Whole-blood RNA transcript-based models can predict clinical response in two large independent clinical studies of patients with advanced melanoma treated with the checkpoint inhibitor, tremelimumab

A prospective multi-cohort study identifies and validates a 5-gene peripheral blood signature predictive of immunotherapy response in non-small cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape for non-small cell lung cancer (NSCLC). The variability in patient responses necessitates a blood-based, multi-cohort gene signature to predict ICI response in NSCLC.

METHODS

We performed transcriptomic profiling of peripheral blood mononuclear cell (PBMC) and buffy coat (BC) samples from three independent cohorts of NSCLC patients treated with ICIs: a retrospective cohort (PMBCR, n = 59), a retrospective validation cohort (BC, n = 44), and a prospective validation cohort (PBMCP, n = 42). We identified a 5-gene signature (UQCRB, NDUFA3, CDKN2D, FMNL1-DT, and APOL3) predictive of ICI response and validated its clinical utility in the prospective PBMCP cohort. Response was evaluated using RECIST criteria, and patients were followed up for progression-free survival (PFS) and overall survival (OS).

RESULTS

In the prospective PBMCP cohort, the 5-gene signature demonstrated high accuracy in stratifying patients into responders and non-responders (AUC = 0.89, 95% CI: 0.80-0.99). Predicted responders exhibited significantly longer PFS compared to predicted non-responders (median: 13.8 months vs. 4.2 months, HR = 0.21, 95% CI: 0.07-0.58, p = 0.005).

CONCLUSION

Our study confirms a 5-gene signature as a key biomarker for ICI response in NSCLC, enhancing treatment precision.

Immunogenic cell death signatures from on-treatment tumor specimens predict immune checkpoint therapy response in metastatic melanoma

Melanoma is a highly malignant form of skin cancer that typically originates from abnormal melanocytes. Despite significant advances in treating metastatic melanoma with immune checkpoint blockade (ICB) therapy, a substantial number of patients do not respond to this treatment and face risks of recurrence and metastasis. This study collected data from multiple datasets, including cohorts from Riaz et al., Gide et al., MGH, and Abril-Rodriguez et al., focusing on on-treatment samples during ICB therapy. We used the single-sample gene set enrichment analysis (ssGSEA) method to calculate immunogenic cell death scores (ICDS) and employed an elastic network algorithm to construct a model predicting ICB efficacy. By analyzing 18 ICD gene signatures, we identified 9 key ICD gene signatures that effectively predict ICB treatment response for on-treatment metastatic melanoma specimens. Results showed that patients with high ICD scores had significantly higher response rates to ICB therapy compared to those with low ICD scores. ROC analysis demonstrated that the AUC values for both the training and validation sets were around 0.8, indicating good predictive performance. Additionally, survival analysis revealed that patients with high ICD scores had longer progression-free survival (PFS). This study used an elastic network algorithm to identify 9 ICD gene signatures related to the immune response in metastatic melanoma. These gene features can not only predict the efficacy of ICB therapy but also provide references for clinical decision-making. The results indicate that ICD plays an important role in metastatic melanoma immunotherapy and that expressing ICD signatures can more accurately predict ICB treatment response and prognosis for on-treatment metastatic melanoma specimens, thus providing a basis for personalized treatment.

Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature

We employed single-cell analysis techniques, specifically the inferCNV method, to dissect the complex progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) through minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). This approach enabled the identification of Cluster 6, which was significantly associated with LUAD progression. Our comprehensive analysis included intercellular interaction, transcription factor regulatory networks, trajectory analysis, and gene set variation analysis (GSVA), leading to the development of the lung progression associated signature (LPAS). Interestingly, we discovered that the LPAS not only accurately predicts the prognosis of LUAD patients but also forecasts genomic alterations, distinguishes between 'cold' and 'hot' tumours, and identifies potential candidates suitable for immunotherapy. PSMB1, identified within Cluster 6, was experimentally shown to significantly enhance cancer cell invasion and migration, highlighting the clinical relevance of LPAS in predicting LUAD progression and providing a potential target for therapeutic intervention. Our findings suggest that LPAS offers a novel biomarker for LUAD patient stratification, with significant implications for improving prognostic accuracy and guiding treatment decisions.

Phase 1 dose expansion and biomarker study assessing first-in-class tumor microenvironment modulator VT1021 in patients with advanced solid tumors

BACKGROUND

Preclinical studies have demonstrated that VT1021, a first-in-class therapeutic agent, inhibits tumor growth via stimulation of thrombospondin-1 (TSP-1) and reprograms the tumor microenvironment. We recently reported data from the dose escalation part of a phase I study of VT1021 in solid tumors. Here, we report findings from the dose expansion phase of the same study.

METHODS

We analyzed the safety and tolerability, clinical response, and biomarker profile of VT1021 in the expansion portion of the phase I study (NCT03364400). Safety/tolerability is determined by adverse events related to the treatment. Clinical response is determined by RECIST v1.1 and iRECIST. Biomarkers are measured by multiplexed ion beam imaging and enzyme-linked immunoassay (ELISA).

