• abscopal
• bladder cancer
• immunotherapy
• microenvironment
• radiation

• Humans
• Urinary Bladder Neoplasms/therapy
• Urinary Bladder Neoplasms/immunology
• Urinary Bladder Neoplasms/radiotherapy
• Urinary Bladder Neoplasms/pathology
• Immunotherapy/methods
• Combined Modality Therapy
• Tumor Microenvironment/immunology
• Tumor Microenvironment/radiation effects
• B7-H1 Antigen/antagonists & inhibitors

• -omics
• bladder cancer
• epigenetics
• genomics
• non-muscle-invasive
• progression
• recurrence
• transcriptomics

• Immunotherapy
• MFAP2
• PD-L1
• Triple-negative breast cancer (TNBC)
• Tumor mutational burden (TMB)

• JSSCBS20211600 Jiangsu Innovative and Enterpreneurial Talent Programme
• BK20220605 Natural Science Foundation of Jiangsu Province
• 82200819 National Natural Science Foundation of China

• DNA-seq
• Tumor Mutational Burden
• analysis pipeline
• pan-cancer
• personalized medicine

• Regione Siciliana

• Immunotherapy
• Neutrophil
• Triple-negative breast cancer
• Tumor microenvironment
• Tumor mutation burden

• Humans
• Triple Negative Breast Neoplasms/pathology
• Neutrophils/pathology
• DNA Copy Number Variations
• Prognosis

• Bladder cancer
• immune infiltration
• prognostic model
• recurrence

• Humans
• Prognosis
• Biomarkers
• Urinary Bladder Neoplasms/diagnosis
• Urinary Bladder
• Risk Factors

• hepatocellular carcinoma
• immune checkpoint inhibitors
• immunotherapy
• liquid biopsy
• microsatellite instability
• neoantigens
• tumor immune microenvironment
• tumor mutational burden

• Humans
• Carcinoma, Hepatocellular
• Liver Neoplasms
• Mutation
• Immunotherapy
• Biomarkers, Tumor/genetics

• B cell
• Bladder cancer
• Immunotherapy
• Senescence
• Tumor immunity

• Humans
• Cellular Senescence
• Urinary Bladder Neoplasms/genetics
• Urinary Bladder Neoplasms/therapy
• Algorithms
• Cluster Analysis
• Immunotherapy

Necroptosis is considered to be a new form of programmed necrotic cell death, which is associated with metastasis, progression and prognosis of various types of tumors. However, the potential role of necroptosis-related genes (NRGs) in the triple negative breast cancer (TNBC) is unclear.

We extracted the gene expression and relevant clinicopathological data of TNBC from The Cancer Genome Atlas (TCGA) databases and the Gene Expression Omnibus (GEO) databases. We analyzed the expression, somatic mutation, and copy number variation (CNV) of 67 NRGs in TNBC, and then observed their interaction, biological functions, and prognosis value. By performing Lasso and COX regression analysis, a NRGs-related risk model for predicting overall survival (OS) was constructed and its predictive capabilities were verified. Finally, the relationship between risk_score and immune cell infiltration, tumor microenvironment (TME), immune checkpoint, and tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity were analyzed.

A total 67 NRGs were identified in our analysis. A small number of genes (23.81%) detected somatic mutation, most genes appeared to have a high frequency of CNV, and there was a close interaction between them. These genes were remarkably enriched in immune-related process. A seven-gene risk_score was generated, containing TPSG1, KRT6A, GPR19, EIF4EBP1, TLE1, SLC4A7, ESPN. The low-risk group has a better OS, higher immune score, TMB and CSC index, and lower IC50 value of common therapeutic agents in TNBC. To improve clinical practicability, we added age, stage_T and stage_N to the risk_score and construct a more comprehensive nomogram for predicting OS. It was verified that nomogram had good predictive capability, the AUC values for 1-, 3-, and 5-year OS were 0.847, 0.908, and 0.942.

