Closed system RT-qPCR as a potential companion diagnostic test for immunotherapy outcome in metastatic melanoma

Multi-Institutional Study of Pathologist Reading of the Programmed Cell Death Ligand-1 Combined Positive Score Immunohistochemistry Assay for Gastric or Gastroesophageal Junction Cancer

The assessment of the expression of programmed cell death ligand-1 (PD-L1) using immunohistochemistry (IHC) has been controversial since its introduction. The methods of assessment and the range of assays and platforms contribute to confusion. Perhaps the most challenging aspect of PD-L1 IHC is the combined positive score (CPS) method of interpretation of IHC results. Although the CPS method is prescribed for more indications than any other PD-L1 scoring system, its reproducibility has never been rigorously assessed. In this study, we collected a series of 108 gastric or gastroesophageal junction cancer cases, stained them using the Food and Drug Administration-approved 22C3 assay, scanned them, and then circulated them to 14 pathologists at 13 institutions for the assessment of interpretative concordance for the CPS system. We found that higher cut points (10 or 20) performed better than a CPS of <1 or >1. We used the Observers Needed to Evaluate Subjective Tests algorithm to assess how the CPS system might perform in the real-world setting and found that the cut points of <1 or >1 showed an overall percent agreement of only 30% among the pathologist raters, with a plateau occurring at 8 raters. The raters performed better at higher cut points. However, the best cut point of <20 versus that of >20 was still disappointing, with a plateau at an overall percent agreement of 70% (at 7 raters). Although there is no ground truth for CPS, we compared the score with quantitative messenger RNA measurement and showed no relationship between the score (at any cut point) and messenger RNA amount. In summary, we showed that CPS shows high subjective variability among pathologist readers and is likely to perform poorly in the real-world setting. This system may be the root cause of the poor specificity and relatively low predictive value of IHC companion diagnostic tests for PD-1 axis therapies that use the CPS system.

Regulated cell death in cancer: from pathogenesis to treatment

ABSTRACT

Regulated cell death (RCD), including apoptosis, pyroptosis, necroptosis, and ferroptosis, is regulated by a series of evolutionarily conserved pathways, and is required for development and tissue homeostasis. Based on previous genetic and biochemical explorations of cell death subroutines, the characteristics of each are generally considered distinctive. However, recent in-depth studies noted the presence of crosstalk between the different forms of RCD; hence, the concept of PANoptosis appeared. Cancer, a complex genetic disease, is characterized by stepwise deregulation of cell apoptosis and proliferation, with significant morbidity and mortality globally. At present, studies on the different RCD pathways, as well as the intricate relationships between different cell death subroutines, mainly focus on infectious diseases, and their roles in cancer remain unclear. As cancers are characterized by dysregulated cell death and inflammatory responses, most current treatment strategies aim to selectively induce cell death via different RCD pathways in cancer cells. In this review, we describe five types of RCD pathways in detail with respect to tumorigenesis and cancer progression. The potential value of some of these key effector molecules in tumor diagnosis and therapeutic response has also been raised. We then review and highlight recent progress in cancer treatment based on PANoptosis and ferroptosis induced by small-molecule compounds, immune checkpoint inhibitors, and nanoparticles. Together, these findings may provide meaningful evidence to fill in the gaps between cancer pathogenesis and RCD pathways to develop better cancer therapeutic strategies.

A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma

Cutaneous melanoma (CM) is an aggressive form of malignancy with poor prognostic value. Cuproptosis is a novel type of cell death regulatory mechanism in tumors. However, the role of cuproptosis-related long noncoding RNAs (lncRNAs) in CM remains elusive. The cuproptosis-related lncRNAs were identified using the Pearson correlation algorithm. Through the univariate and multivariate Cox regression analysis, the prognosis of seven lncRNAs associated with cuproptosis was established and a new risk model was constructed. ESTIMATE, CIBERSORT, and single sample gene set enrichment analyses (ssGSEA) were applied to evaluate the immune microenvironment landscape. The Kaplan–Meier survival analysis revealed that the overall survival (OS) of CM patients in the high-risk group was remarkably lower than that of the low-risk group. The result of the validated cohort and the training cohort indicated that the risk model could produce an accurate prediction of the prognosis of CM. The nomogram result demonstrated that the risk score based on the seven prognostic cuproptosis-related lncRNAs was an independent prognostic indicator feature that distinguished it from other clinical features. The result of the immune microenvironment landscape indicated that the low-risk group showed better immunity than high-risk group. The immunophenoscore (IPS) and immune checkpoints results conveyed a better benefit potential for immunotherapy clinical application in the low-risk groups. The enrichment analysis and the gene set variation analysis (GSVA) were adopted to reveal the role of cuproptosis-related lncRNAs mediated by the immune-related signaling pathways in the development of CM. Altogether, the construction of the risk model based on cuproptosis-related lncRNAs can accurately predict the prognosis of CM and indicate the immune microenvironment of CM, providing a new perspective for the future clinical treatment of CM.

