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The harmful side effects of opioid drugs such as respiratory depression, tolerance, dependence, and abuse potential have limited the therapeutic utility of opioids for their entire clinical history. However, no previous attempt to develop effective pain drugs that substantially ameliorate these effects has succeeded, and the current opioid epidemic affirms that they are a greater hindrance to the field of pain management than ever. Recent attempts at new opioid development have sought to reduce these side effects by minimizing engagement of the regulatory protein arrestin-3 at the mu-opioid receptor, but there is significant controversy around this approach. Here, we discuss the ongoing effort to develop safer opioids and its relevant historical context. We propose a new model that reconciles results previously assumed to be in direct conflict to explain how different signaling profiles at the mu-opioid receptor contribute to opioid tolerance and dependence. Our goal is for this framework to inform the search for a new generation of lower liability opioid analgesics.

IntroductionOpioid drugs are potent analgesics that mimic the endogenous opioid peptides, endorphins and enkephalins, by activating the µ-opioid receptor. Opioid use is limited by side effects, including significant risk of opioid use disorder. Improvement of the effect/side effect profile of opioid medications is a key pursuit of opioid research, yet there is no consensus on how to achieve this goal. One hypothesis is that the degree of arrestin-3 recruitment to the µ-opioid receptor impacts therapeutic utility. However, it is not clear whether increased or decreased interaction of the µ-opioid receptor with arrestin-3 would reduce compulsive drug-seeking.MethodsWe utilized three genotypes of mice with varying abilities to recruit arrestin-3 to the µ-opioid receptor in response to morphine in a novel longitudinal operant self-administration model. We also created a quantitative method to define compulsivity in drug-seeking based on a multi-variate analysis of several operant response variables.ResultsWe demonstrate that arrestin-3 knockout and wild type mice have highly variable drug-seeking behavior with few genotype differences. In contrast, in mice where the µ-opioid receptor strongly recruits arrestin-3, drug-seeking behavior is much less varied. We found that mice lacking arrestin-3 were more likely to meet the criteria for compulsivity whereas mice with enhanced arrestin-3 recruitment did not develop a compulsive phenotype.ConclusionThese experiments show that a lack of arrestin-3 is not protective against the abuse liability of morphine in an operant self-administration context. Our data also suggest that opioids that engage both G protein and arrestin-3, recapitulating the endogenous signaling pattern, will reduce abuse liability.

Abstract Extremely rapid rates of rise in level and discharge in a subset of flash floods (‘abrupt wave front floods’, AWF) are separate hazards from peak level. Such flood events are investigated for Pennine catchments in northern England using both gauged and historical information. Gauged level and flow digital records at 15‐min intervals provide recent data. Historical information for 122 AWF events is extracted from a chronology of flash floods for Britain. Historical AWF events are mapped and found to occur on every major Pennine catchment; catchment descriptors are derived as a basis for assessing catchment vulnerability. We discuss the disputed origin of AWF. Using gauged data, we contrast the rising limb of AWF and ‘normal’ floods. We investigate time series of historical AWF, noting a puzzling peak in the late 19th century. Current rainfall and river monitoring does not provide a reliable basis for understanding AWF processes or for operational response and we suggest improvements. Similarly, current models for design flood estimation and forecasting do not generate the observed rapid increase in level in AWF floods.

Therapies targeting the programmed cell death protein-1/programmed death-ligand 1 (PD-L1) (abbreviated as PD-(L)1) axis are a significant advancement in the treatment of many tumor types. However, many patients receiving these agents fail to respond or have an initial response followed by cancer progression. For these patients, while subsequent immunotherapies that either target a different axis of immune biology or non-immune combination therapies are reasonable treatment options, the lack of predictive biomarkers to follow-on agents is impeding progress in the field. This review summarizes the current knowledge of mechanisms driving resistance to PD-(L)1 therapies, the state of biomarker development along this axis, and inherent challenges in future biomarker development for these immunotherapies. Innovation in the development and application of novel biomarkers and patient selection strategies for PD-(L)1 agents is required to accelerate the delivery of effective treatments to the patients most likely to respond.

Non-stationary methods of flood frequency analysis are widespread in research but rarely implemented by practitioners. One reason may be that research papers on non-stationary statistical models tend to focus on model fitting rather than extracting the sort of results needed by designers and decision makers. It can be difficult to extract useful results from non-stationary models that include stochastic covariates for which the value in any future year is unknown. We explore the motivation for including such covariates, whether on their own or in addition to a covariate based on time. We set out a method for expressing the results of non-stationary models as an integrated flow estimate, which removes the dependence on the covariates. This can be defined either for a particular year or over a longer period of time. The methods are illustrated by application to a set of 375 river gauges across England and Wales. We find annual rainfall to be a useful covariate at many gauges, sometimes in conjunction with a time-based covariate. For estimating flood frequency in future conditions, we advocate exploring hybrid approaches that combine the best attributes of non-stationary statistical models and simulation models that can represent changes in climate and river catchments. HIGHLIGHTS We explore why and how to include physical variables as covariates in statistical models of flood frequency.; We develop and illustrate methods for extracting flow estimates from such models so that practitioners can obtain useful results.; Practitioners now have tools and guidance to apply non-stationary methods for flood management in England.;