Our research identified the significant impact of NRGs on immunity and prognosis in TNBC. These findings were expected to provide a new strategy for personalize the treatment of TNBC and improve its clinical benefit.

• Biomarkers, Tumor/genetics
• DNA Copy Number Variations
• Humans
• Necroptosis/genetics
• Nerve Tissue Proteins/genetics
• Prognosis
• Receptors, G-Protein-Coupled/genetics
• Receptors, Neurotransmitter
• Triple Negative Breast Neoplasms/pathology
• Tumor Microenvironment/genetics

• National Natural Science Foundation of China

We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA).

Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA.

Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database.

Three genes could predict prognosis and evaluate the response to ICB in BLCA.

• adrenocortical carcinoma
• immune microenvironment infiltration
• prognosis
• tumor mutation burden

• Adrenal Cortex Neoplasms/genetics
• Adrenocortical Carcinoma/genetics
• Biomarkers, Tumor/genetics
• Humans
• Killer Cells, Natural
• Mutation
• Tumor Microenvironment/genetics

Background: Heat shock protein B8 (HSPB8) is expressed in various cancers. However, the functional and clinicopathological significance of HSPB8 expression in bladder cancer (BC) remains unclear. The present study sought to elucidate the clinicopathological features and prognostic value of HSPB8 in BC.

Methods: A BC RNA-seq data set was obtained from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) database, and the external validation dataset GSE130598 was downloaded from the GEO database. Samples in the TCGA-BLCA were categorized into two groups based on HSPB8 expression. Differentially expressed genes (DEGs) between the two groups were defined as HSPB8 co-expressed genes. Gene set enrichment analysis (GSEA), protein-protein interaction networks, and mRNA-microRNA (miRNA) interaction networks were generated to predict the function and interactions of genes that are co-expressed with HSPB8. Finally, we examined immune cell infiltration and constructed a survival prediction model for BC patients.

Results: The expression level of HSBP8 has a significant difference between cancer samples and normal samples, and its diagnosis effect was validated by the ROC curve. 446 differential expressed genes between HSBP8 high-expression and HSBP8 low expression groups were identified. Gene enrichment analysis and GSEA analysis show that these differential gene functions are closely related to the occurrence and development of BC and the metabolic pathways of BC. The cancer-related pathways included Cytokine-cytokine receptor Interaction, Focal adhesion, and Proteoglycans in cancer. PPI and protein-coding gene-miRNA network visualized the landscape for these tightly bounded gene interactions. Immune cell infiltration shows that B cells, CD4+T cells, and CD8+T cells have strongly different infiltration levels between the HSBP8 high exp group and low exp group. The survival prediction model shows that HSBP8 has strong prognosis power in the BLCA cohort.

Conclusion: Identifying DEGs may enhance understanding of BC development’s causes and molecular mechanisms. HSPB8 may play an essential role in BC progression and prognosis and serve as a potential biomarker for BC treatment.

• HSPB8
• biomarker
• bladder cancer
• microarray
• prognosis

There is evidence suggesting that immune genes play pivotal roles in the development and progression of colorectal cancer (CRC). Colorectal carcinoma patient data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) were randomly classified into a training set, a test set, and an external validation set. Differentially expressed gene (DEG) analyses, univariate Cox regression, and the least absolute shrinkage and selection operator (LASSO) were used to identify survival-associated immune genes and develop a prognosis model. Receiver operating characteristic (ROC) analysis and principal component analysis (PCA) were used to evaluate the discrimination of the risk models. The model genes predicted were verified using the Human Protein Atlas (HPA) databases, colorectal cell lines, and fresh CRC and adjacent tissues. To understand the relationship between IRGs and immune invasion and the TME, we analyzed the content of immune cells and scored the TME using CIBERSORT and ESTIMATE algorithms. Finally, we predicted the potential sensitive chemotherapeutic drugs in different risk score groups by the Genomics of Drug Sensitivity in Cancer (GDSC). A total of 491 IRGs were screened, and 14 IRGs were identified to be significantly related to overall survival (OS) and applied to construct an immune-related gene (IRG) prognostic signature (IRGSig) for CRC patients. Calibration plots showed that nomograms have powerful predictive ability. PCA and ROC analysis further verified the predictive value of this fourteen-gene prognostic model in three independent databases. Furthermore, we discovered that the tumor microenvironment changed significantly during the tumor development process, from early to middle to late stage, which may be an essential factor for tumor deterioration. Finally, we selected six commonly used chemotherapeutic drugs that have the potential to be useful in the treatment of CRC. Altogether, immune genes were used to construct a prognosis model for CRC patients, and a variety of methods were used to test the accuracy of this model. In addition, we explored the immune mechanisms of CRC through immune cell infiltration and TME in CRC. Furthermore, we assessed the therapeutic sensitivity of many commonly used chemotherapeutic medicines in individuals with varying risk factors. Finally, the immune risk model and immune mechanism of CRC were thoroughly investigated in this paper.

