Blood mRNA expression profiling predicts survival in patients treated with tremelimumab

Phospholipase PLA2G7 is complementary to GPX4 in mitigating punicic-acid-induced ferroptosis in prostate cancer cells

Ferroptosis is a cell death pathway that can be promoted by peroxidizable polyunsaturated fatty acids in cancer cells. Here, we investigated the mechanisms underlying the toxicity of punicic acid (PunA), an isomer of conjugated linolenic acids (CLnAs) bearing three conjugated double bonds highly prone to peroxidation, on prostate cancer (PCa) cells. PunA induced ferroptosis in PCa cells and triggered massive lipidome remodeling, more strongly in PC3 androgen-negative cells than in androgen-positive cells. The greater sensitivity of androgen-negative cells to PunA was associated with lower expression of glutathione peroxidase 4 (GPX4). We then identified the phospholipase PLA2G7 as a PunA-induced ferroptosis suppressor in PCa cells. Overexpressing PLA2G7 decreased lipid peroxidation levels, suggesting that PLA2G7 hydrolyzes hydroperoxide-containing phospholipids, thus preventing ferroptosis. Importantly, overexpressing both PLA2G7 and GPX4 strongly prevented PunA-induced ferroptosis in androgen-negative PCa cells. This study shows that PLA2G7 acts complementary to GPX4 to protect PCa cells from CLnA-induced ferroptosis.

Combination of theoretical analysis and experiments: Exploring the role of PLA2G7 in human cancers, including renal cancer

Background

The pivotal role of phospholipase A2 group VII (PLA2G7) has been identified in specific human cancers, such as prostate cancer, diffuse large B cell lymphoma, and melanoma. Given PLA2G7's significant involvement in established tumors, exploring its role in other cancers is highly relevant.

Methods

In this study, we acquired and analyzed data from The Cancer Genome Atlas database, the UCSC XENA website, and other online platforms including Gene Set Cancer Analysis, cBioPortal, Tumor Immune Estimation Resource, and TISIDB to investigate PLA2G7's role in human cancers, including renal cancer. Furthermore, in vitro experiments, including immunofluorescence, western blotting, and CCK-8 assays, were conducted to elucidate PLA2G7's role in renal cancer. Finally, the relationship between PLA2G7 and various drug sensitivity was explored.

Results

Our findings demonstrate that PLA2G7 is highly expressed and may serve as a valuable candidate biomarker in pan-cancer. PLA2G7 exhibits distinct alteration frequencies across human cancers and is correlated with tumor mutation burden, tumor microenvironment, DNA stemness score, RNA stemness score, tumorigenesis, tumor immunity, and microsatellite instability in pan-cancer. Immunofluorescence and western blotting revealed a relative high level of PLA2G7 protein in renal cancer cell lines (ACHN and 786-O), predominantly localized in the cytoplasm. Treatment with a PLA2G7 gene inhibitor (darapladib) significantly decreased the viability of ACHN and 786-O cell lines. Additionally, we observed an association between PLA2G7 mRNA levels and various drug sensitivity.

Conclusions

Our study suggests that PLA2G7 has the potential to serve as a valuable biomarker and therapeutic target for cancer, particularly in the context of renal cancer.

Inhibiting PLA2G7 reverses the immunosuppressive function of intratumoral macrophages and augments immunotherapy response in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is an exceptionally immunosuppressive malignancy characterized by limited treatment options and a dismal prognosis. Macrophages constitute the primary and heterogeneous immune cell population within the HCC microenvironment. Our objective is to identify distinct subsets of macrophages implicated in the progression of HCC and their resistance to immunotherapy.

METHODS

Intratumoral macrophage-specific marker genes were identified via single-cell RNA sequencing analyses. The clinical relevance of phospholipase A2 Group VII (PLA2G7), a pivotal enzyme in phospholipid metabolism, was assessed in patients with HCC through immunohistochemistry and immunofluorescence. Flow cytometry and an in vitro co-culture system were used to elucidate the specific role of PLA2G7 in macrophages. Orthotopic and subcutaneous HCC mouse models were employed to evaluate the potential of the PLA2G7 inhibitor in complementing immune checkpoint blockade (ICB) therapy.

