Hot or Not: Tumor Mutational Burden (TMB) as a Biomarker of Immunotherapy Response in Genitourinary Cancers

Combining Mass Cytometry Data by CyTOFmerge Reveals Additional Cell Phenotypes in the Heterogeneous Ovarian Cancer Tumor Microenvironment: A Pilot Study

The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness.

Systematic pan-cancer analysis identified neuropilin 1 as an immunological and prognostic biomarker

Neuropilin 1 (NRP1) is a transmembrane glycoprotein, nontyrosine kinase receptor that plays an important role in axonal growth and angiogenesis in the nervous system. Although currently more and more studies have shown that NRP1 plays an important role in some cancers, no systematic pan-cancer analysis of NRP-1 has been performed to date. Therefore, we aimed to investigate the associated immune function and prognostic value of NRP1 in 33 tumors of various cancer types. In this study, based on The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, Genotype Tissue Expression, cBioportal for cancer genomics, and Human Protein Atlas (HPA databases), various bioinformatics analysis methods were used to investigate the potential carcinogenic effects of NRP1 activation, pan-cancer analysis of NRP1 expression, and the relationship between NRP1 expression and prognosis indicators including overall survival, disease-specific survival, disease-free interval, and progression-free interval, tumor mutational burden (TMB), and microsatellite instability (MSI). The results showed that NRP1 was highly expressed in most tumors. In addition, NRP1 was found to be positively or negatively correlated with the prognosis of different tumors. Also, the expression of NRP1 was associated with TMB and MSI in in 27 and 21 different types of tumors, respectively, and with DNA methylation in almost all the various types of tumors. The expression of the NRP1 gene was negatively correlated with the infiltration levels of most immune cells. In addition, the correlation between the level of immune cell infiltration and NRP1 expression varied according to immune cell subtype. Our study suggests that NRP1 plays an important role in tumor development and tumor immunity and could potentially be used as a prognostic indicator in a variety of malignancies.

Immunotherapy in Genitourinary Cancers: Role of Surgical Pathologist for Detection of Immunooncologic Predictive Factors

Genitourinary malignancies include a broad spectrum of distinct tumor entities occurring in the kidney, the urinary tract, the prostate, the adrenal glands, the penis, and testicles. Each tumor entity presents with unique biological characteristics, especially in terms of immunobiology. The immune landscape of genitourinary malignancies differs between immunoreactive tumors like urothelial carcinoma or carcinomas of the kidney, for which several immunotherapeutic treatment options have been approved in the past years. In contrast, prostate cancer presents with low immunogenicity and previous trials exploring immune checkpoint inhibitors and other immunotherapeutic agents did not proof substantial survival benefits. In this review, we are presenting a streamlined overview on the role of surgical pathologists within the contemporary practice of immune oncology. It includes current indications for pathologic programmed death-ligand 1 (PD-L1) assessment and important pathologic considerations on PD-L1 testing harmonization including interassay and algorithm variabilities. In addition, we will discuss emerging biomarkers beyond PD-L1 and their potential to predict immunotherapy responses including tumor mutational burden, microsatellite instability, gene expression signatures, and histologic factors.

Elevated PTTG1 predicts poor prognosis in kidney renal clear cell carcinoma and correlates with immunity

Background

PTTG1 has been reported to be linked with the prognosis and progression of various cancers, including kidney renal clear cell carcinoma (KIRC). In this article, we mainly investigated the associations between prognosis, immunity, and PTTG1 in KIRC patients.

Method

We downloaded transcriptome data from the TCGA-KIRC database. PCR and immunohistochemistry were used, respectively, to validate the expression of PTTG1 in KIRC at the cell line and the protein levels. Survival analyses as well as univariate or multivariate Cox hazard regression analyses were used to prove whether PTTG1 alone could affect the prognosis of KIRC. The most important point was to study the relationship between PTTG1 and immunity.

Results

The results of the paper revealed that the expression levels of PTTG1 were elevated in KIRC compared with para-cancerous normal tissues, validated by PCR and immunohistochemistry at the cell line and the protein levels (P < 0.05). High PTTG1 expression was related to shorter overall survival (OS) in patients with KIRC (P < 0.05). Through univariate or multivariate regression analysis, PTTG1 was confirmed to be an independent prognostic factor for OS of KIRC (P < 0.05), and its related seven pathways were obtained through gene set enrichment analysis (GSEA; P < 0.05). Moreover, tumor mutational burden (TMB) and immunity were found to be significantly connected with PTTG1 in KIRC (P < 0.05). Correlations between PTTG1 and immunotherapy responses implied that the low-PTTG1 group was more sensitive to immunotherapy (P < 0.05).

Conclusions

PTTG1 was closely associated with TMB or immunity, and it had a superior ability to forecast the prognosis of KIRC patients.