Summary: Background: Tertiary Lymphoid Structures (TLS) correlate with positive outcomes in patients with NSCLC and the efficacy of immune checkpoint blockade (ICB) in cancer. The actin regulatory protein hMENA undergoes tissue-specific splicing, producing the epithelial hMENA11a linked to favorable prognosis in early NSCLC, and the mesenchymal hMENAΔv6 found in invasive cancer cells and pro-tumoral cancer-associated fibroblasts (CAFs). This study investigates how hMENA isoforms in tumor cells and CAFs relate to TLS presence, localization and impact on patient outcomes and ICB response. Methods: Methods involved RNA-SEQ on NSCLC cells with depleted hMENA isoforms. A retrospective observational study assessed tissues from surgically treated N0 patients with NSCLC, using immunohistochemistry for tumoral and stromal hMENA isoforms, fibronectin, and TLS presence. ICB-treated patient tumors were analyzed using Nanostring nCounter and GeoMx spatial transcriptomics. Multiparametric flow cytometry characterized B cells and tissue-resident memory T cells (TRM). Survival and ICB response were estimated in the cohort and validated using bioinformatics pipelines in different datasets. Findings: Findings indicate that hMENA11a in NSCLC cells upregulates the TLS regulator LTβR, decreases fibronectin, and favors CXCL13 production by TRM. Conversely, hMENAΔv6 in CAFs inhibits LTβR-related NF-kB pathway, reduces CXCL13 secretion, and promotes fibronectin production. These patterns are validated in N0 NSCLC tumors, where hMENA11ahigh expression, CAF hMENAΔv6low, and stromal fibronectinlow are associated with intratumoral TLS, linked to memory B cells and predictive of longer survival. The hMENA isoform pattern, fibronectin, and LTβR expression broadly predict ICB response in tumors where TLS indicates an anti-tumor immune response. Interpretation: This study uncovers hMENA alternative splicing as an unexplored contributor to TLS-related Tumor Immune Microenvironment (TIME) and a promising biomarker for clinical outcomes and likely ICB responsiveness in N0 patients with NSCLC. Funding: This work is supported by AIRC (IG 19822), ACC (RCR-2019-23669120), CAL.HUB.RIA Ministero Salute PNRR-POS T4, “Ricerca Corrente” granted by the Italian Ministry of Health.

Abstract Background Identifying response markers is highly needed to guide the treatment strategy in patients with metastatic melanoma. Methods A retrospective study was carried out in patients with unresectable/metastatic melanoma (stage IIIb–IV), treated with anti-PD-1 in the first line setting, to better explore the role and the timing of neutrophil/lymphocyte ratio (NLR) as potential biomarker of response. The relationship of NLR with inflammation-immune mediators and the underlying negative effect of raising NLR during immunotherapy, have been investigated with transcriptomic gene analysis. Results The results confirmed previous findings that a high baseline NLR is associated with a poorer prognosis and with higher serum level of lactate dehydrogenase (LDH), regardless of the presence of brain metastases. The transcriptomic analysis showed that high baseline NLR is associated with a characteristic gene signature CCNA1, LDHA and IL18R1, which correlates with inflammation and tumorigenesis. Conversely, low baseline NLR is associated with the signature CD3, SH2D1A, ZAP70 and CD45RA, linked to the immune-activation. The genes positively associated with NLR (CD39 (ENTPD1), PTEN, MYD88, MMP9 and LDH) are involved in processes of immunosuppression, inflammation and tumor-promoting activity. Increased expression of CD39 correlated with TGFβ2, a marker of the N2 neutrophils with immunosuppressive activity. Conclusions These results suggest that increasing NLR is associated with an increased neutrophil population, with polarization to the N2 phenotype, and this process may be the basis for the negatively prognostic role of NLR.

Resistance biomarkers are needed to identify patients with advanced melanoma obtaining a response to ICI treatment and developing resistance later. We searched a combination of molecular signatures of response to ICIs in patients with metastatic melanoma. In a retrospective study on patients with metastatic melanoma treated with an anti-PD-1 agent carried out at Istituto Nazionale Tumori—IRCCS—Fondazione “G. Pascale”, Naples, Italy. We integrated a whole proteome profiling of metastatic tissue with targeted transcriptomics. To assess the prognosis of patients according to groups of low and high risk, we used PFS and OS as outcomes. To identify the proteins and mRNAs gene signatures associated with the patient’s response groups, the discriminant analysis for sparse data performed via partial least squares procedure was performed. Tissue samples from 22 patients were analyzed. A combined protein and gene signature associated with poorer response to ICI immunotherapy in terms of PFS and OS was identified. The PFS and OS Kaplan–Meier curves were significantly better for patients with high expression of the protein signature compared to patients with low expression of the protein signature and who were high-risk (Protein: HR = 0.023, 95% CI: 0.003–0.213; p < 0.0001. Gene: HR = 0.053, 95% CI: 0.011–0.260; p < 0.0001). The Kaplan–Meier curves showed that patients with low-risk gene signatures had better PFS (HR = 0 0.221, 95% CI: 0.071–0.68; p = 0.007) and OS (HR = 0.186, 95% CI: 0.05–0.695; p = 0.005). The proteomic and transcriptomic combined analysis was significantly associated with the outcomes of the anti-PD-1 treatment with a better predictive value compared to a single signature. All the patients with low expression of protein and gene signatures had progression within 6 months of treatment (median PFS = 3 months, 95% CI: 2–3), with a significant difference vs. the low-risk group (median PFS = not reached; p < 0.0001), and significantly poorer survival (OS = 9 months, 95% CI: 5–9) compared to patients with high expression of protein and gene signatures (median OS = not reached; p < 0.0001). We propose a combined proteomic and transcriptomic signature, including genes involved in pro-tumorigenic pathways, thereby identifying patients with reduced probability of response to immunotherapy with ICIs for metastatic melanoma.