PD-L1 and PD-L2 mRNA measured using closed system qRT-PCR are associated with outcome and high negative predictive value in immunotherapy-treated non-small cell lung cancer

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have become standard of care in lung cancer management, but only a relatively small percentage of patients treated respond. Current predictive biomarkers, including immunohistochemical (IHC) detection of PD-L1, are insufficient for determining who will respond or, more importantly in the adjuvant setting, who will not respond to ICI therapy. Here, we investigate an alternative method of assessment of PD-L1 to predict non-response.

METHODS

This study utilizes a research use only quantitative real-time reverse transcription polymerase chain reaction assay on the GeneXpert® (GX) system, to test for the association between 4 target immune genes, CD274 (PD-L1), PDCD1LG2 (PD-L2), CD8A, and IRF1, and response to ICI therapy. Tissues were collected from 122 patients with advanced non-small cell lung cancer prior to ICI therapy in a retrospective cohort, macro-dissected, and analyzed using the GX.

RESULTS

Both high PD-L1 and PD-L2 mRNA expression levels were associated with improved long-term benefit at 24 months (p=0.047 for both PD-L1 and PD-L2) and overall survival (PD-L1, p= 0.048; PD-L2 p= 0.049). Both PD-L1 and PD-L2 mRNA levels were higher in patients with KRAS mutations. Most importantly, low PD-L1 mRNA showed a high negative predictive value of 0.92 for absence of long-term benefit.

CONCLUSIONS

With further validation this assay in low stage patients, assessment of PD-L1 mRNA rather than protein, could be a method to determine which low stage patients should not be treated with ICIs in the adjuvant setting. This approach may also be a useful objective method for selecting patients for treatment in the advanced setting.

Development of an automated liquid biopsy assay for methylated markers in advanced breast cancer

Current molecular liquid biopsy assays to detect recurrence or monitor response to treatment require sophisticated technology, highly trained personnel, and a turnaround time of weeks. We describe the development and technical validation of an automated Liquid Biopsy for Breast Cancer Methylation (LBx-BCM) prototype, a DNA methylation detection cartridge assay that is simple to perform and quantitatively detects nine methylated markers within 4.5 h. LBx-BCM demonstrated high interassay reproducibility when analyzing exogenous methylated DNA (75-300 DNA copies) spiked into plasma (Coefficient of Variation, CV = 7.1 - 10.9%) and serum (CV = 19.1 - 36.1%). It also demonstrated high interuser reproducibility (Spearman r = 0.887, P < 0.0001) when samples of metastatic breast cancer (MBC, N = 11) and normal control (N = 4) were evaluated independently by two users. Analyses of interplatform reproducibility indicated very high concordance between LBx-BCM and the reference assay, cMethDNA, among 66 paired plasma samples (MBC N = 40, controls N = 26; Spearman r = 0.891; 95% CI = 0.825 - 0.933, P< 0.0001). LBx-BCM achieved a ROC AUC = 0.909 (95% CI = 0.836 - 0.982), 83% sensitivity and 92% specificity; cMethDNA achieved a ROC AUC = 0.896 (95% CI = 0.817 - 0.974), 83% sensitivity and 92% specificity in test set samples. The automated LBx-BCM cartridge prototype is fast, with performance levels equivalent to the highly sensitive, manual cMethDNA method. Future prospective clinical studies will evaluate LBx-BCM detection sensitivity and its ability to monitor therapeutic response during treatment for advanced breast cancer.