RESULTS

First, we report the safety and tolerability data as the primary outcome of this study. Adverse events (AE) suspected to be related to the study treatment (RTEAEs) are mostly grade 1-2. There are no grade 4 or 5 adverse events. VT1021 is safe and well tolerated in patients with solid tumors in this study. We report clinical responses as a secondary efficacy outcome. VT1021 demonstrates promising single-agent clinical activity in recurrent GBM (rGBM) in this study. Among 22 patients with rGBM, the overall disease control rate (DCR) is 45% (95% confidence interval, 0.24-0.67). Finally, we report the exploratory outcomes of this study. We show the clinical confirmation of TSP-1 induction and TME remodeling by VT1021. Our biomarker analysis identifies several plasmatic cytokines as potential biomarkers for future clinical studies.

CONCLUSIONS

VT1021 is safe and well-tolerated in patients with solid tumors in a phase I expansion study. VT1021 has advanced to a phase II/III clinical study in glioblastoma (NCT03970447).

Clinical prognostication and immunotherapy response prediction in esophageal squamous cell carcinoma using the DNA damage repair-associated signature

BACKGROUND

The relationship between DNA damage repair (DDR) and cancer is intricately intertwined; however, its specific role in esophageal squamous cell carcinoma (ESCC) remains enigmatic.

METHODS

Employing single-cell analysis, we delineated the functionality of DDR-related genes within the tumor microenvironment (TME). A diverse array of scoring mechanisms, including AUCell, UCell, singscore, ssgsea, and AddModuleScore, were harnessed to scrutinize the activity of DDR-related genes across different cell types. Differential pathway alterations between high-and low-DDR activity cell clusters were compared. Furthermore, leveraging multiple RNA-seq datasets, we constructed a robust DDR-associated signature (DAS), and through integrative multiomics analysis, we explored differences in prognosis, pathways, mutational landscapes, and immunotherapy predictions among distinct DAS groups.

RESULTS

Notably, high-DDR activity cell subpopulations exhibited markedly enhanced cellular communication. The DAS demonstrated uniformity across multiple datasets. The low-DAS group exhibited improved prognoses, accompanied by heightened immune infiltration and elevated immune checkpoint expression. SubMap analysis of multiple immunotherapy datasets suggested that low-DAS group may experience enhanced immunotherapy responses. The "oncopredict" R package analyzed and screened sensitive drugs for different DAS groups.

CONCLUSION

Through the integration of single-cell and bulk RNA-seq data, we have developed a DAS associated with prognosis and immunotherapy response. This signature holds promise for the future stratification and personalized treatment of ESCC patients in clinical settings.

An advanced comprehensive muti-cell-type-specific model for predicting anti-PD-1 therapeutic effect in melanoma

Rationale: Immune checkpoint inhibitors targeting the programmed cell death (PD)-1/PD-L1 pathway have promise in patients with advanced melanoma. However, drug resistance usually results in limited patient benefits. Recent single-cell RNA sequencing studies have elucidated that MM patients display distinctive transcriptional features of tumor cells, immune cells and interstitial cells, including loss of antigen presentation function of tumor cells, exhaustion of CD8+T and extracellular matrix secreted by fibroblasts to prevents immune infiltration, which leads to a poor response to immune checkpoint inhibitors (ICIs). However, cell subgroups beneficial to anti-tumor immunity and the model developed by them remain to be further identified. Methods: In this clinical study of neoadjuvant therapy with anti-PD-1 in advanced melanoma, tumor tissues were collected before and after treatment for single-nucleus sequencing, and the results were verified using multicolor immunofluorescence staining and public datasets. Results: This study describes four cell subgroups which are closely associated with the effectiveness of anti-PD-1 treatment. It also describes a cell-cell communication network, in which the interaction of the four cell subgroups contributes to anti-tumor immunity. Furthermore, we discuss a newly developed predictive model based on these four subgroups that holds significant potential for assessing the efficacy of anti-PD-1 treatment. Conclusions: These findings elucidate the primary mechanism of anti-PD-1 resistance and offer guidance for clinical drug administration for melanoma.

Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Despite the rapid evolution of targeted therapies, immunotherapy with checkpoint inhibition (ICI) as well as combination therapies, the cure of metastatic ccRCC (mccRCC) is infrequent, while the optimal use of the various novel agents has not been fully clarified. With the different treatment options, there is an essential need to identify biomarkers to predict therapeutic efficacy and thus optimize therapeutic approaches. This study seeks to explore the diversity in mRNA expression profiles of inflammation and immunity-related circulating genes for the development of biomarkers that could predict the effectiveness of immunotherapy-based treatments using ICIs for individuals with mccRCC. Gene mRNA expression was tested by the RT2 profiler PCR Array on a human cancer inflammation and immunity crosstalk kit and analyzed for differential gene expression along with a machine learning approach for sample classification. A number of mRNAs were found to be differentially expressed in mccRCC with a clinical benefit from treatment compared to those who progressed. Our results indicate that gene expression can classify these samples with high accuracy and specificity.

Whole-Blood Gene Expression Profiles Correlate with Response to Immune Checkpoint Inhibitors in Patients with Metastatic Renal Cell Carcinoma

In metastatic renal cell carcinoma (mRCC), the clinical response to immune checkpoint inhibitors (ICIs) is limited in a subset of patients and the need exists to identify non-invasive, blood-based, predictive biomarkers for responses. We performed RNA sequencing using whole-blood samples prospectively collected from 49 patients with mRCC prior to the administration of ipilimumab (IPI) and/or nivolumab (NIVO) to determine whether gene expression profiles were associated with responses. An analysis from 33 mRCC patients with complete responses (n = 5), partial responses (n = 14), and progressive disease (n = 14) showed 460 differentially expressed genes (DEGs) related to immune responses between the responder and non-responder groups with significant differences. A set of 14 genes generated from the initial 460 DEGs accurately classified responders (sensitivity 94.7% and specificity 50.0%) while consensus clustering defined clusters with significantly differing response rates (92.3% and 35.0%). These clustering results were replicated in a cohort featuring 16 additional SD patients (49 total patients): response rates were 95.8% and 48.0%. Collectively, whole-blood gene expression profiles derived from mRCC patients treated with ICIs clearly differed by response and hierarchical clustering using immune response DEGs accurately classified responder patients. These results suggest that such screening may serve as a predictor for ICI responses in mRCC patients.

Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Reveals a Tissue-Resident Macrophage-Related Signature for Predicting Immunotherapy Response in Breast Cancer Patients

Immune checkpoint therapy (ICT) is among the widely used treatments for breast cancer (BC), but most patients do not respond to ICT and the availability of the predictive biomarkers is limited. Emerging evidence indicates that tissue-resident macrophages (RTMs) inhibit BC progression, suggesting that their presence may predict immunotherapy response. A single-cell RNA-sequencing analysis of BC samples was performed to identify five RTM clusters with a mixed phenotype of M1-M2 macrophages. The comprehensive results showed that a high score of each RTM cluster was associated with a high infiltration of CD8+ T cells, M1 macrophages, and dendritic cells, and improved overall survival. In addition, a low score of each RTM cluster was associated with a high infiltration of M0 macrophages, naïve B cells and Tregs, and poor overall survival. Gene signatures from each RTM cluster were significantly enriched in responders compared with nonresponders. Each RTM cluster expression was significantly higher in responders than in nonresponders. The analyses of bulk RNA-seq datasets of BC samples led to identification and validation of a gene expression signature, named RTM.Sig, which contained the related genes of RTM clusters for predicting response to immunotherapy. This study highlights RTM.Sig could provide a valuable tool for clinical decisions in administering ICT.

NETest: serial liquid biopsies in gastroenteropancreatic NET surveillance

Objective

Up to now, serial NETest measurements in individuals assessing the disease course of gastroenteropancreatic neuroendocrine tumors (GEPNETs) at long-term follow-up and treatment response were not studied.

Design

The study was a longitudinal validation study of serial NETest measurements - a blood-based gene expression signature - in 132 patients with GEPNETs on therapy or watch-and-wait strategy.

Methods

Serial samples were collected during 46 (range: 6-71) months of follow-up. NETest scores were compared with Response Evaluation Criteria in Solid Tumors version 1.1-defined treatment response (e.g. no evidence of disease (NED), stable disease (SD) or progressive disease (PD)).

Results

Consecutive NETest scores fluctuated substantially (range: 0-100) over time in individuals with SD (n = 28) and NED (n = 30). Follow-up samples were significantly higher in SD (samples 3-5) and NED subgroups (samples 2-5) compared with baseline results, without changes in imaging. In 82% of untreated patients with PD, consecutive NETest scores consistently remained high. In patients undergoing systemic treatment, the median pre-treatment NETest score in treatment-responders was 76.5 (n = 22) vs 33 (n = 12) in non-responders (P = 0.001). Patients with low pre-treatment scores had 21 months reduced progression-free survival (10 vs 31 months; P = 0.01). The accuracy of the NETest for treatment response prediction was 0.73 (P = 0.009).

Conclusion

In patients not undergoing treatment, consecutive low NETest scores are associated with indolent behavior. Patients who develop PD exhibit elevated scores. Elevated results have important predictive value for treatment responsiveness and could be used for individualizing decisions on systemic therapy. The clinical value of follow-up NETest scores for patients who choose to watch and wait requires further study.

An immunotherapy response prediction model derived from proliferative CD4+ T cells and antigen-presenting monocytes in ccRCC

Most patients with clear cell renal cell carcinoma (ccRCC) have an impaired response to immune checkpoint blockade (ICB) therapy. Few biomarkers can predict responsiveness, and there is insufficient evidence to extend them to ccRCC clinical use. To explore subtypes and signatures of immunocytes with good predictive performance for ICB outcomes in the ccRCC context, we reanalyzed two ccRCC single-cell RNA sequencing (scRNA-seq) datasets from patients receiving ICB treatment. A subtype of proliferative CD4⁺ T cells and regulatory T cells and a subtype of antigen-presenting monocytes that have good predictive capability and are correlated with ICB outcomes were identified. These findings were corroborated in independent ccRCC ICB pretreatment bulk RNA-seq datasets. By incorporating the cluster-specific marker genes of these three immunocyte subtypes, we developed a prediction model, which reached an AUC of 93% for the CheckMate cohort (172 samples). Our study shows that the ICB response prediction model can serve as a valuable clinical decision-making tool for guiding ICB treatment of ccRCC patients.