Abstract Treatment with immune checkpoint inhibitors has altered the course of malignant melanoma, with approximately half of the patients with advanced disease surviving for more than 5 years after diagnosis. Currently, there are no biomarker methods for predicting outcome from immunotherapy. Here, we obtained transcriptomic information from a total of 105 baseline tumor samples comprising two cohorts of patients with advanced melanoma treated with programmed cell death protein 1 (PD-1)-based immunotherapies. Gene expression profiles were correlated with progression-free survival (PFS) within consecutive clinical benefit intervals (i.e., 6, 12, 18, and 24 months). Elastic net binomial regression models with cross validation were utilized to compare the predictive value of distinct genes across time. Lasso regression was used to generate a signature predicting long-term benefit (LTB), defined as patients who remain alive and free of disease progression at 24 months post treatment initiation. We show that baseline gene expression profiles were consistently able to predict long-term immunotherapy outcomes with high accuracy. The predictive value of different genes fluctuated across consecutive clinical benefit intervals, with a distinct set of genes defining benefit at 24 months compared to earlier outcomes. A 12-gene signature was able to predict LTB following anti-PD-1 therapy with an area under the curve (AUC) equal to 0.92 and 0.74 in the training and validation set, respectively. Evaluation of LTB, via a unique signature may complement objective response classification and characterize the logistics of sustained antitumor immune responses.

Abstract Background The clinical observation showed a potential additive effect of anti-PD-1 agents and cetirizine in patients with advanced melanoma. Methods Clinical outcomes of concomitant cetirizine/anti-PD-1 treatment of patients with stage IIIb–IV melanoma were retrospectively collected, and a transcriptomic analysis was performed on blood samples obtained at baseline and after 3 months of treatment. Results Patients treated with cetirizine concomitantly with an anti-PD-1 agent had significantly longer progression-free survival (PFS; mean PFS: 28 vs 15 months, HR 0.46, 95% CI: 0.28–0.76; p = 0.0023) and OS (mean OS was 36 vs 23 months, HR 0.48, 95% CI: 0.29–0.78; p = 0.0032) in comparison with those not receiving cetirizine. The concomitant treatment was significantly associated with ORR and DCR (p

Background Understanding how cancer signaling pathways promote an immunosuppressive program which sustains acquired or primary resistance to immune checkpoint blockade (ICB) is a crucial step in improving immunotherapy efficacy. Among the pathways that can affect ICB response is the interferon (IFN) pathway that may be both detrimental and beneficial. The immune sensor retinoic acid-inducible gene I (RIG-I) induces IFN activation and secretion and is activated by actin cytoskeleton disturbance. The actin cytoskeleton regulatory protein hMENA, along with its isoforms, is a key signaling hub in different solid tumors, and recently its role as a regulator of transcription of genes encoding immunomodulatory secretory proteins has been proposed. When hMENA is expressed in tumor cells with low levels of the epithelial specific hMENA11a isoform, identifies non-small cell lung cancer (NSCLC) patients with poor prognosis. Aim was to identify cancer intrinsic and extrinsic pathways regulated by hMENA11a downregulation as determinants of ICB response in NSCLC. Here, we present a potential novel mechanism of ICB resistance driven by hMENA11a downregulation.Methods Effects of hMENA11a downregulation were tested by RNA-Seq, ATAC-Seq, flow cytometry and biochemical assays. ICB-treated patient tumor tissues were profiled by Nanostring IO 360 Panel enriched with hMENA custom probes. OAK and POPLAR datasets were used to validate our discovery cohort.Results Transcriptomic and biochemical analyses demonstrated that the depletion of hMENA11a induces IFN pathway activation, the production of different inflammatory mediators including IFNβ via RIG-I, sustains the increase of tumor PD-L1 levels and activates a paracrine loop between tumor cells and a unique macrophage subset favoring an epithelial-mesenchymal transition (EMT). Notably, when we translated our results in a clinical setting of NSCLC ICB-treated patients, transcriptomic analysis revealed that low expression of hMENA11a, high expression of IFN target genes and high macrophage score identify patients resistant to ICB therapy.Conclusions Collectively, these data establish a new function for the actin cytoskeleton regulator hMENA11a in modulating cancer cell intrinsic type I IFN signaling and extrinsic mechanisms that promote protumoral macrophages and favor EMT. These data highlight the role of actin cytoskeleton disturbance in activating immune suppressive pathways that may be involved in resistance to ICB in NSCLC.