Expression of CD274 mRNA Measured by qRT-PCR Correlates With PD-L1 Immunohistochemistry in Gastric and Urothelial Carcinoma

Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is widely used to predict the clinical responses to immune checkpoint inhibitors (ICIs). However, PD-L1 IHC suffers from the complexity of multiple testing platforms and different cutoff values caused by the current one drug-one diagnostic test co-development approach for ICIs. We aimed to test whether PD-L1 (CD274) mRNA expression levels measured using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) can represent PD-L1 IHC and predict responses to ICI. The FDA-approved PD-L1 IHC results with 22C3 pharmDx (gastric cancer) and SP142 (urothelial carcinoma) were compared with CD274 mRNA expression levels via qRT-PCR using the same formalin-fixed, paraffin-embedded tissue blocks from 59 gastric cancer and 41 urothelial carcinoma samples. CD274 mRNA expression was identified using three independent sets of primers and TaqMan® probes targeting exon 1-2, exon 3-4, and exon 5-6. CD274 mRNA levels in spanning exon 1-2, exon 3-4, and exon 5-6 junctions of CD274 correlated well with PD-L1 expression (r²=0.81, 0.65, and 0.59, respectively). The area under the curve of exon 1-2 was the highest (0.783), followed by exon 3-4 (0.701), and exon 5-6 (0.671) of the CD274 gene against the PD-L1 combined positive score cutoff of 10. When CD274 mRNA expression was matched for response to immunotherapy, the overall response rate was higher in patients with high CD274 mRNA levels with a cutoff of 0.0722 (gastric cancer) and 0.0480 (urothelial carcinoma) than in those with low CD274 mRNA expression (P < 0.001 and P = 0.018, respectively). These results show that CD274 mRNA levels predicted ICI responses in patients with gastric or urothelial carcinomas and could be used as alternatives for PD-L1 IHC.

Inhibition of renalase drives tumour rejection by promoting T cell activation

BACKGROUND

Although programmed cell death protein 1 (PD-1) inhibitors have revolutionised treatment for advanced melanoma, not all patients respond. We previously showed that inhibition of the flavoprotein renalase (RNLS) in preclinical melanoma models decreases tumour growth. We hypothesised that RNLS inhibition promotes tumour rejection by effects on the tumour microenvironment (TME).

METHODS

We used two distinct murine melanoma models, studied in RNLS knockout (KO) or wild-type (WT) mice. WT mice were treated with the anti-RNLS antibody, m28, with or without anti-PD-1. 10X single-cell RNA-sequencing was used to identify transcriptional differences between treatment groups, and tumour cell content was interrogated by flow cytometry. Samples from patients treated with immunotherapy were examined for RNLS expression by quantitative immunofluorescence.

RESULTS

RNLS KO mice injected with wild-type melanoma cells reject their tumours, supporting the importance of RNLS in cells in the TME. This effect was blunted by anti-cluster of differentiation 3. However, MØ-specific RNLS ablation was insufficient to abrogate tumour formation. Anti-RNLS antibody treatment of melanoma-bearing mice resulted in enhanced T cell infiltration and activation and resulted in immune memory on rechallenging mice with injection of melanoma cells. At the single-cell level, treatment with anti-RNLS antibodies resulted in increased tumour density of MØ, neutrophils and lymphocytes and increased expression of IFNγ and granzyme B in natural killer cells and T cells. Intratumoural Forkhead Box P3 + CD4 cells were decreased. In two distinct murine melanoma models, we showed that melanoma-bearing mice treated with anti-RNLS antibodies plus anti-PD-1 had superior tumour shrinkage and survival than with either treatment alone. Importantly, in pretreatment samples from patients treated with PD-1 inhibitors, high RNLS expression was associated with decreased survival (log-rank P = 0.006), independent of other prognostic variables.

CONCLUSIONS

RNLS KO results in melanoma tumour regression in a T-cell-dependent fashion. Anti-RNLS antibodies enhance anti-PD-1 activity in two distinct aggressive murine melanoma models resistant to PD-1 inhibitors, supporting the development of anti-RNLS antibodies with PD-1 inhibitors as a novel approach for melanomas poorly responsive to anti-PD-1.

Potential prognostic value of PD-L1 and NKG2A expression in Indonesian patients with skin nodular melanoma

OBJECTIVE

Biomarker mRNA levels have been suggested to be predictors of patient survival and therapy response in melanoma cases. This study aimed to investigate the correlations between the mRNA expression levels of PD-L1 and NKG2A in melanoma tissue with clinicopathologic characteristics and survival in Indonesian primary nodular melanoma patients.