Transcriptomic datasets of cancer patients treated with immune-checkpoint inhibitors: a systematic review

The availability of immune-checkpoint inhibitors (ICI) in the last decade has resulted in a paradigm shift in certain areas of oncology. Patients can be treated either by a monotherapy of anti-CTLA-4 (tremelimumab or ipilimumab), anti-PD-1 (nivolumab or pembrolizumab), or anti-PD-L1 (avelumab or atezolizumab or durvalumab) or as combination therapy of anti-CTLA-4 and anti-PD-1. To maximize the clinical treatment benefit of cancer immunotherapy, the prediction of the actual immune response by the identification and application of clinically useful biomarkers will be required. Whole transcriptomic datasets of patients with ICI treatment could provide the basis for large-scale discovery and ranking of such potential biomarker candidates. In this review, we summarize currently available transcriptomic data from different biological sources (whole blood, fresh-frozen tissue, FFPE) obtained by different methods (microarray, RNA-Seq, RT-qPCR). We directly include only results from clinical trials and other investigations where an ICI treatment was administered. The available datasets are grouped based on the administered treatment and we also summarize the most important results in the individual cohorts. We discuss the limitations and shortcomings of the available datasets. Finally, a subset of animal studies is reviewed to provide an overview of potential in vivo ICI investigations. Our review can provide a swift reference for researchers aiming to find the most suitable study for their investigation, thus saving a significant amount of time.

Oncolytic Activity of a Chimeric Influenza A Virus Carrying a Human CTLA4 Antibody in Hepatocellular Carcinoma

Oncolytic virotherapy belongs to a kind of active immunotherapy, which could trigger a potent antitumor immune response, showing great potential in clinical application. OVs could induce immune responses through the dual mechanisms of selective tumor killing without destroying normal tissues and induction of systemic antitumor immunity. In this study, we successfully rescued a chimeric oncolytic influenza virus carrying a human CTLA4 antibody in the background of the A/PR/8/34 (PR8) virus. The chimeric virus, called rFlu-huCTLA4, contained the heavy and light chains of the human CTLA4 antibody in the PB1 and PA segments of the PR8 virus, respectively. The first-generation hemagglutination (HA) titers of the rFlu-huCTLA4 virus ranged from 2⁷ to 2⁸, which could be passaged stably in specific pathogen-free (SPF) chicken embryos from P1 to P5. The morphology and size distribution of the chimeric virus were consistent with those of the wt influenza virus. The rFlu-huCTLA4 virus could effectively replicate in various cells in time- and dose-dependent manners. ELISA assay revealed that the secreted huCTLA4 antibody levels in chicken embryos increased gradually over time. Furthermore, MTS and crystal violet analysis showed that the selective cytotoxicity of the virus was higher in hepatocellular carcinoma cells (HepG2 and Huh7) than in normal liver cells (MIHA). In vivo experiments displayed that intratumoral injection with rFlu-huCTLA4 reduced tumor growth and increased the survival of mice compared with the PR8 group. More importantly, in the rFlu-huCTLA4 group, we found that CD4+ and CD8 +T cells were significantly increased in tumor-bearing BALB/c mice. Taken together, these findings demonstrated that the chimeric oncolytic virus rFlu-huCTLA4 could selectively destroy hepatocellular carcinoma cells in vitro and in vivo and may provide a promising clinical strategy for targeted immunotherapy of HCC with the oncolytic flu virus.

Integrated transcriptional-phenotypic analysis captures systemic immunomodulation following antiangiogenic therapy in renal cell carcinoma patients

BACKGROUND

The combination of immune checkpoint blockade (ICB) with standard therapies is becoming a common approach for overcoming resistance to cancer immunotherapy in most human malignancies including metastatic renal cell carcinoma (mRCC). In this regard, insights into the immunomodulatory properties of antiangiogenic agents may help designing multidrug schedules based on specific immune synergisms.

METHODS

We used orthogonal transcriptomic and phenotyping platforms combined with functional analytic pipelines to elucidate the immunomodulatory effect of the antiangiogenic agent pazopanib in mRCC patients. Nine patients were studied longitudinally over a period of 6 months. We also analyzed transcriptional data from The Cancer Genome Atlas (TCGA) RCC cohort (N = 571) to assess the prognostic implications of our findings. The effect of pazopanib was assessed in vitro on NK cells and T cells. Additionally, myeloid-derived suppressor (MDSC)-like cells were generated from CD14+ monocytes transfected with mimics of miRNAs associated with MDSC function in the presence or absence of pazopanib.

RESULTS

Pazopanib administration caused a rapid and dramatic reshaping in terms of frequency and transcriptional activity of multiple blood immune cell subsets, with a downsizing of MDSC and regulatory T cells in favor of a strong enhancement in PD-1 expressing cytotoxic T and Natural Killer effectors. These changes were paired with an increase of the expression of transcripts reflecting activation of immune-effector functions. This immunomodulation was marked but transient, peaking at the third month of treatment. Moreover, the intratumoral expression level of a MDSC signature (MDSC INT) was strongly associated with poor prognosis in RCC patients. In vitro experiments indicate that the observed immunomodulation might be due to an inhibitory effect on MDSC-mediated suppression, rather than a direct effect on NK and T cells.

CONCLUSIONS

The marked but transient nature of this immunomodulation, peaking at the third month of treatment, provides the rationale for the use of antiangiogenics as a preconditioning strategy to improve the efficacy of ICB.

Identification of Genes Related to Immune Infiltration in the Tumor Microenvironment of Cutaneous Melanoma

Cutaneous melanoma (CM) is the leading cause of skin cancer deaths and is typically diagnosed at an advanced stage, resulting in a poor prognosis. The tumor microenvironment (TME) plays a significant role in tumorigenesis and CM progression, but the dynamic regulation of immune and stromal components is not yet fully understood. In the present study, we quantified the ratio between immune and stromal components and the proportion of tumor-infiltrating immune cells (TICs), based on the ESTIMATE and CIBERSORT computational methods, in 471 cases of skin CM (SKCM) obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis to identify prognosis-related genes. The developed prognosis model contains ten genes, which are all vital for patient prognosis. The areas under the curve (AUC) values for the developed prognostic model at 1, 3, 5, and 10 years were 0.832, 0.831, 0.880, and 0.857 in the training dataset, respectively. The GSE54467 dataset was used as a validation set to determine the predictive ability of the prognostic signature. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were used to verify “real” hub genes closely related to the TME. These hub genes were verified for differential expression by immunohistochemistry (IHC) analyses. In conclusion, this study might provide potential diagnostic and prognostic biomarkers for CM.