Although many studies highlight the implication of circular RNAs (circRNAs) in carcinogenesis and tumor progression, their potential as cancer biomarkers has not yet been fully explored in the clinic due to the limitations of current quantification methods. Here, we report the use of the nCounter platform as a valid technology for the analysis of circRNA expression patterns in non‐small cell lung cancer (NSCLC) specimens. Under this context, our custom‐made circRNA panel was able to detect circRNA expression both in NSCLC cells and formalin‐fixed paraffin‐embedded (FFPE) tissues. CircFUT8 was overexpressed in NSCLC, contrasting with circEPB41L2, circBNC2, and circSOX13 downregulation even at the early stages of the disease. Machine learning (ML) approaches from different paradigms allowed discrimination of NSCLC from nontumor controls (NTCs) with an 8‐circRNA signature. An additional 4‐circRNA signature was able to classify early‐stage NSCLC samples from NTC, reaching a maximum area under the ROC curve (AUC) of 0.981. Our results not only present two circRNA signatures with diagnosis potential but also introduce nCounter processing following ML as a feasible protocol for the study and development of circRNA signatures for NSCLC.

Abstract Trastuzumab acts in part through the adaptive immune system. Previous studies showed that enrichment of immune-related gene expression was associated with improved outcomes in HER2-positive (HER2+) breast cancer. However, the role of the immune system in response to lapatinib is not fully understood. Gene expression analysis was performed in 1,268 samples from the North Central Cancer Treatment Group (NCCTG) N9831 and 244 samples from the NeoALTTO trial. In N9831, enrichment of CD45 and immune-subset signatures were significantly associated with improved outcomes. We identified a novel 17-gene adaptive immune signature (AIS), which was found to be significantly associated with improved RFS among patients who received adjuvant trastuzumab (HR 0.66, 95% CI 0.49–0.90, Cox regression model p = 0.01) but not in patients who received chemotherapy alone (HR 0.96, 95% CI 0.67–1.40, Cox regression model p = 0.97). This result was validated in NeoALTTO. Overall, AIS-low patients had a significantly lower pathologic complete response (pCR) rate compared with AIS-high patients (χ2 p

Introduction: Opioid drugs are potent analgesics that mimic the endogenous opioid peptides, endorphins and enkephalins, by activating the µ-opioid receptor. Opioid use is limited by side effects, including significant risk of opioid use disorder. Improvement of the effect/side effect profile of opioid medications is a key pursuit of opioid research, yet there is no consensus on how to achieve this goal. One hypothesis is that the degree of arrestin-3 recruitment to the µ-opioid receptor impacts therapeutic utility. However, it is not clear whether increased or decreased interaction of the µ-opioid receptor with arrestin-3 would reduce compulsive drug-seeking. Methods: We utilized three genotypes of mice with varying abilities to recruit arrestin-3 to the µ-opioid receptor in response to morphine in a novel longitudinal operant self-administration model. We also created a quantitative method to define compulsivity in drug-seeking based on a multi-variate analysis of several operant response variables. Results: We demonstrate that arrestin-3 knockout and wild type mice have highly variable drug-seeking behavior with few genotype differences. In contrast, in mice where the µ-opioid receptor strongly recruits arrestin-3, drug-seeking behavior is much less varied. We found that mice lacking arrestin-3 were more likely to meet the criteria for compulsivity whereas mice with enhanced arrestin-3 recruitment did not develop a compulsive phenotype. Conclusion: These experiments show that a lack of arrestin-3 is not protective against the abuse liability of morphine in an operant self-administration context. Our data also suggest that opioids that engage both G protein and arrestin-3, recapitulating the endogenous signaling pattern, will reduce abuse liability. [ABSTRACT FROM AUTHOR]

In October 2022, Elon Musk took over Twitter. Although conservatives cheered the takeover, progressives decried it as dangerous for democracy. Despite scholarly interest in Twitter, little is known about the impact of “old” Twitter’s policies on the information environment, making it difficult to speculate about Musk’s effects. The authors begin to address this gap through an analysis of 245,020 tweets collected before and after Twitter suspended eight accounts calling for state audits of the 2020 presidential election results. In this analysis of message amplifiers, or accounts receiving 200 or more retweets, and message drivers, or top-ranked accounts, no evidence is found that the Twitter ban improved the ideas or the quality of information shared about the election, nor did it dramatically change who posted about the audit. The authors conclude with a discussion of the implications of these findings for future research on Twitter under Musk’s control.

The application of circulating tumor cells (CTCs) in both clinical practice and research has been continuously limited by the rare number of targets that can be found in a tube of peripheral blood. Diagnostic leukapheresis (DLA) was used to increase the sampling volume. AdnaTest was used to process the whole leukopak, and the RNAs of captured CTCs was then profiled by NanoString nCounter platform. Spike-in experiments and leukopaks from patients with metastatic prostate cancer were used to validate this new strategy. The whole leukopak was further concentrated five times to reduce the total volume from 150 ​mL to 30 ​mL, which enabled it to be processed by 3 separate AdnaTest kits. The spike-in experiment demonstrated a reliable capture when there were more than 100 cancer cells/10 ​mL of concentrated leukopak. In 1 out of 5 real patient samples, CTCs were only detected in the leukopak, but not in peripheral blood. The RNA profiling of DLA CTCs indicated a more aggressive phenotype of CTCs occurred when the patient was experiencing a disease relapse, even when the serum prostate specific antigen (PSA) level was still relatively low and CTCs in peripheral blood were not detectable. We established a new protocol, integrating DLA, AdnaTest and NanoString nCounter technology, to profile RNAs from CTCs captured from a large blood screening volume. The new protocol can process the whole leukopak with sensitive CTC capture. The RNA profiling of CTCs can provide valuable information for disease monitoring.