RESULTS

Thirty-one tissue samples were obtained; two were excluded from survival analysis due to Breslow depth of less than 4 mm. The median survival of upregulated and normoregulated PD-L1-patients were 15.800 ± 2.345 and 28.945 ± 4.126 months, respectively. However, this difference was not significant statistically (p = 0.086). Upregulated and normoregulated NKG2A patients differed very little in median survival time (25.943 ± 7.415 vs 26.470 ± 3.854 months; p = 0.981). Expression of PD-L1 and NKG2A were strongly correlated (r_s: 0.787, p < 0.001). No clinicopathologic associations with PD-L1 and NKG2A mRNA levels were observed. These results suggest that PD-L1 may have potential as a prognostic factor. Although an unlikely prognostic factor, NKG2A may become an adjunct target for therapy. The strong correlation between PD-L1 and NKG2A suggests that anti-PD-1 and anti-NKG2A agents could be effective in patients with PD-L1 upregulation. The mRNA levels of these two genes may help direct choice of immunotherapy and predict patient outcomes.

Find the Flame: Predictive Biomarkers for Immunotherapy in Melanoma

Immunotherapy has revolutionized the therapeutic landscape of melanoma. In particular, checkpoint inhibition has shown to increase long-term outcome, and, in some cases, it can be virtually curative. However, the absence of clinically validated predictive biomarkers is one of the major causes of unpredictable efficacy of immunotherapy. Indeed, the availability of predictive biomarkers could allow a better stratification of patients, suggesting which type of drugs should be used in a certain clinical context and guiding clinicians in escalating or de-escalating therapy. However, the difficulty in obtaining clinically useful predictive biomarkers reflects the deep complexity of tumor biology. Biomarkers can be classified as tumor-intrinsic biomarkers, microenvironment biomarkers, and systemic biomarkers. Herein we review the available literature to classify and describe predictive biomarkers for checkpoint inhibition in melanoma with the aim of helping clinicians in the decision-making process. We also performed a meta-analysis on the predictive value of PDL-1.

Biomarkers in Precision Cancer Immunotherapy: Promise and Challenges

The rapid expansion of modern cancer immunotherapeutics has led to a dramatic improvement in patient survival and sustained remission for otherwise refractory malignancies. However, a significant limitation behind these current treatment modalities is an irregularity in clinical response, which is especially pronounced among checkpoint inhibition. This unpredictability leads to significant side effects, financial costs, and health care burden, with unsatisfactory clinical benefit in the majority of treated patients. Additionally, although ongoing studies and trials investigate the use of multiple biomarkers predictive of patient response or harm, none of these are comprehensive in predicting potential benefit. This unmet need for validated biomarkers is largely secondary to a prohibitive complexity within tumor parenchyma and microenvironment, dynamic clonal and proteomic changes to therapy, heterogenous host immune defects, and varied standardization among sample preparation and reporting. Herein, we discuss current advantages of predictive biomarkers, as well as limitations in their clinical use and application. We also review future directions, ideal characteristics, and trial design needed for proper precision immuno-oncology and biomarker development.

CTLA-4 blockade and interferon-α induce proinflammatory transcriptional changes in the tumor immune landscape that correlate with pathologic response in melanoma

Patients with locally/regionally advanced melanoma were treated with neoadjuvant combination immunotherapy with high-dose interferon α-2b (HDI) and ipilimumab in a phase I clinical trial. Tumor specimens were obtained prior to the initiation of neoadjuvant therapy, at the time of surgery and progression if available. In this study, gene expression profiles of tumor specimens (N = 27) were investigated using the NanoString nCounter® platform to evaluate associations with clinical outcomes (pathologic response, radiologic response, relapse-free survival (RFS), and overall survival (OS)) and define biomarkers associated with tumor response. The Tumor Inflammation Signature (TIS), an 18-gene signature that enriches for response to Programmed cell death protein 1 (PD-1) checkpoint blockade, was also evaluated for association with clinical response and survival. It was observed that neoadjuvant ipilimumab-HDI therapy demonstrated an upregulation of immune-related genes, chemokines, and transcription regulator genes involved in immune cell activation, function, or cell proliferation. Importantly, increased expression of baseline pro-inflammatory genes CCL19, CD3D, CD8A, CD22, LY9, IL12RB1, C1S, C7, AMICA1, TIAM1, TIGIT, THY1 was associated with longer OS (p < 0.05). In addition, multiple genes that encode a component or a regulator of the extracellular matrix such as MMP2 and COL1A2 were identified post-treatment as being associated with longer RFS and OS. In all baseline tissues, high TIS scores were associated with longer OS (p = 0.0166). Also, downregulated expression of cell proliferation-related genes such as CUL1, CCND1 and AAMP at baseline was associated with pathological and radiological response (unadjusted p < 0.01). In conclusion, we identified numerous genes that play roles in multiple biological pathways involved in immune activation, immune suppression and cell proliferation correlating with pathological/radiological responses following neoadjuvant immunotherapy highlighting the complexity of immune responses modulated by immunotherapy. Our observations suggest that TIS may be a useful biomarker for predicting survival outcomes with combination immunotherapy.