A novel risk score predicts prognosis in melanoma: The combination of three tumor-infiltrating immune cells and four immune-related genes

Tumor-infiltrating immune cells (TIICs) and immune-related genes (IRGs) of melanoma are associated with prognosis. However, whether the combination of TIICs and IRGs can be used as prognostic clinical biomarkers are still unknown. Here, we downloaded transcription profile of melanoma from TCGA. Then, three TIICs and four IRGs that associated with the overall survival were used to constructed the Immune Cell Score (ICS) and Immune Gene Score (IGS) respectively. Next, to improve the accuracy of ICS and IGS for melanoma prognostic, we combined the ICS and IGS constructed the Immune Cell and Gene Score (ICGS) model. ICGS had higher accuracy and predictive ability than ICS or IGS. Meanwhile, ICGS model reliability was validated by two independent datasets of melanoma. Functional enrichment and protein-protein interaction network analysis based on ICGS were performed to identify T cell mediated immune and inflammatory response are highly associated with melanoma.

DNA methylation regulator-mediated modification patterns and tumor microenvironment characterization in gastric cancer

Growing evidence implies a link between DNA methylation and tumor immunity/immunotherapy. However, the global influence of DNA methylation on the characteristics of the tumor microenvironment and the efficacy of immunotherapy remains to be clarified. In this study, we systematically evaluated the DNA methylation regulator patterns and tumor microenvironment characteristics of 1,619 gastric cancer patients by clustering the gene expression of 20 DNA methylation regulators. Three gastric cancer subtypes that had different DNA methylation modification patterns and distinct tumor microenvironment characteristics were recognized. Then, a DNA methylation score (DMS) was constructed to evaluate DNA methylation modification individually. High DMS was characterized by immune activation status, increased tumor mutation burden, and tumor neoantigens, with a favorable prognosis. Conversely, activation of the stroma and absence of immune cell infiltration were observed in the low DMS group, with relatively poor survival. High DMS was also certified to be correlated with enhanced efficacy of immunotherapy in four immune checkpoint blocking treatment cohorts. In conclusion, the characterization of DNA methylation modification patterns may help to enhance our recognition of the tumor immune microenvironment of gastric cancer and guide more personalized immunotherapy strategies in the future.

A gene expression signature of TREM2hi macrophages and γδ T cells predicts immunotherapy response

Identifying factors underlying resistance to immune checkpoint therapy (ICT) is still challenging. Most cancer patients do not respond to ICT and the availability of the predictive biomarkers is limited. Here, we re-analyze a publicly available single-cell RNA sequencing (scRNA-seq) dataset of melanoma samples of patients subjected to ICT and identify a subset of macrophages overexpressing TREM2 and a subset of gammadelta T cells that are both overrepresented in the non-responding tumors. In addition, the percentage of a B cell subset is significantly lower in the non-responders. The presence of these immune cell subtypes is corroborated in other publicly available scRNA-seq datasets. The analyses of bulk RNA-seq datasets of the melanoma samples identify and validate a signature - ImmuneCells.Sig - enriched with the genes characteristic of the above immune cell subsets to predict response to immunotherapy. ImmuneCells.Sig could represent a valuable tool for clinical decision making in patients receiving immunotherapy.

HAS3-induced extracellular vesicles from melanoma cells stimulate IHH mediated c-Myc upregulation via the hedgehog signaling pathway in target cells

Intercellular communication is fundamental to the survival and maintenance of all multicellular systems, whereas dysregulation of communication pathways can drive cancer progression. Extracellular vesicles (EVs) are mediators of cell-to-cell communication that regulate a variety of cellular processes involved in tumor progression. Overexpression of a specific plasma membrane enzyme, hyaluronan synthase 3 (HAS3), is one of the factors that can induce EV shedding. HAS3, and particularly its product hyaluronan (HA), are carried by EVs and are known to be associated with the tumorigenic properties of cancer cells. To elucidate the specific effects of cancerous, HAS3-induced EVs on target cells, normal human keratinocytes and melanoma cells were treated with EVs derived from GFP-HAS3 expressing metastatic melanoma cells. We found that the HA receptor CD44 participated in the regulation of EV binding to target cells. Furthermore, GFP-HAS3-positive EVs induced HA secretion, proliferation and invasion of target cells. Our results suggest that HAS3-EVs contains increased quantities of IHH, which activates the target cell hedgehog signaling cascade and leads to the activation of c-Myc and regulation of claspin expression. This signaling of IHH in HAS3-EVs resulted in increased cell proliferation. Claspin immunostaining correlated with HA content in human cutaneous melanocytic lesions, supporting our in vitro findings and suggesting a reciprocal regulation between claspin expression and HA synthesis. This study shows for the first time that EVs originating from HAS3 overexpressing cells carry mitogenic signals that induce proliferation and epithelial-to-mesenchymal transition in target cells. The study also identifies a novel feedback regulation between the hedgehog signaling pathway and HA metabolism in melanoma, mediated by EVs carrying HA and IHH.