Background Nivolumab is an anti-PD-1 antibody approved for treating metastatic melanoma (MM), for which still limited evidence is available on the correlation between drug exposure and patient outcomes.Methods In this observational retrospective study, we assessed whether nivolumab concentration is associated with treatment response in 88 patients with MM and if the patient’s genetic profile plays a role in this association.Results We observed a statistically significant correlation between nivolumab serum concentration and clinical outcomes, measured as overall and progression-free survival. Moreover, patients who achieved a clinical or partial response tended to have higher levels of nivolumab than those who reached stable disease or had disease progression. However, the difference was not statistically significant. In particular, patients who reached a clinical response had a significantly higher concentration of nivolumab and presented a distinct genetic signature, with more marked activation of ICOS and other genes involved in effector T-cells mediated proinflammatory pathways.Conclusions In conclusion, these preliminary results show that in patients with MM, nivolumab concentration correlates with clinical outcomes and is associated with an increased expression of ICOS and other genes involved in the activation of T effectors cells.

Immunotherapy has reshaped the field of cancer therapeutics but the population that benefits are small in many tumor types, warranting a companion diagnostic test. While immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) or mismatch repair (MMR) and polymerase chain reaction (PCR) for microsatellite instability (MSI) are the only approved companion diagnostics others are under consideration. An optimal companion diagnostic test might combine the spatial information of IHC with the quantitative information from RNA expression profiling. Here, we show proof of concept for combination of spatially resolved protein information acquired by the NanoString GeoMx® Digital Spatial Profiler (DSP) with transcriptomic information from bulk mRNA gene expression acquired using NanoString nCounter® PanCancer IO 360™ panel on the same cohort of immunotherapy treated melanoma patients to create predictive models associated with clinical outcomes. We show that the combination of mRNA and spatially defined protein information can predict clinical outcomes more accurately (AUC 0.97) than either of these factors alone.

Abstract Extracellular vesicles (EVs) are double-layered phospholipid membrane vesicles that are released by most cells and can mediate intercellular communication through their RNA cargo. In this study, we tested if the NanoString nCounter platform can be used for the analysis of EV-mRNA. We developed and optimized a methodology for EV enrichment, EV-RNA extraction and nCounter analysis. Then, we demonstrated the validity of our workflow by analyzing EV-RNA profiles from the plasma of 19 cancer patients and 10 controls and developing a gene signature to differentiate cancer versus control samples. TRI reagent outperformed automated RNA extraction and, although lower plasma input is feasible, 500 μL provided highest total counts and number of transcripts detected. A 10-cycle pre-amplification followed by DNase treatment yielded reproducible mRNA target detection. However, appropriate probe design to prevent genomic DNA binding is preferred. A gene signature, created using a bioinformatic algorithm, was able to distinguish between control and cancer EV-mRNA profiles with an area under the ROC curve of 0.99. Hence, the nCounter platform can be used to detect mRNA targets and develop gene signatures from plasma-derived EVs.

Abstract Background Studies carried out in vitro and in a mouse model have shown that BRAF inhibitors enhance the effects of IFN-α on BRAFV600E melanoma cells through the inhibition of ERK. Therefore, the combination of vemurafenib and IFN-α in patients with BRAFV600E melanoma may provide therapeutic benefits; MEK inhibition may prevent the reactivation of the MAPK pathway induced by BRAF inhibitor resistance. Patients and methods In a phase I study, adult patients with advanced BRAFV600-mutated melanoma were treated with vemurafenib + PEG-IFN-α-2b or vemurafenib + cobimetinib + PEG-IFN-α-2b, to assess the safety of the combination and the upregulation of IFN-α/β receptor-1 (IFNAR1). Results Eight patients were treated; 59 adverse events with four serious ones (three related to study treatments) were reported. Patients with a pre-treatment IFNAR1 expression on ≤ 35% melanoma cells had a median progression-free survival of 12.0 months (range: 5.6–18.4 months) and a median overall survival of 31.0 months (range: 19.8–42.2 months), while patients with a pre-treatment IFNAR1 expression on > 35% of melanoma cells had a median progression-free survival of 4.0 months (range: 0–8.8; p = 0.03), and a median overall survival of 5 months (p = 0.02). Following treatment, responders had higher levels of growth-suppressor genes, including GAS1 and DUSP1, and genes involved in a metabolically robust immune response, including FAP. Conclusion Our study supports the overall safety of the vemurafenib + PEG-IFN-α-2b + cobimetinib combination. IFNAR1 expression levels correlated with response to treatment, including survival. Vemurafenib + PEG-IFN-α-2b + cobimetinib would have difficulty finding a niche in the current treatment scenario for advanced melanoma, but we speculate that our findings may contribute to identify subjects particularly responsive to treatment. Trial registration: The study was registered at clinicaltrials.gov (NCT01959633). Registered 10 October 2013, https://clinicaltrials.gov/ct2/show/NCT01959633

Introduction. The objective of this study was to establish a baseline of current use in practice of the Canadian Occupational Performance Measure (COPM) by consulting 33 expert French occupational therapists, who trained in this method between 2012 and 2017 and use of the COPM with their clients. The areas of health intervention are pediatrics, psychiatry, neurology, and geriatrics. An email invitation to participate in the research was therefore sent to 113 occupational therapists. We received 33 responses. Methods. A novel mixed method study combined a Delphi method with a lexical analysis of experts’ responses and principal component analysis (PCA). Results. In the last Delphi round, the consensus of the expert group was attained on 31 benefits and 1 limitation, confirming the generally positive influence of the COPM in French health services. Discussion. The COPM was clearly identified as a tool that supports occupational therapy clinical reasoning, facilitates team decision-making for care pathways, and enables people with disabilities and health conditions to make decisions for their care. Conclusion. The Delphi study revealed that the COPM appears to be well adapted to French culture and should be widely incorporated into preregistration training.