Interferon regulatory factor 1 (IRF-1) and IRF-2 regulate PD-L1 expression in hepatocellular carcinoma (HCC) cells

The objective response rate of immune checkpoint blockade (ICB) in hepatocellular carcinoma (HCC) with anti PD-L1/PD-1 therapy is low. Discovering the signaling pathways regulating PD-L1 might help to improve ICB response rates. Here, we investigate transcription factors IRF-1 and IRF-2 signaling pathways regulating PD-L1 in HCC cells. In vivo studies show that IRF-1 and PD-L1 mRNA expression in human HCC tumors are significantly repressed compared with noncancerous background liver. IRF-1, IRF-2, and PD-L1 mRNA expression correlated positively in HCC tumors. Increased IRF-1 mRNA expression was observed in patients with well-differentiated or early stage HCC tumors. In vitro studies show that IFN-γ induces PD-L1 mRNA and protein expression through upregulation of IRF-1 in mouse and human HCC cells. IRF-1, IRF-2, and PD-L1 mRNA expression is upregulated in murine HCC by co-culture with effector T cells from spleen cells incubated with anti-CD3/CD28 antibodies. IRF-2 over-expression down-regulates IFN-γ induced PD-L1 promoter activity and protein levels in a dose-dependent manner. We identify two IRF-1 response elements (IRE1/IRE2) in the upstream 5'-flanking region of the CD274 (PD-L1) gene promoter. Site-directed mutagenesis shows both IRE1 and IRE2 are functional in transfection promoter assays. IRF-1 traditionally functions as tumor suppressor gene. However, these novel findings show a complex role for IRF-1 which upregulates PD-L1 in the inflammatory tumor microenvironment. IRF-1 antagonizes IRF-2 for binding to the IRE promoter element in PD-L1 which gives new insight to the regulation of PD-L1/PD-1 pathways in HCC ICB therapy.

PD-1 mRNA expression in peripheral blood mononuclear cells as a biomarker for different stages of primary gouty arthritis

There is currently a lack of biomarkers to assist the diagnosis and prediction of primary gouty arthritis (PG). Therefore, we evaluated the clinical value of programmed cell death protein 1 (PD-1) mRNA expression in peripheral blood mononuclear cells (PBMCs) of patients with PG. This study included 36 patients with acute phase PG (APPG), 48 with non-acute phase PG (NAPPG), 42 with asymptomatic hyperuricemia (AH) and 79 normal controls (NCs). PD-1 mRNA expression levels were detected by qRT-PCR. PD-1 mRNA expression was statistically analysed by ANOVA or t tests, while correlations between PD-1 mRNA and clinical variables were assessed using Pearson correlation tests. Receiver operator characteristic (ROC) curve analysis was used to evaluate the diagnostic value of PD-1 in different PG stages. PD-1 mRNA expression was significantly lower in patients with APPG than that in NAPPG, AH and NCs (P < 0.01). Correlation analysis revealed that PD-1 mRNA levels correlated negatively with T-score (r = -0.209, P < 0.01). ROC curve analysis showed that serum uric acid (SUA), PD-1 mRNA and both combined displayed higher diagnostic value in patients with PG, NAPPG and APPG compared to that in NCs and patients with non-PG arthritis (NPG). Moreover, ROC curve analysis showed that SUA and PD-1 mRNA had good diagnostic value in APPG, with the greatest diagnostic power when combined. PD-1 mRNA could be a clinical auxiliary diagnostic biomarker for APPG, and the combined use of PD-1 mRNA and SUA is better than that of SUA alone.