RESULTS

Single-cell RNA sequencing analyses disclosed predominant PLA2G7 expression in intratumoral macrophages within the HCC microenvironment. The macrophage-specific PLA2G7 was significantly correlated with poorer prognosis and immunotherapy resistance in patients with HCC. PLA2G7high macrophages represent a highly immunosuppressive subset and impede CD8 T-cell activation. Pharmacological inhibition of PLA2G7 by darapladib improved the therapeutic efficacy of anti-programmed cell death protein 1 antibodies in the HCC mouse models.

CONCLUSIONS

Macrophage-specific PLA2G7 serves as a novel biomarker capable of prognosticating immunotherapy responsiveness and inhibiting PLA2G7 has the potential to enhance the efficacy of ICB therapy for HCC.

Phosphoproteomic Analysis of the Jejunum Tissue Response to Colostrum and Milk Feeding in Dairy Calves during the Passive Immunity Period

Improvements in the feeding of calves are of increasing importance for the development of the dairy industry. While colostrum is essential for the health of newborn calves, knowledge of protein phosphorylation alterations in neonatal calves that are fed colostrum or mature milk is lacking. Here, mid-jejunum tissue samples were collected from calves that received colostrum or milk. Subsequently, the jejunum phosphoproteome was analyzed using a phosphopeptide enrichment method, i.e., titanium immobilized metal ion affinity chromatography, coupled with liquid chromatography-tandem mass spectrometry. A total of 2093 phosphopeptides carrying unique 1851 phosphorylation sites corresponding to 1180 phosphoproteins were identified. Of the 1180 phosphoproteins, 314 phosphorylation sites on 241 proteins were differentially expressed between the groups. Gene ontology analysis indicated that the phosphoproteins were strongly associated with developmental and macromolecule metabolic processes, signal transduction, and responses to stimuli and insulin. Pathway analysis showed that the spliceosome, Hippo, insulin, and neurotrophin signaling pathways were enriched. These results reveal the expression pattern and changes in the function of phosphoproteins in bovine jejunum tissues under different feeding conditions and provide further insights into the crucial role of colostrum feeding during the early stages of life.

Efficacy comparison of immune treating strategies for NSCLC patients with negative PD-L1 expression

BACKGROUND

We intended to compare and grade the proposed immune treating strategies for non-small cell lung cancer (NSCLC) with negative Programmed Cell Death Ligand 1(PD-L1).

METHODS

We compared the efficacy of single immune checkpoint inhibitor (ICI), single ICI plus chemotherapy, and doublet ICIs with chemotherapy alone, as well as single ICI plus radiotherapy with single ICI for negative PD-L1 (<1%) NSCLC patients. Hazard Ratio (HR) and 95% confidence interval (CI) of progression-free survival (PFS) and overall survival (OS) were used as outcomes.

RESULTS

We included 23 randomized control trials with 4665 patients. Compared with chemotherapy alone, single ICI, single ICI plus chemotherapy and doublet ICIs all showed a better OS (0.84 [0.71, 0.99] ; 0.77 [0.69, 0.85] ; 0.64 [0.53, 0.77])), while single ICI plus chemotherapy and doublet ICIs showed a better PFS (0.68 [0.61, 0.75] ; 0.69 [0.56, 0.85]). Additionally, single ICI plus radiotherapy obtained a greater pooled PFS (0.49 [0.28-0.87]) than single ICI.

CONCLUSIONS

Both single ICI plus chemotherapy and doublet ICIs were probably better treatment decisions than chemotherapy alone for negative PD-L1 NSCLC patients. Also, single ICI plus radiotherapy carved out a new strategy.

Identification of PLA2G7 as a novel biomarker of diffuse large B cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma is the most common form of non-Hodgkin lymphoma globally, and patients with relapsed or refractory DLBCL typically experience poor long-term outcomes.

METHODS

Differentially expressed genes associated with DLBCL were identified using two GEO datasets in an effort to detect novel diagnostic or prognostic biomarkers of this cancer type, after which receiver operating characteristic curve analyses were conducted. Genes associated with DLBCL patient prognosis were additionally identified via WCGNA analyses of the TCGA database. The expression of PLA2G7 in DLBCL patient clinical samples was further assessed, and the functional role of this gene in DLBCL was assessed through in vitro and bioinformatics analyses.