PSME2 identifies immune-hot tumors in breast cancer and associates with well therapeutic response to immunotherapy

Breast cancer (BrCa) is a heterogeneous disease, which leads to unsatisfactory prognosis in females worldwide. Previous studies have proved that tumor immune microenvironment (TIME) plays crucial roles in oncogenesis, progression, and therapeutic resistance in Breast cancer. However, biomarkers related to TIME features have not been fully discovered. Proteasome activator complex subunit 2 (PSME2) is a member of proteasome activator subunit gene family, which is critical to protein degradation mediated by the proteasome. In the current research, we comprehensively analyzed the expression and immuno-correlations of Proteasome activator complex subunit 2 in Breast cancer. Proteasome activator complex subunit 2 was significantly upregulated in tumor tissues but associated with well prognosis. In addition, Proteasome activator complex subunit 2 was overexpressed in HER2-positive Breast cancer but not related to other clinicopathological features. Interestingly, Proteasome activator complex subunit 2 was positively related to immune-related processes and identified immuno-hot TIME in Breast cancer. Specifically, Proteasome activator complex subunit 2 was positively correlated with immunomodulators, tumor-infiltrating immune cells (TIICs), immune checkpoints, and tumor mutation burden (TMB) levels. Moreover, the positive correlation between Proteasome activator complex subunit 2 and PD-L1 expression was confirmed in a tissue microarray (TMA) cohort. Furthermore, in an immunotherapy cohort of Breast cancer, patients with pathological complete response (pCR) expressed higher Proteasome activator complex subunit 2 compared with those with non-pathological complete response. In conclusion, Proteasome activator complex subunit 2 is upregulated in tumor tissues and correlated with the immuno-hot tumor immune microenvironment, which can be a novel biomarker for the recognition of tumor immune microenvironment features and immunotherapeutic response in Breast cancer.

Prognostic Value and Clinical Significance of FGFR Genomic Alterations (GAs) in Metastatic Urothelial Cancer Patients

Fibroblast growth factor receptor (FGFR) genomic alterations (GAs) represent an actionable target, key to the pathogenesis of some urothelial cancers (UCs). Though FGFR GAs are common in noninvasive UC, little is known about their role in the metastatic(m) setting and response to therapy. This study aimed to assess the impact of FGFR alterations on sensitivity to systemic treatments and survival and to validate Bajorin’s and Bellmunt’s prognostic scores in mUC patients according to their FGFR status. We retrospectively analyzed data from 98 patients with tumor-sequenced UC who received treatment between January 2010 and December 2020. Up to 77 developed metastatic disease and were deemed the study population. Twenty-six showed FGFR GAs. A trend toward a better response to cisplatin and checkpoint inhibitors was suggested favoring FGFR GA tumors. FGFR GA patients who received an FGFR inhibitor as first-line had poorer responses compared with other options (20% vs. 68.4%, p = 0.0065). Median PFS was 6 vs. 5 months in the FGFR GA vs. FGFR WT cohort (p = 0.71). Median OS was significantly worse in the FGFR GA vs. FGFR WT cohort (16.2 vs. 31.9 months, p = 0.045). Multivariate analyses deemed FGFR GAs as a factor independently associated with the outcome (HR 2.59 (95% CI 1.21–5.55)). Bajorin’s model correctly predicted clinical outcomes in the whole study population but not in FGFR GA cases. FGFR GAs are a relevant biomarker in mUC that could condition the response to systemic therapy. New prognostic models, including this molecular determination, should be designed and validated.

Prognosis Prediction Through an Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Data in Triple-Negative Breast Cancer

Background: Genomic and antigenic heterogeneity pose challenges in the precise assessment of outcomes of triple-negative breast cancer (TNBC) patients. Thus, this study was designed to investigate the cardinal genes related to cell differentiation and tumor malignant grade to advance the prognosis prediction in TNBC patients through an integrated analysis of single-cell and bulk RNA-sequencing (RNA-seq) data.

Methods: We collected RNA-seq and microarray data of TNBC from two public datasets. Using single-cell pseudotime analysis, differentially expressed genes (DEGs) among trajectories from 1534 cells of 6 TNBC patients were identified as the potential genes crucial for cell differentiation. Furthermore, the grade- and tumor mutational burden (TMB)-related DEGs were explored via a weighted correlation network analysis using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Subsequently, we utilized the DEGs to construct a prognostic signature, which was validated using another independent dataset. Moreover, as gene set variation analysis indicated the differences in immune-related pathways between different risk groups, we explored the immune differences between the two groups.

Results: A signature including 10 genes related to grade and TMB was developed to assess the outcomes of TNBC patients, and its prognostic efficacy was prominent in two cohorts. The low-risk group generally harbored lower immune infiltration compared to the high-risk group.