Extracellular Vesicles as Biomarkers in Cancer Immunotherapy

Simple Summary

Extracellular vesicles (EVs) are small particles found throughout the body. EVs are released by living cells and contain cargo representing the cell of origin. In recent years, EVs have gained attention in cancer research. Since the cargo found inside EVs can be traced back to the cell of origin, EVs shed from cancer cells, in particular, may be used to better describe and characterize a patient’s tumor. EVs have been found and isolated from a variety of bodily fluids, including blood, saliva, and amniotic fluid, and therefore offer a non-invasive way of also diagnosing and monitoring patients before, during, and after cancer immunotherapy. The aim of this review article was to summarize some of the recent work conducted in this field and the challenges we face moving forward in utilizing EVs for cancer diagnostic and therapeutic purposes in cancer immunotherapy in the clinical setting.

Abstract

Extracellular vesicles (EVs), including exosomes and microvesicles, are membrane-bound vesicles secreted by most cell types during both physiologic conditions as well in response to cellular stress. EVs play an important role in intercellular communication and are emerging as key players in tumor immunology. Tumor-derived EVs (TDEs) harbor a diverse array of tumor neoantigens and contain unique molecular signature that is reflective of tumor’s underlying genetic complexity. As such they offer a glimpse into the immune tumor microenvironment (TME) and have the potential to be a novel, minimally invasive biomarker for cancer immunotherapy. Immune checkpoint inhibitors (ICI), such as anti- programmed death-1(PD-1) and its ligand (PD-L1) antibodies, have revolutionized the treatment of a wide variety of solid tumors including head and neck squamous cell carcinoma, urothelial carcinoma, melanoma, non-small cell lung cancer, and others. Typically, an invasive tissue biopsy is required both for histologic diagnosis and next-generation sequencing efforts; the latter have become more widespread in daily clinical practice. There is an unmet need for noninvasive or minimally invasive (e.g., plasma-based) biomarkers both for diagnosis and treatment monitoring. Targeted analysis of EVs in biospecimens, such as plasma and saliva could serve this purpose by potentially obviating the need for tissue sample. In this review, we describe the current challenges of biomarkers in cancer immunotherapy as well as the mechanistic role of TDEs in modulating antitumor immune response.

In-depth plasma proteomics reveals increase in circulating PD-1 during anti-PD-1 immunotherapy in patients with metastatic cutaneous melanoma

BACKGROUND

Immune checkpoint inhibitors (ICIs) have significantly improved the outcome in metastatic cutaneous melanoma (CM). However, therapy response is limited to subgroups of patients and clinically useful predictive biomarkers are lacking.

METHODS

To discover treatment-related systemic changes in plasma and potential biomarkers associated with treatment outcome, we analyzed serial plasma samples from 24 patients with metastatic CM, collected before and during ICI treatment, with mass-spectrometry-based global proteomics (high-resolution isoelectric focusing liquid chromatography-mass spectrometry (HiRIEF LC-MS/MS)) and targeted proteomics with proximity extension assays (PEAs). In addition, we analyzed plasma proteomes of 24 patients with metastatic CM treated with mitogen-activated protein kinase inhibitors (MAPKis), to pinpoint changes in protein plasma levels specific to the ICI treatment. To detect plasma proteins associated with treatment response, we performed stratified analyses in anti-programmed cell death protein 1 (anti-PD-1) responders and non-responders. In addition, we analyzed the association between protein plasma levels and progression-free survival (PFS) by Cox proportional hazards models.

RESULTS

Unbiased HiRIEF LC-MS/MS-based proteomics showed plasma levels' alterations related to anti-PD-1 treatment in 80 out of 1160 quantified proteins. Circulating PD-1 had the highest increase during anti-PD-1 treatment (log2-FC=2.03, p=0.0008) and in anti-PD-1 responders (log2-FC=2.09, p=0.005), but did not change in the MAPKis cohort. Targeted, antibody-based proteomics by PEA confirmed this observation. Anti-PD-1 responders had an increase in plasma proteins involved in T-cell response, neutrophil degranulation, inflammation, cell adhesion, and immune suppression. Furthermore, we discovered new associations between plasma proteins (eg, interleukin 6, interleukin 10, proline-rich acidic protein 1, desmocollin 3, C-C motif chemokine ligands 2, 3 and 4, vascular endothelial growth factor A) and PFS, which may serve as predictive biomarkers.

CONCLUSIONS

We detected an increase in circulating PD-1 during anti-PD-1 treatment, as well as diverse immune plasma proteomic signatures in anti-PD-1 responders. This study demonstrates the potential of plasma proteomics as a liquid biopsy method and in discovery of putative predictive biomarkers for anti-PD-1 treatment in metastatic CM.