RESULTS

DLBCL-related DEGs were found to be most closely associated with immune responses, cell proliferation, and angiogenesis. WCGNA analyses revealed that PLA2G7 exhibited prognostic value in DLBCL patients, and the upregulation of this gene in DLBCL patient samples was subsequently validated. PLA2G7 was also found to be closely linked to tumor microenvironmental composition such that DLBCL patients expressing higher levels of this gene exhibited high local monocyte and gamma delta T cell levels. In vitro experiments also revealed that knocking down PLA2G7 expression was sufficient to impair the migration and proliferation of DLBCL cells while promoting their apoptotic death. Furthmore, the specific inhibitor of PLA2G7, darapladib, could noticeably restrained the DLBCL cell viability and induced apoptosis.

CONCLUSIONS

PLA2G7 may represent an important diagnostic, prognostic, or therapeutic biomarker in patients with DLBCL.

Dimeric Structure of the Pseudokinase IRAK3 Suggests an Allosteric Mechanism for Negative Regulation

Interleukin-1 receptor associated kinases (IRAKs) are key players in innate immune signaling that mediate the host response to pathogens. In contrast to the active kinases IRAK1 and IRAK4, IRAK2 and IRAK3 are pseudokinases lacking catalytic activity and their functions are poorly understood. IRAK3 is thought to be a negative regulator of innate immune signaling and mutations in IRAK3 are associated with asthma and cancer. Here, we report the crystal structure of the human IRAK3 pseudokinase domain in a closed, pseudoactive conformation. IRAK3 dimerizes in a unique way through a head-to-head arrangement not observed in any other kinases. Multiple conserved cysteine residues imply a potential redox control of IRAK3 conformation and dimerization. By analyzing asthma-associated mutations, we identify an evolutionarily conserved surface on IRAK3 that could form an interaction interface with IRAK4, suggesting a model for the negative regulation of IRAK4 by IRAK3.

SMARCA4 promotes benign skin malignant transformation into melanoma through Adherens junction signal transduction

PURPOSE

Melanoma is a malignant skin tumor, and its incidence is rising. To explore the specific differences in benign and malignant melanoma at the genetic level, we performed a series of bioinformatics analyses, including differential gene analysis, co-expression analysis, enrichment analysis, and regulatory prediction.

METHODS

The microarray data of benign and malignant melanocytes were downloaded from GEO, and 1917 differential genes were obtained by differential analysis (p < 0.05). Weighted gene co-expression network analysis obtained three functional barrier modules. The essential genes of each module are SMARTA4, HECA, and C1R.

RESULTS

The results of the enrichment analysis showed that the dysfunctional module gene was mainly associated with RNA splicing and Adherens junction. Through the pivotal analysis of ncRNA, it was found that miR-448, miR-152-3p, and miR-302b-3p essentially regulate three modules, which we consider to be critical regulators. In the pivot analysis of TF, more control modules include ARID3A, E2F1, E2F3, and E2F8.

CONCLUSIONS

We believe that the regulator (miR-448, miR-152-3p, miR-302b-3p) regulates the expression of the core gene SMARCA4, which in turn affects the signal transduction of the Adherens junction. It eventually leads to the deterioration of benign skin spasms into melanoma.

Biomarkers Predictive of Survival and Response to Immune Checkpoint Inhibitors in Melanoma

Immunotherapy has revolutionized the treatment of melanoma. Targeting of the immune checkpoints cytotoxic T-lymphocyte-associated protein 4 and programmed cell death protein 1 has led to improved survival in a subset of patients. Unfortunately, the use of immune checkpoint inhibitors is associated with significant side effects and many patients do not respond to treatment. Thus, there is an urgent need both for prognostic biomarkers to estimate risk and for predictive biomarkers to determine which patients are likely to respond to therapy. In this review, prognostic and predictive biomarkers that are an active area of research are outlined. Of note, certain transcriptomic signatures are already used in the clinic, albeit not routinely, to prognosticate patients. In the predictive setting, programmed cell death protein ligand 1 expression has been shown to correlate with benefit but is not precise enough to be used as an exclusionary biomarker. Future investigation will need to focus on biomarkers that are easily reproducible, cost effective, and accurate. The use of readily available clinical material, such as serum or hematoxylin and eosin-stained images, may offer one such path forward.