Abstract Background The 18-gene tumor inflammation signature (TIS) is a clinical research assay that enriches for clinical benefit to immune checkpoint blockade. We evaluated its ability to predict clinical benefit of immunotherapy in cancer patients treated with PD-1 checkpoint inhibitors in routine clinical care. Methods The CERTIM cohort is a prospective cohort which includes patients receiving immune checkpoint inhibitors in Cochin University hospital. RNA extracted from 58 archival formalin fixed paraffin embedded tumor blocks (including 38 lung cancers, 5 melanomas, 10 renal carcinomas, 4 urothelial carcinomas and 1 colon carcinoma) was hybridized to a beta version of the NanoString® PanCancer IO360™ CodeSet using nCounter® technology. Gene expression signatures were correlated with tumor responses (by RECIST criteria) and overall survival. PD-L1 immunostaining on tumor cells was assessed in 37 non-small cell lung cancer (NSCLC) samples and tumor mutational burden (TMB) measured by whole exome sequencing in 19 of these. Results TIS scores were significantly associated with complete or partial response to anti-PD-1 treatment in the whole cohort (odds ratio = 2.64, 95% CI [1.4; 6.0], p = 0.008), as well as in the NSCLC population (odds ratio = 3.27, 95% CI [1.2; 11.6], p = 0.03). Patients whose tumor had a high TIS score (upper tertile) showed prolonged overall survival compared to patients whose tumor had lower TIS scores, both in the whole cohort (hazard ratio = 0.37, 95% CI [0.18, 0.76], p = 0.005) and in the NSCLC population (hazard ratio = 0.36, 95% CI [0.14, 0.90], p = 0.02). In the latter, the TIS score was independent from either PD-L1 staining on tumor cells (spearman coefficient 0.2) and TMB (spearman coefficient − 0.2). Conclusions These results indicate that validated gene expression assay measuring the level of tumor microenvironment inflammation such as TIS, are accurate and independent predictive biomarkers and can be easily implemented in the clinical practice.

Abstract Tumor immunology has changed the landscape of cancer treatment. Yet, not all patients benefit as cancer immune responsiveness (CIR) remains a limitation in a considerable proportion of cases. The multifactorial determinants of CIR include the genetic makeup of the patient, the genomic instability central to cancer development, the evolutionary emergence of cancer phenotypes under the influence of immune editing, and external modifiers such as demographics, environment, treatment potency, co-morbidities and cancer-independent alterations including immune homeostasis and polymorphisms in the major and minor histocompatibility molecules, cytokines, and chemokines. Based on the premise that cancer is fundamentally a disorder of the genes arising within a cell biologic process, whose deviations from normality determine the rules of engagement with the host’s response, the Society for Immunotherapy of Cancer (SITC) convened a task force of experts from various disciplines including, immunology, oncology, biophysics, structural biology, molecular and cellular biology, genetics, and bioinformatics to address the complexity of CIR from a holistic view. The task force was launched by a workshop held in San Francisco on May 14–15, 2018 aimed at two preeminent goals: 1) to identify the fundamental questions related to CIR and 2) to create an interactive community of experts that could guide scientific and research priorities by forming a logical progression supported by multiple perspectives to uncover mechanisms of CIR. This workshop was a first step toward a second meeting where the focus would be to address the actionability of some of the questions identified by working groups. In this event, five working groups aimed at defining a path to test hypotheses according to their relevance to human cancer and identifying experimental models closest to human biology, which include: 1) Germline-Genetic, 2) Somatic-Genetic and 3) Genomic-Transcriptional contributions to CIR, 4) Determinant(s) of Immunogenic Cell Death that modulate CIR, and 5) Experimental Models that best represent CIR and its conversion to an immune responsive state. This manuscript summarizes the contributions from each group and should be considered as a first milestone in the path toward a more contemporary understanding of CIR. We appreciate that this effort is far from comprehensive and that other relevant aspects related to CIR such as the microbiome, the individual’s recombined T cell and B cell receptors, and the metabolic status of cancer and immune cells were not fully included. These and other important factors will be included in future activities of the taskforce. The taskforce will focus on prioritization and specific actionable approach to answer the identified questions and implementing the collaborations in the follow-up workshop, which will be held in Houston on September 4–5, 2019.