The Role of the Lymphocyte Functional Crosstalk and Regulation in the Context of Checkpoint Inhibitor Treatment-Review

During the last decade, the dynamics of the cellular crosstalk have highlighted the significance of the host vs. tumor interaction. This resulted in the development of novel immunotherapeutic strategies in order to modulate/inhibit the mechanisms leading to escape of tumor cells from immune surveillance. Different monoclonal antibodies directed against immune checkpoints, e.g., the T lymphocyte antigen 4 and the programmed cell death protein 1/ programmed cell death ligand 1 have been successfully implemented for the treatment of cancer. Despite their broad activity in many solid and hematologic tumor types, only 20–40% of patients demonstrated a durable treatment response. This might be due to an impaired T cell tumor interaction mediated by immune escape mechanisms of tumor and immune cells as well as alterations in the composition of the tumor microenvironment, peripheral blood, and microbiome. These different factors dynamically regulate different steps of the cancer immune process thereby negatively interfering with the T cell –mediated anti-tumoral immune responses. Therefore, this review will summarize the current knowledge of the different players involved in inhibiting tumor immunogenicity and mounting resistance to checkpoint inhibitors with focus on the role of tumor T cell interaction. A better insight of this process might lead to the development of strategies to revert these inhibitory processes and represent the rational for the design of novel immunotherapies and combinations in order to improve their efficacy.

Immunotherapy and targeted therapies in older patients with advanced melanoma; Young International Society of Geriatric Oncology review paper

Malignant melanoma is an aggressive cancer associated with a poor prognosis in patients with metastatic disease. As in many other cancers, the incidence of melanoma rises with age; and combined with the longer life expectancy, this led to an increasing prevalence of melanoma in the older population. Recently, immune checkpoint inhibitors significantly improved the treatment of melanoma given their efficacy and tolerability profile. Two major classes of agents include the anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) inhibitors, such as ipilimumab, and the anti-programmed death-ligand 1 (PD-1) inhibitors, such as nivolumab and pembrolizumab. Treatment of metastatic disease with immune checkpoint inhibitors demonstrated improved efficacy and better safety profiles compared to cytotoxic drugs and appears to be an attractive treatment option. Nevertheless, there is a need for tools designed to better predict which older patients will benefit from its use and who will experience toxicities related to the treatment. Current data do not show a major increase in toxicity rates in older patients. However, patients above 75 are often under-represented and those who are included are not representative of the general population of older patients, thereby also stressing the need for real-life data. Ongoing research is aiming at maximizing the potential treatment efficacy and developing novel immune-targeting modalities. Future studies should include older patients and assess geriatric domains in these older patients to better guide decision-making. This review discusses published clinical trials and where known, the efficacy and toxicity in older patients. Moreover, the clinical implications and future perspectives are discussed, with current recommendations for older patients, management of toxicities, and a proposal for an initial approach to the treatment of older patients with metastatic melanoma.

Cytokines, Chemokines, and Other Biomarkers of Response for Checkpoint Inhibitor Therapy in Skin Cancer

Immunotherapy for skin malignancies has ushered in a new era for cancer treatments by demonstrating unprecedented durable responses in the setting of metastatic Melanoma. Consequently, checkpoint inhibitors are now the first-line treatment of metastatic melanoma and widely used as adjuvant therapy for stage III disease. With the observation that higher tumor mutational burden correlates with a better response, checkpoint inhibitors are tested in other skin cancer types of known high tumor mutational burden with promising results and recently became the first-ever FDA-approved treatment for metastatic Merkel cell carcinoma. The emerging new standards-of-care will necessitate more precise biomarkers and predictors for treatment response and immune-related adverse events. Measurable immune-related mediators are currently under investigation as factors that promote or block the response to cancer immunotherapy and may provide insights into the underlying immune response to the tumor. Cytokines and chemokines are such mediators and are crucial for facilitating the recruitment and activation of specific subsets of leukocytes within the microenvironment of skin cancers. The exact mechanisms of how these meditators, both immunological and non-immunological, operate in the tumor microenvironment is an area of active research, so to reliable biomarkers of responses to cancer immunotherapy. Here, we will review and summarize the expanding body of literature for immune-related biomarkers pertaining to Melanoma, Basal cell carcinoma, Squamous cell carcinoma, and Merkel cell carcinoma, highlighting clinically relevant checkpoint inhibitor therapy biomarker advancements.

A whole-blood RNA transcript-based gene signature is associated with the development of CTLA-4 blockade-related diarrhea in patients with advanced melanoma treated with the checkpoint inhibitor tremelimumab

BACKGROUND

Anti-CTLA-4 immune checkpoint blockade is associated with immune-related adverse events (irAEs). Grade 3-4 diarrhea/colitis is the most frequent irAE requiring treatment discontinuation. Predicting high-risk diarrhea/colitis patients may facilitate early intervention, limit irAE severity, and extend treatment duration. No biomarkers currently predict for anti-CTLA-4 immunotherapy related severe diarrhea.

METHODS

Whole-blood was collected pre-treatment and 30 days post-treatment initiation from patients with stage III or IV unresectable melanoma who received 15 mg/kg tremelimumab at 90 day intervals in two clinical trials. The discovery dataset was a phase II study that enrolled 150 patients between December 2005 and November 2006. The validation dataset was a phase III study that enrolled 210 patients between March 2006 and July 2007. RT-PCR was performed for 169 genes associated with inflammation, immunity, CTLA-4 pathway and melanoma. Gene expression was correlated with grade 0-1 versus grade 2-4 diarrhea/colitis development.