• CRC
• GDSC
• IRGSig
• LASSO analysis
• PCA
• TME

Tumor mutational burden (TMB) and APOBEC mutational signatures are potential prognostic markers in patients with advanced urothelial carcinoma (aUC). Their utility in predicting outcomes to specific therapies in aUC warrants additional study.

We retrospectively reviewed consecutive UC cases assessed with UCSF500, an institutional assay that uses hybrid capture enrichment of target DNA to interrogate 479 common cancer genes. Hypermutated tumors (HM), defined as having TMB ≥10 mutations/Mb, were also assessed for APOBEC mutational signatures, while non-HM (NHM) tumors were not assessed due to low TMB. The logrank test was used to determine if there were differences in overall survival (OS) and progression-free survival (PFS) among patient groups of interest.

Among 75 aUC patients who had UCSF500 testing, 46 patients were evaluable for TMB, of which 19 patients (41%) had HM tumors and the rest had NHM tumors (27 patients). An additional 29 patients had unknown TMB status. Among 19 HM patients, all 16 patients who were evaluable for analysis had APOBEC signatures. HM patients (N=19) were compared with NHM patients (N=27) and had improved OS from diagnosis (125.3 months vs 35.7 months, p=0.06) but inferior OS for patients treated with chemotherapy (7.0 months vs 13.1 months, p=0.04). Patients with APOBEC (N=16) were compared with remaining 56 patients, comprised of 27 NHM patients and 29 patients with unknown TMB, showing APOBEC patients to have improved OS from diagnosis (125.3 months vs 44.5 months, p=0.05) but inferior OS for patients treated with chemotherapy (7.0 months vs 13.1 months, p=0.05). Neither APOBEC nor HM status were associated with response to immunotherapy.

In a large, single-institution aUC cohort assessed with UCSF500, an institutional NGS panel, HM tumors were common and all such tumors that were evaluated for mutational signature analysis had APOBEC signatures. APOBEC signatures and high TMB were prognostic of improved OS from diagnosis and both analyses also predicted inferior outcomes with chemotherapy treatment.

There has been no report to use camrelizumab with chemotherapy for advanced bladder cancer patients with positive programmed death-ligand 1 (PD-L1) expression and high tumor mutational burden (TMB). More effective predictors of bladder cancer immunotherapy have yet to be explored, and the combination of multiple factors may be more predictive than a single factor.

We report the case of a 74-year-old male patient with recurrent metastatic bladder cancer, which demonstrated positive PD-L1 expression and high TMB. The immune checkpoint inhibitor camrelizumab was administered to the patient in combination with gemcitabine and cisplatin. The patient achieved a partial response with a progression-free survival of 11 mo.

This is the first report to use camrelizumab with chemotherapy for advanced bladder cancer patients with positive PD-L1 expression and high TMB.