Conclusion: Cell differentiation and grade- and TMB-related DEGs were identified using single-cell and bulk RNA-seq data. A 10-gene signature for prognosis prediction in TNBC patients was constructed, and its performance was excellent. Interestingly, the signature was found to be closely related to tumor immune infiltration, which might provide evidence for the crucial roles of immune cells in malignant initiation and progression in TNBC.

Developing an Immune-Related Signature for Predicting Survival Rate and the Response to Immune Checkpoint Inhibitors in Patients With Glioma

Background: Glioma is one of the most aggressive cancer types affecting the central nerve system, with poor overall survival (OS) rates. The present study aimed to construct a novel immune-related signature to predict prognosis and the efficiency of immunotherapy in patients with glioma.

Methods: The mRNA expression data and other clinical information of patients with glioblastoma multiforme (GBM) and low grade glioma (LGG) were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. The immune-related genes were obtained from the Immunology Database and Analysis Portal database. Subsequently, an immune-related signature was created following the results obtained from the Least Absolute Shrinkage and Selection Operator regression model. To validate the predictability of the signature, Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves were created. Moreover, both univariate and multivariate analyses were carried out using the OS between this signature and other clinicopathologic factors, and a nomogram was constructed. In addition, the association between signature, immune cell infiltration, tumor mutation burden and immunophenoscore were determined.

Results: Results of the present study using 118 GBM and LGG samples uncovered 15 immune-related genes that were also differently expressed in glioma samples. These were subsequently used to construct the immune-related signature. This signature exhibits the ability to predict prognosis, the infiltration of immune cells in the tumor microenvironment and the response of patients with glioma to immunotherapy.

Conclusion: Results of the present study demonstrated that the aforementioned novel immune-related signature may accurately predict prognosis and the response of patients with glioma to immunotherapy.

Construction of an immune-related lncRNA signature pair for predicting oncologic outcomes and the sensitivity of immunosuppressor in treatment of lung adenocarcinoma

Background

Although immunotherapy has shown clinical activity in lung adenocarcinoma (LUAD), LUAD prognosis has been a perplexing problem. We aimed to construct an immune-related lncRNA pairs (IRLPs) score for LUAD and identify what immunosuppressor are appropriate for which group of people with LUAD.

Methods

Based on The Cancer Genome Atlas (TCGA)-LUAD cohort, IRLPs were identified to construct an IRLPs scoring system by Cox regression and validated in the Gene Expression Omnibus (GEO) dataset using log-rank test and the receiver operating characteristic curve (ROC). Next, we used spearman’s correlation analysis, t-test, signaling pathways analysis and gene mutation analysis to explore immune and molecular characteristics in different IRLP subgroups. The “pRRophetic” package was used to predict the sensitivity of immunosuppressant.

Results

The IRLPs score was constructed based on eight IRLPs calculated as 2.12 × (MIR31HG|RRN3P2) + 0.43 × (NKX2-1-AS1|AC083949.1) + 1.79 × (TMPO-AS1|LPP-AS2) + 1.60 × (TMPO-AS1|MGC32805) + 1.79 × (TMPO-AS1|PINK1-AS) + 0.65 × (SH3BP5-AS1|LINC01137) + 0.51 × (LINC01004|SH3PXD2A-AS1) + 0.62 × (LINC00339|AGAP2-AS1). Patients with a lower IRLPs risk score had a better overall survival (OS) (Log-rank test P_{TCGA train dataset} < 0.001, P_{TCGA test dataset} = 0.017, P_{GEO dataset} = 0.027) and similar results were observed in the AUCs of TCGA dataset and GEO dataset (AUC _{TCGA train dataset} = 0.777, AUC _{TCGA test dataset} = 0.685, AUC _{TCGA total dataset} = 0.733, AUC _{GEO dataset} = 0.680). Immune score (Cor = -0.18893, P < 0.001), stoma score (Cor = -0.24804, P < 0.001), and microenvironment score (Cor = -0.22338, P < 0.001) were significantly decreased in the patients with the higher IRLP risk score. The gene set enrichment analysis found that high-risk group enriched in molecular changes in DNA and chromosomes signaling pathways, and in this group the tumor mutation burden (TMB) was higher than in the low-risk group (P = 0.0015). Immunosuppressor methotrexate sensitivity was higher in the high-risk group (P = 0.0052), whereas parthenolide (P < 0.001) and rapamycin (P = 0.013) sensitivity were lower in the high-risk group.

Conclusions

Our study established an IRLPs scoring system as a biomarker to help in the prognosis, the identification of molecular and immune characteristics, and the patient-tailored selection of the most suitable immunosuppressor for LUAD therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02043-4.