Predictive biomarkers for immune checkpoint blockade and opportunities for combination therapies

Immune checkpoint blockade therapies (ICBs) are a prominent breakthrough in cancer immunotherapy in recent years (named the 2013 “Breakthrough of the Year” by the Science magazine). Thus far, FDA-approved ICBs primarily target immune checkpoints CTLA-4, PD-1, and PD-L1. Notwithstanding their impressive long-term therapeutic benefits, their efficacy is limited to a small subset of cancer patients. In addition, ICBs induce inadvertent immune-related adverse events (irAEs) and can be costly for long-term use. To overcome these limitations, two strategies are actively being pursued: identification of predictive biomarkers for clinical response to ICBs and multi-pronged combination therapies. Biomarkers will allow clinicians to practice a precision medicine approach in ICBs (biomarker-based patient selection) such as treating triple-negative breast cancer patients that exhibit PD-L1 staining of tumor-infiltrating immune cells in ≥1% of the tumor area with nanoparticle albumin-bound (nab)–paclitaxel plus anti-PD-L1 and treating patients of MSI-H or MMR deficient unresectable or metastatic solid tumors with pembrolizumab (anti-PD-1). Importantly, the insights gained from these biomarker studies can guide rational combinatorial strategies such as CDK4/6 inhibitor/fractionated radiotherapy/HDACi in conjunction with ICBs to maximize therapeutic benefits. Further, with the rapid technological advents (e.g., ATCT-Seq), we predict more reliable biomarkers will be identified, which in turn will inspire more promising combination therapies.

Lipoprotein-associated phospholipase A2: The story continues

Inflammation is thought to play an important role in the pathogenesis of vascular diseases. Lipoprotein-associated phospholipase A2 (Lp-PLA2) mediates vascular inflammation through the regulation of lipid metabolism in blood, thus, it has been extensively investigated to identify its role in vascular inflammation-related diseases, mainly atherosclerosis. Although darapladib, the most advanced Lp-PLA2 inhibitor, failed to meet the primary endpoints of two large phase III trials in atherosclerosis patients cotreated with standard medical care, the research on Lp-PLA2 has not been terminated. Novel pathogenic, epidemiologic, genetic, and crystallographic studies regarding Lp-PLA2 have been reported recently, while novel inhibitors were identified through a fragment-based lead discovery strategy. More strikingly, recent clinical and preclinical studies revealed that Lp-PLA2 inhibition showed promising therapeutic effects in diabetic macular edema and Alzheimer's disease. In this review, we not only summarized the knowledge of Lp-PLA2 established in the past decades but also emphasized new findings in recent years. We hope this review could be valuable for helping researchers acquire a much deeper insight into the nature of Lp-PLA2, identify more potent and selective Lp-PLA2 inhibitors, and discover the potential indications of Lp-PLA2 inhibitors.

A distinct epigenetic program underlies the 1;7 translocation in myelodysplastic syndromes

The unbalanced translocation dic(1;7)(q10;p10) in myelodysplastic syndromes (MDS) is originated by centromeric juxtaposition resulting into 1q trisomy and 7q monosomy. More than half of cases arise after chemo/radio-therapy. To date, given the absence of genes within the centromeric regions, no specific molecular events have been identified in this cytogenetic subgroup. We performed the first comprehensive genetic and epigenetic analysis of MDS with dic(1;7)(q10;p10) compared to normal controls and therapy-related myeloid neoplasms (t-MNs). RNA-seq showed a unique downregulated signature in dic(1;7) cases, affecting more than 80% of differentially expressed genes. As revealed by pathway and gene ontology analyses, downregulation of ATP-binding cassette (ABC) transporters and lipid-related genes and upregulation of p53 signaling were the most relevant biological features of dic(1;7). Epigenetic supervised analysis revealed hypermethylation at intronic enhancers in the dicentric subgroup, in which low expression levels of enhancer putative target genes accounted for around 35% of the downregulated signature. Enrichment of Krüppel-like transcription factor binding sites emerged at enhancers. Furthermore, a specific hypermethylated pattern on 1q was found to underlie the hypo-expression of more than 50% of 1q-deregulated genes, despite trisomy. In summary, dic(1;7) in MDS establishes a specific transcriptional program driven by a unique epigenomic signature.

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.