• Programmed death-ligand 1
• Tumor mutational burden
• Bladder cancer
• Camrelizumab
• Next-generation sequencing
• Case report

• genome instability
• hypoxia
• microsatellites
• mutation burden
• tumor microenvironment

Background: Tumor microenvironment, especially infiltrating immune cell, is crucial for solid tumors including glioma. However, the hub genes as well as their effects on patient prognosis and immunotherapy efficacy remain obscure.

Methods: We employed a total of 952 lower grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases, and 24 samples in our hospital for subsequent analyses. Abundances of immune infiltrates were evaluated using CIBERSORT and ImmuCellAI. Their correlations with prognosis were assessed by log-rank test. Immune infiltration-related hub genes were obtained from overlapped differential expressed genes (DEGs) in various subsets of survival-related immune cell types. The risk signature was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. The functional analyses were estimated by GVSA and Gene Set Enrichment Analysis (GSEA) algorithms. And protein–protein interaction enrichment analysis was carried out with the Metascape database integrating STRING, BioGrid, OmniPath, and InWeb_IM.

Results: Among the 21 infiltrates, the abundances of five immune infiltrates were correlated with overall survival (OS) in LGG patients. Higher abundances of naïve CD4+ T cells (p = 0.002), activated mast cells (p = 0.015), and monocytes (p = 0.014) were correlated with better prognosis, while higher abundances of resting memory CD4+ T cells (p = 0.015) and M1 macrophages (p = 0.020) correlated with poorer OS. We finally obtained 44 hub genes and constructed an immune infiltration-related signature (IIRS). The IIRS correlates with clinicopathological characteristics and exhibited potential power in predicting the immunotherapy efficacy. The IRRS correlates with cancer related pathways, especially “epithelial-mesenchymal transition (EMT),” and cytotoxic T lymphocytes.

Conclusion: Our study constructed and validated a novel signature for risk stratification and prediction of immunotherapy response in grade II and III gliomas, which was closely associated with glioma immune microenvironment and could serve as a promising prognostic biomarker for glioma patients.

• function
• glioma
• immune infiltration
• immunotherapy
• prognosis

To explore the signature function of the tumor mutational burden (TMB) and potential biomarkers in prostate cancer (PCa), transcriptome profiles, somatic mutation data, and clinicopathologic feature information were downloaded from The Cancer Genome Atlas (TCGA) database. R software package was used to generate a waterfall plot to summarize the specific mutation information and calculate the TMB value of PCa. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to select the hub genes related to the TMB from the ImmPort network to build a risk score (RS) model to evaluate prognostic values and plot Kaplan–Meier (K-M) curves to predict PCa patients survival. The results showed that PCa patients with a high TMB exhibited higher infiltration of CD8+ T cells and CD4+ T cells and better overall survival (OS) than those with a low TMB. The anti-Mullerian hormone (AMH), baculoviral IAP repeat-containing 5 (BIRC5), and opoid receptor kappa 1 (OPRK1) genes were three hub genes and their copy number variation (CNV) was relatively likely to affect the infiltration of immune cells. Moreover, PCa patients with low AMH or BIRC5 expression had a longer survival time and lower cancer recurrence, while elevated AMH or BIRC5 expression favored PCa progression. In contrast, PCa patients with low OPRK1 expression had poorer OS in the early stage of PCa and a higher recurrent rate than those with high expression. Taken together, these results suggest that the TMB may be a promising prognostic biomarker for PCa and that AMH, OPRK1, and BIRC5 are hub genes affecting the TMB; AMH, OPRK1, and BIRC5 could serve as potential immunotherapeutic targets for PCa treatment.