Avelumab maintenance in advanced urothelial carcinoma: biomarker analysis of the phase 3 JAVELIN Bladder 100 trial

In a recent phase 3 randomized trial of 700 patients with advanced urothelial cancer (JAVELIN Bladder 100; NCT02603432 ), avelumab/best supportive care (BSC) significantly prolonged overall survival relative to BSC alone as maintenance therapy after first-line chemotherapy. Exploratory biomarker analyses were performed to identify biological pathways that might affect survival benefit. Tumor molecular profiling by immunohistochemistry, whole-exome sequencing and whole-transcriptome sequencing revealed that avelumab survival benefit was positively associated with PD-L1 expression by tumor cells, tumor mutational burden, APOBEC mutation signatures, expression of genes underlying innate and adaptive immune activity and the number of alleles encoding high-affinity variants of activating Fcγ receptors. Pathways connected to tissue growth and angiogenesis might have been associated with reduced survival benefit. Individual biomarkers did not comprehensively identify patients who could benefit from therapy; however, multi-parameter models incorporating genomic alteration, immune responses and tumor growth showed promising predictive utility. These results characterize the complex biologic pathways underlying survival benefit from immune checkpoint inhibition in advanced urothelial cancer and suggest that multiple biomarkers might be needed to identify patients who would benefit from treatment.

Natural Killer Cells and Dendritic Cells: Expanding Clinical Relevance in the Non-Small Cell Lung Cancer (NSCLC) Tumor Microenvironment

Non-small cell lung cancer (NSCLC) is a major subtype of lung cancer that accounts for almost 85% of lung cancer cases worldwide. Although recent advances in chemotherapy, radiotherapy, and immunotherapy have helped in the clinical management of these patients, the survival rate in advanced stages remains dismal. Furthermore, there is a critical lack of accurate prognostic and stratification markers for emerging immunotherapies. To harness immune response modalities for therapeutic benefits, a detailed understanding of the immune cells in the complex tumor microenvironment (TME) is required. Among the diverse immune cells, natural killer (NK cells) and dendritic cells (DCs) have generated tremendous interest in the scientific community. NK cells play a critical role in tumor immunosurveillance by directly killing malignant cells. DCs link innate and adaptive immune systems by cross-presenting the antigens to T cells. The presence of an immunosuppressive milieu in tumors can lead to inactivation and poor functioning of NK cells and DCs, which results in an adverse outcome for many cancer patients, including those with NSCLC. Recently, clinical intervention using modified NK cells and DCs have shown encouraging response in advanced NSCLC patients. Herein, we will discuss prognostic and predictive aspects of NK cells and DC cells with an emphasis on NSCLC. Additionally, the discussion will extend to potential strategies that seek to enhance the anti-tumor functionality of NK cells and DCs.

Advances in the management of urothelial carcinoma: is immunotherapy the answer?

Introduction: Urothelial carcinoma (UC) is the second most common malignancy of the genitourinary system in the US, but mortality rate has not significantly improved despite advances in therapy. Over the past few years, the treatment landscape of non-muscle-invasive, muscle-invasive and metastatic UC (mUC) has evolved with the advent of immunotherapy.Areas covered: This paper summarizes current data and ongoing research into the use of immune checkpoint inhibitors (ICIs) in various settings of UC, including as maintenance therapy in chemotherapy-responsive mUC (with recent approval for avelumab in this setting) and as neoadjuvant and adjuvant therapies in localized and non-muscle-invasive disease. In addition, the authors review the combination of ICIs with chemotherapy, radiation and targeted therapies in an effort to increase response durability and efficacy.Expert opinion: While there has been a rapid expansion in clinical trials, platinum-based chemotherapy remains standard treatment in perioperative and first-line metastatic UC. The identification of biomarkers that can identify patients who will respond to ICIs has yielded conflicting results and has been largely non-generalizable to clinical practice. Further research into novel strategies and combinations with ICIs is needed to better characterize the role of immunotherapy in UC.

The Multiple Potential Biomarkers for Predicting Immunotherapy Response-Finding the Needle in the Haystack

Immune checkpoint inhibitors (ICIs) are being increasingly utilised in a variety of advanced malignancies. Despite promising outcomes in certain patients, the majority will not derive benefit and are at risk of potentially serious immune-related adverse events (irAEs). The development of predictive biomarkers is therefore critical to personalise treatments and improve outcomes. A number of biomarkers have shown promising results, including from tumour (programmed cell death ligand 1 (PD-L1), tumour mutational burden (TMB), stimulator of interferon genes (STING) and apoptosis-associated speck-like protein containing a CARD (ASC)), from blood (peripheral blood mononuclear cells (PBMCs), circulating tumour DNA (ctDNA), exosomes, cytokines and metal chelators) and finally the microbiome.