Biomarkers for Clinical Benefit of Immune Checkpoint Inhibitor Treatment-A Review From the Melanoma Perspective and Beyond

Background

Immune checkpoint inhibition (ICI) with anti-CTLA-4 and/or anti-PD-1 antibodies is standard treatment for metastatic melanoma. Anti-PD-1 (pembrolizumab, nivolumab) and anti-PD-L1 antibodies (atezolizumab, durvalumab, and avelumab) have been approved for treatment of several other advanced malignancies, including non-small-cell lung cancer (NSCLC); renal cell, and urothelial carcinoma; head and neck cancer; gastric, hepatocellular, and Merkel-cell carcinoma; and classical Hodgkin lymphoma. In some of these malignancies approval was based on the detection of biomarkers such as PD-L1 expression or high microsatellite instability.

Methods

We review the current status of prognostic and predictive biomarkers used in ICI for melanoma and other malignancies. We include clinical, tissue, blood, and stool biomarkers, as well as imaging biomarkers.

Results

Several biomarkers have been studied in ICI for metastatic melanoma. In clinical practice, pre-treatment tumor burden measured by means of imaging and serum lactate dehydrogenase level is already being used to estimate the likelihood of effective ICI treatment. In peripheral blood, the number of different immune cell types, such as lymphocytes, neutrophils, and eosinophils, as well as different soluble factors, have been correlated with clinical outcome. For intra-tumoral biomarkers, expression of the PD-1 ligand PD-L1 has been found to be of some predictive value for anti-PD-1-directed therapy for NSCLC and melanoma. A high mutational load, particularly when accompanied by neoantigens, seems to facilitate immune response and correlates with patient survival for all entities treated by use of ICI. Tumor microenvironment also seems to be of major importance. Interestingly, even the gut microbiome has been found to correlate with response to ICI, most likely through immuno-stimulatory effects of distinct bacteria. New imaging biomarkers, e.g., for PET, and magnetic resonance imaging are also being investigated, and results suggest they will make early prediction of patient response possible.

Conclusion

Several promising results are available regarding possible biomarkers for response to ICI, which need to be validated in large clinical trials. A better understanding of how ICI works will enable the development of biomarkers that can predict the response of individual patients.

A panel of three oxidative stress-related genes predicts overall survival in ovarian cancer patients received platinum-based chemotherapy

Ovarian cancer yields the highest mortality rate of all lethal gynecologic cancers, and the prognosis is unsatisfactory with the major obstacle in resistance to chemotherapy. The generation of reactive oxygen species (ROS) in tumor tissues was associated with chemotherapeutic effectiveness by mediating cellular longevity. In this study, we screened the prognostic values of oxidative stress-related genes in ovarian cancer patients received platinum-based chemotherapy, and conducted a prognostic gene signature composing of three genes, TXNRD1, GLA and GSTZ1. This three-gene signature was significantly associated with overall survival (OS), but not progression-free survival (PFS), in both training (n=276) and validation cohorts (n=230). Interestingly, we found that the prognostic value of three-gene signature was reinforced in platinum-sensitive patients. Subgroup analysis further suggested that patients with elder age, higher pathological grades and advanced tumor stages in low-risk score group could benefit from platinum-based chemotherapy. Functional analysis showed that the inactivation of several signaling pathways, including cell cycle, insulin-like growth factor 1 (IGF1) /mTOR and Fas pathways, was affected by three genes. Collectively, our results provided evidence that a panel of three oxidative stress-related gene signature had prognostic values for ovarian cancer patients received platinum-based chemotherapy.

Immunotherapy for breast cancer: past, present, and future

Immunotherapy has shown promise in many solid tumors including melanoma and non-small cell lung cancer with an evolving role in breast cancer. Immunotherapy encompasses a wide range of therapies including immune checkpoint inhibition, monoclonal antibodies, bispecific antibodies, vaccinations, antibody-drug conjugates, and identifying other emerging interventions targeting the tumor microenvironment. Increasing efficacy of these treatments in breast cancer patients requires identification of better biomarkers to guide patient selection; recognizing when to initiate these therapies in multi-modality treatment plans; establishing novel assays to monitor immune-mediated responses; and creating combined systemic therapy options incorporating conventional treatments such as chemotherapy and endocrine therapy. This review will focus on the current role and future directions of many of these immunotherapies in breast cancer, as well as highlighting clinical trials that are investigating several of these active issues.