Abstract Background How the immune microenvironment changes during neoadjuvant chemotherapy of primary breast cancer is not well understood. Methods We analyzed pre- and post-treatment samples from 60 patients using the NanoString PanCancer IO360™ assay to measure the expression of 750 immune-related genes corresponding to 14 immune cell types and various immune functions, and assessed TIL counts and PD-L1 protein expression by immunohistochemistry. Treatment associated changes in gene expression levels were compared using t-test with Bonferroni correction. TIL count, PD-L1 protein and immune metagenes were compared using Wilcoxon test. Baseline immune markers were correlated with pathologic complete response (pCR) using estrogen receptor and treatment arm adjusted logistic regression. Results At baseline, high TIL counts and high expression of chemoattractant cytokines (CCL21, CCL19) and cytotoxic T cell markers were associated with higher pCR rate. High expression of stromal genes (VEGFB, TGFB3, PDGFB, FGFR1, IGFR1), mast and myeloid inflammatory cell metagenes, stem cell related genes (CD90, WNT11, CTNNB1) and CX3CR1, and IL11RA were associated with residual disease (RD). After treatment, in cases with pCR, TIL counts and most immune genes decreased significantly. Among RD cases, TIL counts and PD-L1 expression did not change but cellular stress and hypoxia associated genes (DUSP1, EGR1), and IL6, CD36, CXCL2, CD69 and the IL8/VEGF metagene increased. Conclusions Activated T cells in the tumor microenvironment are associated with pCR whereas stromal functions are associated with residual disease. Most immune functions decrease during neoadjuvant chemotherapy but several immunotherapy targets (PD-L1, IL6, IL8) remain expressed in RD suggesting potential therapeutic strategies.

Abstract Background Clinical benefit from checkpoint inhibitors has been associated in a tumor-agnostic manner with two main tumor traits. The first is tumor antigenicity, which is typically measured by tumor mutation burden, microsatellite instability (MSI), or Mismatch Repair Deficiency using gene sequence platforms and/or immunohistochemistry. The second is the presence of a pre-existing adaptive immune response, typically measured by immunohistochemistry (e.g. single analyte PD-L1 expression) and/or gene expression signatures (e.g. tumor “inflamed” phenotype). These two traits have been shown to provide independent predictive information. Here we investigated the potential of using gene expression to predict tumor MSI, thus enabling the measurement of both tumor antigenicity and the level of tumor inflammation in a single assay, possibly reducing sample requirement, turn-around time, and overall cost. Methods Using The Cancer Genome Atlas RNA-seq datasets with the greatest MSI-H incidence, i.e. those from colon (n = 208), stomach (n = 269), and endometrial (n = 241) cancers, we trained an algorithm to predict tumor MSI from under-expression of the mismatch repair genes MLH1, PMS2, MSH2, and MSH6 and from 10 additional genes with strong pan-cancer associations with tumor hypermutation. The algorithms were validated on the NanoString nCounter™ platform in independent cohorts of colorectal (n = 52), endometrial (n = 11), and neuroendocrine (n = 4) tumors pre-characterized using the MMR immunohistochemistry assay. Results In the validation cohorts, the algorithm showed high prediction accuracy of tumor MSI status, with sensitivity of at least 88% attained at thresholds chosen to achieve 100% specificity. Furthermore, MSI status was compared to the Tumor Inflammation Signature (TIS), an analytically validated diagnostic assay which measures a suppressed adaptive immune response in the tumor and enriches for response to immune checkpoint blockade. TIS score was largely independent of MSI status, suggesting that measuring both parameters may identify more patients that would respond to immune checkpoint blockade than either assay alone. Conclusions Development of a gene expression signature of MSI status raises the possibility of a combined diagnostic assay on a single platform which measures both tumor antigenicity and presence of a suppressed adaptive immune response. Such an assay would have significant advantages over multi-platform assays for both ease of use and turnaround time and could lead to a diagnostic test with improved clinical performance.

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.

Background The profound disparity in response to immune checkpoint blockade (ICB) by cutaneous melanoma (CM) and uveal melanoma (UM) patients is not well understood. Therefore, we characterized metastases of CM and UM from the same metastatic site (liver), in order to dissect the potential underlying mechanism in differential response on ICB.Methods Tumor liver samples from CM (n=38) and UM (n=28) patients were analyzed at the genomic (whole exome sequencing), transcriptional (RNA sequencing) and protein (immunohistochemistry and GeoMx Digital Spatial Profiling) level.Results Comparison of CM and UM metastases from the same metastatic site revealed that, although originating from the same melanocyte lineage, CM and UM differed in somatic mutation profile, copy number profile, tumor mutational burden (TMB) and consequently predicted neoantigens. A higher melanin content and higher expression of the melanoma differentiation antigen MelanA was observed in liver metastases of UM patients. No difference in B2M and human leukocyte antigen-DR (HLA-DR) expression was observed. A higher expression of programmed cell death ligand 1 (PD-L1) was found in CM compared with UM liver metastases, although the majority of CM and UM liver metastases lacked PD-L1 expression. There was no difference in the extent of immune infiltration observed between CM and UM metastases, with the exception of a higher expression of CD163 (p

