer Genome Atlas (TCGA) RNA sequencing data from glioma and on additional 39 tumor biopsies analyzed by flow cytometry. We identified prognostic tumor and peripheral immune signatures, which associate increased inflammation, immune infiltration and activation with shorter overall survival in high-grade glioma patients. Importantly, we confirmed our observations by flow cytometry analysis and validated the tumor-signature using the TCGA dataset. In addition, both tumor genotype and grade associated with the degree of glioma immune infiltration. Unlike in the majority of cancers, lymphocyte infiltration at the tumor site is anegative prognostic factor in glioma, suggesting the ambivalent pro-tumorigenic role of immune responses in glioma.

Identification of the key genes and characterizations of Tumor Immune Microenvironment in Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC)

This study aimed to investigate the key genes and immune microenvironment involved in different TNM stages of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). The gene expression and clinical characteristics data were downloaded from the genomic data commons (GDC) database. After initial data processing, the characteristics of the immune microenvironment were analyzed. The differentially expressed genes (DEGs) in tumor vs. normal, and in early vs. advanced stages were screened, followed by Spearman correlation test for tumor infiltrating immune cells (TIICs) to identify immune-related genes. Finally, functional enrichment, protein-protein interaction, and survival analyses were performed. In LUAD, early stage was with higher immune scores, greater number of memory B cells and M0 macrophages compared to advanced stage. M0 and M2 macrophages, and resting memory CD4+ T cells accounted for a large proportion of TIICs in LUAD. The abundance of M0 macrophage infiltration was significantly correlated with the TNM stage and survival. In LUSC, early stage was with higher cytolytic activity and neoantigen burden compared to advanced stage. M0 and M2 macrophages, and plasma cells accounted for a large proportion of TIICs in LUSC. The abundance of resting and activated mast cells was significantly correlated with TNM stage, while resting dendritic cells, eosinophils, activated memory CD4 T cells, and mast cells were significantly correlated with prognosis. Tumor mutation burden analysis revealed that the median of variants per sample decreased from stage I to IV in LUAD, while it increased in LUSC. Further, 83 and 9 immune-related DEGs were identified in LUAD and LUSC, respectively, of which 23 genes in LUAD and 2 genes in LUSC correlated with survival. In conclusion, we identified the key genes, and characterized the tumor immune microenvironment in LUAD and LUSC which may provide therapeutic targets for the treatment of NSCLC.

ILK silencing inhibits migration and invasion of more invasive glioblastoma cells by downregulating ROCK1 and Fascin-1

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor and it is associated with poor survival. Integrin-linked kinase (ILK) is a serine/threonine protein pseudo-kinase that binds to the cytoplasmic domains of β1 and β3 integrins and has been previously shown to promote invasion and metastasis in many cancer types, including GBM. However, little is known regarding the exact molecular mechanism implicating ILK in GBM aggressiveness. In this study, we used two brain cell lines, the non-invasive neuroglioma H4 cells, and the highly invasive glioblastoma A172 cells, which express ILK in much higher levels than H4. We studied the effect of ILK silencing on the metastatic behavior of glioblastoma cells in vitro and elucidate the underlying molecular mechanism. We showed that siRNA-mediated silencing of ILK inhibits cell migration and invasion of the highly invasive A172 cells while it does not affect the migratory and invasive capacity of H4 cells. These data were also supported by respective changes in the expression of Rho-associated kinase 1 (ROCK1), fascin actin-bundling protein 1 (FSCN1), and matrix metalloproteinase 13 (MMP13), which are known to regulate cell migration and invasion. Our findings were further corroborated by analyzing the Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) dataset. We conclude that ILK promotes glioblastoma cell invasion through activation of ROCK1 and FSCN1 in vitro, providing a more exact molecular mechanism for its action.

PD-L1 Expression Affects Neoantigen Presentation

Although PD-L1 expression on tumor is related to the prognosis of immune checkpoint blockade (ICB) therapy, a recent study also demonstrated clinical benefits even in patients without PD-L1 expression. To understand the relationship between innate resistance and antitumor cytotoxic T lymphocyte (CTL) responses especially against neoantigens, the interaction between PD-L1⁺ or genetically PD-L1-deleted colorectal tumors and CTLs was assessed under an ICB therapy, finding the robust CTL activation in PD-L1-deleted tumor-bearing mice. Using antigen libraries based on immunogenomics, we identified three H2-K^b-restricted, somatic-mutated immunogenic neoantigens by utilizing enhanced CTLs responses due to PD-L1 deficiency. Furthermore, we identified three T cell receptor (TCR) repertoires relevant to the neoantigens, confirming the response of TCR-gene-transduced CTLs to parental tumor cells. Notably, neoantigen-pulsed dendritic cell (DC) therapy reversed the tumor tolerance. Thus, innate resistance of tumors determines their responsiveness to neoantigens and mixed neoantigen peptides may be useful in DC therapy against innate resistance type tumor.

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Poor prognosis of PD-L1-expressing tumors in some cancers

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Identification of TCRVα and Vβ repertoire responsive for H2-K^b-restricted neoantigens

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Neoantigen-epitope-pulsed DC therapy demonstrates antitumor effect in vaccine