Biomarkers for Response of Melanoma Patients to Immune Checkpoint Inhibitors: A Systematic Review

Background

Immune checkpoint inhibitors (ICIs), targeting CTLA-4 or PD-1 molecules, have shown impressive therapeutic results. However, only 20–40% of advanced melanoma patients have durable responses to ICI, and these positive effects must be balanced against severe off-target immune toxicity and high costs. This urges the development of predictive biomarkers for ICI response to select patients with likely clinical benefit from treatment. Although many candidate biomarkers exist, a systematic overview of biomarkers and their usefulness is lacking.

Objectives

Here, we systematically review the current literature of clinical data of ICI treatment to provide an overview of candidate predictive biomarkers for ICI in melanoma patients.

Methods

To identify studies on biomarkers for clinical response or survival to ICI therapy in melanoma patients, we performed a systematic search in OVID MEDLINE and retrieved 429 publications, of which 67 met the eligibility criteria.

Results

Blood and genomic biomarkers were mainly studied for CTLA-4 ICI, while tumor tissue markers were analyzed for both CTLA-4 and PD-1 ICI. Blood cytology and soluble factors correlated more frequently to overall survival (OS) than to response, indicating their prognostic rather than predictive nature. Systemic T-cell response and regulation markers correlated to response, but progression-free survival or OS were not analyzed. Tumor tissue analyses revealed response correlations with mutational load, neoantigen load, immune-related gene expression, and CD8+ T-cell infiltration at the invasive margin. The predictive value of PD-L1 varied, possibly due to the influence of T-cell infiltration on tumor PD-L1 expression. Genomic biomarker studies addressed CTLA-4 and other immune-related genes.

Conclusion

This review outlines all published biomarkers for ICI therapy and highlights potential candidate markers for future research. To date, PD-L1 is the best studied biomarker for PD-1 ICI response. The most promising candidate predictive biomarkers for ICI response have not yet been identified. Variations in outcome parameters, statistical power, and analyses hampered summary of the results. Further investigation of biomarkers in larger patient cohorts using standardized objectives and outcome measures is recommended.

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

Background

Tremelimumab is an antibody that blocks CTLA-4 and demonstrates clinical efficacy in a subset of advanced melanoma patients. An unmet clinical need exists for blood-based response-predictive gene signatures to facilitate clinically effective and cost-efficient use of such immunotherapeutic interventions.

Methods

Peripheral blood samples were collected in PAXgene® tubes from 210 treatment-naïve melanoma patients receiving tremelimumab in a worldwide, multicenter phase III study (discovery dataset). A central panel of radiologists determined objective response using RECIST criteria. Gene expression for 169 mRNA transcripts was measured using quantitative PCR. A 15-gene pre-treatment response-predictive classifier model was identified. An independent population (N = 150) of refractory melanoma patients receiving tremelimumab after chemotherapy enrolled in a worldwide phase II study (validation dataset). The classifier model, using the same genes, coefficients and constants for objective response and one-year survival after treatment, was applied to the validation dataset.

Results

A 15-gene pre-treatment classifier model (containing ADAM17, CDK2, CDKN2A, DPP4, ERBB2, HLA-DRA, ICOS, ITGA4, LARGE, MYC, NAB2, NRAS, RHOC, TGFB1, and TIMP1) achieved an area under the curve (AUC) of 0.86 (95% confidence interval 0.81 to 0.91, p < 0.0001) for objective response and 0.6 (95% confidence interval 0.54 to 0.67, p = 0.0066) for one-year survival in the discovery set. This model was validated in the validation set with AUCs of 0.62 (95% confidence interval 0.54 to 0.70 p = 0.0455) for objective response and 0.68 for one-year survival (95% confidence interval 0.59 to 0.75 p = 0.0002).

Conclusions

To our knowledge, this is the largest blood-based biomarker study of a checkpoint inhibitor, tremelimumab, which demonstrates a validated pre-treatment mRNA classifier model that predicts clinical response. The data suggest that the model captures a biological signature representative of genes needed for a robust anti-cancer immune response. It also identifies non-responders to tremelimumab at baseline prior to treatment.

Electronic supplementary material

The online version of this article (doi:10.1186/s40425-017-0272-z) contains supplementary material, which is available to authorized users.