• biomarker
• hub gene
• immune cell infiltration
• prostate cancer
• tumor mutational burden

Within the endocrine system, thyroid cancer (THCA) is the most typical malignant tumor. Tumor-infiltrating immune cells play vital roles in tumor progression, recurrence, metastasis as well as response to immunotherapy. However, THCA’s immune infiltrative landscape is still not clarified. Therefore, we utilized two statistical algorithms to investigate the immune cell infiltration (ICI) landscape of 505 THCA samples and defined three ICI immune subtypes. The ICI scores were calculated using principal-component analysis. Increased tumor mutation burden (TMB) and immune-related signaling pathways were associated to a high ICI score. The high ICI score group indicated a relatively longer overall survival (OS) than the low ICI score group. Most immune checkpoint-related and immune activation-related genes were considerably upregulated in the ICI high group, which indicates stronger immunogenicity and a greater likelihood of benefiting from immunotherapy. In two cohort studies of patients receiving immunotherapy, high-ICI-score group showed notable therapeutic effects and clinical advantages compared to those with lower ICI scores. These results demonstrate that ICI score acts as an effective prognostic indicator and predictor of response to immunotherapy.

• immunotherapy
• infiltration
• landscape
• prediction
• prognosis
• thyroid cancer

Bladder cancer is the second most common malignant tumor in the urogenital system. The research investigated the prognostic role of immune‐related long non‐coding RNA (lncRNA) in bladder cancer.

We extracted 411 bladder cancer samples from The Cancer Genome Atlas database. Single‐sample gene set enrichment analysis was employed to assess the immune cell infiltration of these samples. We recognized differentially expressed lncRNAs between tumors and paracancerous tissues, and differentially expressed lncRNAs between the high and low immune cell infiltration groups. Venn diagram analysis detected differentially expressed lncRNAs that intersected the above groups. LncRNAs with prognostic significance were identified by regression analysis. Multivariate Cox analysis was used to establish the risk score model. Then we established and evaluated the nomogram. Additionally, we performed gene set enrichment analysis to explore the potential functions of the screened lncRNAs in tumor pathogenesis.

Three hundred and twenty differentially expressed lncRNAs were recognized. We randomly divided patients into the training data set and the testing data set at a 2: 1 ratio. In the training data set, 9 immune‐related lncRNAs with prognostic significance were identified. The risk score model was constructed to classify patients as high‐ and low‐risk cohorts. Patients in the low‐risk cohort had better survival outcomes than those in the high‐risk cohort. The nomogram was established based on the indicators including age, gender, tumor‐node‐metastases stage, and risk score. The model's predictive performance was confirmed by the receiver operating characteristic curve analysis, concordance index method, calibration curve, and decision curve analysis. The testing data set also achieved similar results. Bioinformatics analysis suggested that the 9‐lncRNA signature was involved in the modulation of various immune responses, antigen processing and presentation, and T cell receptor signaling pathway.

Our study uncovered the prognostic value of immune‐related lncRNAs for bladder cancer and showed that they may regulate tumor pathogenesis in various ways.

• TCGA
• bladder cancer
• immune
• lncRNA
• prognostic model

• Chinese
• bladder urothelial carcinoma
• deep sequencing
• genomic alteration
• tumor mutation burden

Reliable and affordable prognostic and predictive biomarkers for urothelial carcinoma treated with immunotherapy may allow patients' outcome stratification and drive therapeutic options. The SAUL trial investigated the safety and efficacy of atezolizumab in a real-world setting on 1004 patients with locally advanced or metastatic urothelial carcinoma who progressed to one to three prior systemic therapies.

Using the SAUL Italian cohort of 267 patients, we investigated the prognostic role of neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) and the best performing one of these in combination with programmed death-ligand 1 (PD-L1) with or without lactate dehydrogenase (LDH). Previously reported cut-offs (NLR >3 and NLR >5; SII >1375) in addition to study-defined ones derived from receiver operating characteristic (ROC) analysis were used.

The cut-off values for NLR and SII by the ROC analysis were 3.65 (sensitivity 60.4; specificity 63.0) and 884 (sensitivity 64.4; specificity 67.5), respectively. The median overall survival (OS) was 14.7 months for NLR <3.65 [95% confidence interval (CI) 9.9-not reached (NR)] versus 6.0 months for NLR ≥3.65 (95% CI 3.9-9.4); 14.7 months for SII <884 (95% CI 10.6-NR) versus 6.0 months for SII ≥884 (95% CI 3.7-8.6). The combination of SII, PD-L1, and LDH stratified OS better than SII plus PD-L1 through better identification of patients with intermediate prognosis (77% versus 48%, respectively). Multivariate analyses confirmed significant correlations with OS and progression-free survival for both the SII + PD-L1 + LDH and SII + PD-L1 combinations.