RESULTS

Pre-treatment blood obtained from the discovery dataset (N = 150) revealed no gene predictive of diarrhea/colitis development (p < 0.05). A 16-gene signature (CARD12, CCL3, CCR3, CXCL1, F5, FAM210B, GADD45A, IL18bp, IL2RA, IL5, IL8, MMP9, PTGS2, SOCS3, TLR9 and UBE2C) was identified from 30 days post-tremelimumab initiation blood that discriminated patients developing grade 0-1 from grade 2-4 diarrhea/colitis. The 16-gene signature demonstrated an AUC of 0.814 (95% CI 0.743 to 0.873, p < 0.0001), sensitivity 42.9%, specificity 99.2%, positive predictive value (PPV) 90.0%, and negative predictive value (NPV) 91.4%. In the validation dataset (N = 210), the 16-gene signature discriminated patients developing grade 0-1 from grade 2-4 diarrhea/colitis with an AUC 0.785 (95% CI 0.723 to 0.838, p < 0.0001), sensitivity 57.1%, specificity 84.4%, PPV 57.1% and NPV 84.4%.

CONCLUSION

This study identifies a whole-blood mRNA signature predictive of a clinically relevant irAE in patients treated with immune checkpoint blockade. We hypothesize that immune system modulation induced by immune checkpoint blockade results in peripheral blood gene expression changes that are detectable prior to clinical onset of severe diarrhea. Assessment of peripheral blood gene expression changes in patients receiving anti-PD-1/PD-L1 immunotherapy, or combination anti-CTLA4 and anti-PD-1/PD-L1 immunotherapy, is warranted to provide early on-treatment mechanistic insights and identify clinically relevant predictive biomarkers.

TRIAL REGISTRATION

Clinicaltrials.gov , NCT00257205 , registered 22 November 2005.

Liquid Biopsy Using Whole Blood from Testis Tumor and Colon Cancer Patients-A New and Simple Way?

Tumor cells shed exosomes, which are released to the blood. Detecting tumor-derived exosomes containing RNA in plasma (liquid biopsy) is currently being investigated for early identification of occult metastases or relapses. Isolation of exosomes is laborious, resulting in low RNA yields. As a more robust (but less sensitive) alternative, the authors examined whether whole blood can be used as well. Tumor samples from nonmetastasized seminoma (n = 5) and colon cancer patients (n = 6) were taken during surgery. Whole-blood samples were taken before and 5-7 d after surgery. A whole genome mRNA microarray screening was performed. Candidate genes were selected based on two criteria: (1) gene expression in the presurgical whole-blood sample/tumor biopsy; and (2) a two-fold decrease in the copy number of candidate genes was expected in the postsurgical whole-blood sample 5-7 d after intervention, relative to the presurgical blood sample. The rationale behind this is the loss of tumor material in the body and the decline in the release of tumor-derived RNA in exosomes. For both tumor entities and for each patient, several hundred candidate genes could be identified. In a group-wise comparison, 20 candidate genes could be identified in the seminoma and 32 in the colon cancer group. These findings indicate that whole blood might be suitable for a liquid biopsy. However, this study identified the short period after surgery (5-7 d) as a possible confounder. The authors plan to add an additional time point several weeks after the operation to discriminate tumor candidate genes from genes induced by the surgery.

Melanoma Immunotherapy: Next-Generation Biomarkers

The recent emergence of cancer immunotherapies initiated a significant shift in the clinical management of metastatic melanoma. Prior to 2011, melanoma patients only had palliative treatment solutions which offered little to no survival benefit. In 2018, with immunotherapy, melanoma patients can now contemplate durable or even complete remission. Treatment with novel immune checkpoint inhibitors, anti-cytotoxic T-lymphocyte protein 4 and anti-programmed cell death protein 1, clearly result in superior median and long-term survivals compared to standard chemotherapy; however, more than half of the patients do not respond to immune checkpoint blockade. Currently, clinicians do not have any effective way to stratify melanoma patients for immunotherapies. Research is now focusing on identifying biomarkers which could predict a patient’s response prior treatment initiation (or very early during treatment course), in order to maximize therapeutic efficacy, avoid unnecessary costs, and undesirable heavy side effects for the patient. Given the rapid developments in this field and the translational potential for some of the biomarkers, we will summarize the current state of biomarker research for immunotherapy in melanoma, with an emphasis on omics technologies such as next-generation sequencing and mass cytometry (CyTOF).

Immune Dysregulation in Cancer Patients Undergoing Immune Checkpoint Inhibitor Treatment and Potential Predictive Strategies for Future Clinical Practice

Realization of the full potential of immune checkpoint inhibitor-targeted onco-immunotherapy is largely dependent on overcoming the obstacles presented by the resistance of some cancers, as well as on reducing the high frequency of immune-related adverse events (IRAEs) associated with this type of immunotherapy. With the exception of combining therapeutic monoclonal antibodies, which target different types of immune checkpoint inhibitory molecules, progress in respect of improving therapeutic efficacy has been somewhat limited to date. Likewise, the identification of strategies to predict and monitor the development of IRAEs has also met with limited success due, at least in part, to lack of insight into mechanisms of immunopathogenesis. Accordingly, considerable effort is currently being devoted to the identification and evaluation of strategies which address both of these concerns and it is these issues which represent the major focus of the current review, particularly those which may be predictive of development of IRAEs. Following an introductory section, this review briefly covers those immune checkpoint inhibitors currently approved for clinical application, as well as more recently identified immune checkpoint inhibitory molecules, which may serve as future therapeutic targets. The remaining and more extensive sections represent overviews of: (i) putative strategies which may improve the therapeutic efficacy of immune checkpoint inhibitors; (ii) recent insights into the immunopathogenesis of IRAEs, most prominently enterocolitis; and (iii) strategies, mostly unexplored, which may be predictive of development of IRAEs.