Systematic evaluation of immune regulation and modulation

Cancer immunotherapies are showing promising clinical results in a variety of malignancies. Monitoring the immune as well as the tumor response following these therapies has led to significant advancements in the field. Moreover, the identification and assessment of both predictive and prognostic biomarkers has become a key component to advancing these therapies. Thus, it is critical to develop systematic approaches to monitor the immune response and to interpret the data obtained from these assays. In order to address these issues and make recommendations to the field, the Society for Immunotherapy of Cancer reconvened the Immune Biomarkers Task Force. As a part of this Task Force, Working Group 3 (WG3) consisting of multidisciplinary experts from industry, academia, and government focused on the systematic assessment of immune regulation and modulation. In this review, the tumor microenvironment, microbiome, bone marrow, and adoptively transferred T cells will be used as examples to discuss the type and timing of sample collection. In addition, potential types of measurements, assays, and analyses will be discussed for each sample. Specifically, these recommendations will focus on the unique collection and assay requirements for the analysis of various samples as well as the high-throughput assays to evaluate potential biomarkers.

Dynamic versus static biomarkers in cancer immune checkpoint blockade: unravelling complexity

Recently, there has been a coordinated effort from academic institutions and the pharmaceutical industry to identify biomarkers that can predict responses to immune checkpoint blockade in cancer. Several biomarkers have been identified; however, none has reliably predicted response in a sufficiently rigorous manner for routine use. Here, we argue that the therapeutic response to immune checkpoint blockade is a critical state transition of a complex system. Such systems are highly sensitive to initial conditions, and critical transitions are notoriously difficult to predict far in advance. Nevertheless, warning signals can be detected closer to the tipping point. Advances in mathematics and network biology are starting to make it possible to identify such warning signals. We propose that these dynamic biomarkers could prove to be useful in distinguishing responding from non-responding patients, as well as facilitate the identification of new therapeutic targets for combination therapy.

Increased cathepsin D protein expression is a biomarker for osteosarcomas, pulmonary metastases and other bone malignancies

Cancer proteomics provide a powerful approach to identify biomarkers for personalized medicine. Particularly, biomarkers for early detection, prognosis and therapeutic intervention of bone cancers, especially osteosarcomas, are missing. Initially, we compared two-dimensional gel electrophoresis (2-DE)-based protein expression pattern between cell lines of fetal osteoblasts, osteosarcoma and pulmonary metastasis derived from osteosarcoma. Two independent statistical analyses by means of PDQuest® and SameSpot® software revealed a common set of 34 differentially expressed protein spots (p < 0.05). 17 Proteins were identified by mass spectrometry and subjected to Ingenuity Pathway Analysis resulting in one high-ranked network associated with Gene Expression, Cell Death and Cell-To-Cell Signaling and Interaction. Ran/TC4-binding protein (RANBP1) and Cathepsin D (CTSD) were further validated by Western Blot in cell lines while the latter one showed higher expression differences also in cytospins and in clinical samples using tissue microarrays comprising osteosarcomas, metastases, other bone malignancies, and control tissues. The results show that protein expression patterns distinguish fetal osteoblasts from osteosarcomas, pulmonary metastases, and other bone diseases with relevant sensitivities between 55.56% and 100% at ≥87.50% specificity. Particularly, CTSD was validated in clinical material and could thus serve as a new biomarker for bone malignancies and potentially guide individualized treatment regimes.

Diagnostic marker signature for esophageal cancer from transcriptome analysis

Esophageal cancer is often diagnosed at an advanced stage. Diagnostic markers are needed for achieving a cure in esophageal cancer detecting and treating tumor cells earlier. In patients with locally advanced squamous cell carcinoma of the esophagus (ESCC), we profiled the gene expression of ESCC compared to corresponding normal biopsies for diagnostic markers by genome microarrays. Profiling of gene expression identified 4844 genes differentially expressed, 2122 upregulated and 2722 downregulated in ESCC. Twenty-three overexpressed candidates with best scores from significance analysis have been selected for further analysis by TaqMan low-density array-technique using a validation cohort of 40 patients. The verification rate was 100 % for ESCC. Twenty-two markers were additionally overexpressed in adenocarcinoma of the esophagus (EAC). The markers significantly overexpressed already in earlier tumor stages (pT1-2) of both histological subtypes (n = 19) have been clustered in a "diagnostic signature": PLA2G7, PRAME, MMP1, MMP3, MMP12, LIlRB2, TREM2, CHST2, IGFBP2, IGFBP7, KCNJ8, EMILIN2, CTHRC1, EMR2, WDR72, LPCAT1, COL4A2, CCL4, and SNX10. The marker signature will be translated to clinical practice to prove its diagnostic impact. This diagnostic signature may contribute to the earlier detection of tumor cells, with the aim to complement clinical techniques resulting in the development of better detection of concepts of esophageal cancer for earlier therapy and more favorite prognosis.