The combination of immune-inflammatory biomarkers based on SII, PD-L1, with or without LDH is a potentially useful and easy-to-assess prognostic tool deserving validation to identify patients who may benefit from immunotherapy alone or alternative therapies.

•

Reliable biomarkers for immunotherapy may assist in treatment decision making and clinical trial design and interpretation.

• LDH
• PD-1
• PD-L1
• biomarker
• immune-checkpoint inhibitor
• immunotherapy
• neutrophil-to-lymphocyte ratio (NLR)
• prognostic
• systemic immune-inflammation index (SII)
• urothelial carcinoma

• GSEA pathway analysis
• drug sensitivity
• immune infiltration
• triple-negative breast cancer
• tumor mutation burden

In order to explore the prognosis of tumor mutation burden (TMB) and the relationship with tumor infiltrating immune cells in hepatocellular carcinoma (HCC), we downloaded somatic mutation data and transcriptome profiles of 376 HCC patients from The Cancer Genome Atlas (TCGA) cohort. We divided the samples into high-TMB and low-TMB groups. A higher TMB level indicated improved overall survival (OS) and was associated with early pathological stages. One hundred and nine differentially expressed genes (DEGs) were identified in HCC. Moreover, based on four hub TMB-related signatures, we constructed a TMB Prognostic model (TMBPM) that possessed good predictive value with area under curve (AUC) of 0.701. HCC patients with higher TMBPM scores showed worse OS outcomes (p < 0.0001). Moreover, DCs subsets not only revealed higher infiltrating abundance in the high-TMB group, but also correlated with worse OS and hazard risk for high-TMB patients in HCC. Meanwhile, CD8+ T cells and B cells were associated with improved survival outcomes. In sum, high TMB indicates good prognosis for HCC and promotes HCC immune infiltration. Hence, DCs and the four hub TMB-related signatures can be used for predicting the prognosis in HCC as supplements to TMB.

• The Cancer Genome Atlas
• hepatocellular carcinoma
• immune infiltration
• tumor mutation burden

• Endometrial cancer (EC)
• immune cells
• tumor mutational burden (TMB)

• WGCNA
• biomarker
• ceRNA
• tumor mutation burden
• tumor-infiltrating immune cells

• Clinical
• Gene
• Prostate cancer
• Tumour mutational burden

• biomarkers
• hepatocellular carcinoma
• immune infiltration
• prognosis
• tumor mutation burden

• Hepatocellular carcinoma (HCC)
• Immune microenvironment (IME)
• Nomogram
• Prognosis
• Tumour mutation burden (TMB)

• OSM
• TP53
• cholangiocarcinoma
• immune infiltration
• prognosis

• Bile Duct Neoplasms/genetics
• Bile Duct Neoplasms/immunology
• Bile Duct Neoplasms/mortality
• Cholangiocarcinoma/genetics
• Cholangiocarcinoma/immunology
• Cholangiocarcinoma/mortality
• Computational Biology
• Gene Expression Profiling
• Humans
• Lymphocytes, Tumor-Infiltrating/immunology
• Lymphocytes, Tumor-Infiltrating/metabolism
• Oncostatin M/biosynthesis
• Prognosis
• Tumor Suppressor Protein p53/genetics

• Immune infiltrate
• Survival
• TCGA
• Tumor mutation burden (TMB)
• skin cutaneous melanoma (SKCM)

• Epithelial-mesenchymal transition
• Gastric cancer
• Immune checkpoint blockade
• Immune infiltration
• TGFB2
• Tumor mutation burden

• epithelial ovarian cancer
• immune infiltrates
• prognostic signature
• tumor mutational burden