Diverse Functions of Plasma PAF-AH in Tumorigenesis

This chapter is focused on the role of the plasma form of platelet-activating factor-acetylhydrolase (PAF-AH), heretofore referred to as PAF-AH, in tumorigenic responses. Biochemical and other properties of this enzyme were discussed in detail in chapter "Plasma PAF-AH (PLA2G7): Biochemical Properties, Association with LDLs and HDLs, and Regulation of Expression" by Stafforini and in other chapters. Although phospholipases tend not to be drivers of tumorigenesis themselves, these enzymes and the lipid mediators whose levels they regulate interact with a variety of oncogenes and tumor suppressors [1]. Like other phospholipases, the functions of PAF-AH in cancer likely are related to its ability to regulate the levels of lipid mediators that participate in cellular processes related to initial tumorigenic events (e.g., proliferation, growth, inflammation) and/or spreading of the disease (e.g., matrix metalloproteinase secretion, actin cytoskeleton reorganization, migration, and angiogenesis) [1]. The importance of substrates and products of PAF-AH on key cellular functions has been evaluated in cell-based analyses which revealed that these metabolites can have pro- and antitumorigenic functions. Studies in genetically engineered mice lacking PAF-AH expression and genetic manipulation of PAF-AH levels in cancer cells demonstrated diverse functions of the protein in models of melanoma, prostate cancer, colon cancer, and others. The following sections highlight lessons learned from studies in cell lines and in mouse models regarding the diversity of functions of PAF-AH in cancer, and the potential of PAFAH transcripts, protein, and/or activity levels to become cancer biomarkers and therapeutic targets.

Trial Watch: Immunomodulatory monoclonal antibodies for oncological indications

Immunomodulatory monoclonal antibodies (mAbs) differ from their tumor-targeting counterparts because they exert therapeutic effects by directly interacting with soluble or (most often) cellular components of the immune system. Besides holding promise for the treatment of autoimmune and inflammatory disorders, immunomodulatory mAbs have recently been shown to constitute a potent therapeutic weapon against neoplastic conditions. One class of immunomodulatory mAbs operates by inhibiting safeguard systems that are frequently harnessed by cancer cells to establish immunological tolerance, the so-called "immune checkpoints." No less than 3 checkpoint-blocking mAbs have been approved worldwide for use in oncological indications, 2 of which during the past 12 months. These molecules not only mediate single-agent clinical activity in patients affected by specific neoplasms, but also significantly boost the efficacy of several anticancer chemo-, radio- or immunotherapies. Here, we summarize recent advances in the development of checkpoint-blocking mAbs, as well as of immunomodulatory mAbs with distinct mechanisms of action.

Combining chemotherapy and checkpoint blockade in thoracic cancer: how to proceed?

SUMMARY 

Given the impressive efficacy of immune checkpoint blockade in thoracic malignancies, and the recently discovered immune-stimulating properties of many cytotoxic drugs, a logical next step would be to combine these treatments. However, the rational design of clinical trials investigating these combinations is hampered by a lack of knowledge regarding the overall immunogenic effects of the different chemotherapeutics. Here, we give an overview of the field with regard to checkpoint blockade and the immunological effects of cytotoxic chemotherapeutics, with particular focus on preclinical and clinical studies investigating the combination of these two treatment modalities. We discuss the hurdles that need to be overcome in order to optimally exploit chemotherapy and immune checkpoint blockade combinations in thoracic cancers.

Transcriptional profiling of whole blood: a rich source of immune biomarkers in cancer

Immunotherapy is at the forefront of cancer treatment, and biomarkers are urgently needed to predict patient response to therapy. Recently, we discovered a 4-gene peripheral blood mRNA signature for prolonged survival in patients treated with tremelimumab. Peripheral blood mRNA is a readily accessible and under-utilized source of clinically relevant biomarkers.