Abstract The Tumor Inflammation Signature (TIS) is an investigational use only (IUO) 18-gene signature that measures a pre-existing but suppressed adaptive immune response within tumors. The TIS has been shown to enrich for patients who respond to the anti-PD1 agent pembrolizumab. To explore this immune phenotype within and across tumor types, we applied the TIS algorithm to over 9000 tumor gene expression profiles downloaded from The Cancer Genome Atlas (TCGA). As expected based on prior evidence, tumors with known clinical sensitivity to anti-programmed cell death protein 1 (PD-1) blockade had higher average TIS scores. Furthermore, TIS scores were more variable within than between tumor types, and within each tumor type a subset of patients with elevated scores was identifiable although with different prevalence associated with each tumor type, the latter consistent with the observed clinical responsiveness to anti PD-1 blockade. Notably, TIS scores only minimally correlated with mutation load in most tumors and ranking tumors by median TIS score showed differing association to clinical sensitivity to PD-1/PD-1 ligand 1 (PD-L1) blockade than ranking of the same tumors by mutation load. The expression patterns of the TIS algorithm genes were conserved across tumor types yet appeared to be minimally prognostic in most cancers, consistent with the TIS score serving as a pan-cancer measurement of the inflamed tumor phenotype. Characterization of the prevalence and variability of TIS will lead to increased understanding of the immune status of untreated tumors and may lead to improved indication selection for testing immunotherapy agents.

Summary: Tumor-derived lactic acid inhibits T and natural killer (NK) cell function and, thereby, tumor immunosurveillance. Here, we report that melanoma patients with high expression of glycolysis-related genes show a worse progression free survival upon anti-PD1 treatment. The non-steroidal anti-inflammatory drug (NSAID) diclofenac lowers lactate secretion of tumor cells and improves anti-PD1-induced T cell killing in vitro. Surprisingly, diclofenac, but not other NSAIDs, turns out to be a potent inhibitor of the lactate transporters monocarboxylate transporter 1 and 4 and diminishes lactate efflux. Notably, T cell activation, viability, and effector functions are preserved under diclofenac treatment and in a low glucose environment in vitro. Diclofenac, but not aspirin, delays tumor growth and improves the efficacy of checkpoint therapy in vivo. Moreover, genetic suppression of glycolysis in tumor cells strongly improves checkpoint therapy. These findings support the rationale for targeting glycolysis in patients with high glycolytic tumors together with checkpoint inhibitors in clinical trials. : Renner et al. demonstrate a negative correlation between glycolytic activity in tumors and response to checkpoint therapy. Genetic blockade of glycolysis or pharmacological inhibition of the main lactate transporters MCT1 and MCT4 preserves T cell function, reverses tumor acidification, and augments response to checkpoint therapy. Keywords: checkpoint, glycolysis, monocarboxylate transporters, lactate, acidification, diclofenac, T cells, NK cells, interferon gamma, tumor

Osteosarcoma (OS) is the most common bone tumor in pediatric and adolescent/young adult patients yet little is known about the microenvironment that supports this aggressive disease. We have used targeted gene expression profiling and immunohistochemistry to characterize the microenvironment of metastatic and non-metastatic OS specimens from pediatric patients exhibiting poor histologic response to chemotherapy. Our results indicate that metastatic specimens exhibit lymphocyte exclusion as T cells are confined to the periphery of the pulmonary lesions. Furthermore, our data provides evidence of vascular dysfunction in metastatic OS indicated by increased expression of VEGFA, an increased ANGPT2:ANGPT1 gene expression ratio, and decreased expression of SELE, the gene encoding the adhesion molecule E-selectin. Moreover, correlation analyses show an inverse relationship between lymphocyte abundance and markers of vascular dysfunction exclusively in the metastatic specimens. Together, our data shows that the non-metastatic OS specimens demonstrate increased expression of various immunotherapeutic targets in comparison metastatic specimens and identifies vascular dysfunction and lymphocyte exclusion as important processes for therapeutic intervention in metastatic disease.

Natural killer (NK) cells are innate cytotoxic and immunoregulatory lymphocytes that have a central role in anti-tumor immunity and play a critical role in mediating cellular immunity in advanced cancer immunotherapies, such as dendritic cell (DC) vaccines. Our group recently tested a novel recombinant adenovirus-transduced autologous DC-based vaccine that simultaneously induces T cell responses against three melanoma-associated antigens for advanced melanoma patients. Here, we examine the impact of this vaccine as well as the subsequent systemic delivery of high-dose interferon-α2b (HDI) on the circulatory NK cell profile in melanoma patients. At baseline, patient NK cells, particularly those isolated from high-risk patients with no measurable disease, showed altered distribution of CD56dim CD16+ and CD56dim CD16− NK cell subsets, as well as elevated serum levels of immune suppressive MICA, TN5E/CD73 and tactile/CD96, and perforin. Surprisingly, patient NK cells displayed a higher level of activation than those from healthy donors as measured by elevated CD69, NKp44 and CCR7 levels, and enhanced K562 killing. Elevated cytolytic ability strongly correlated with increased representation of CD56dim CD16+ NK cells and amplified CD69 expression on CD56dim CD16+ NK cells. While intradermal DC immunizations did not significantly impact circulatory NK cell activation and distribution profiles, subsequent HDI injections enhanced CD56bright CD16− NK cell numbers when compared to patients that did not receive HDI. Phenotypic analysis of tumor-infiltrating NK cells showed that CD56dim CD16− NK cells are the dominant subset in melanoma tumors. NanoString transcriptomic analysis of melanomas resected at baseline indicated that there was a trend of increased CD56dim NK cell gene signature expression in patients with better clinical response. These data indicate that melanoma patient blood NK cells display elevated activation levels, that intra-dermal DC immunizations did not effectively promote systemic NK cell responses, that systemic HDI administration can modulate NK cell subset distributions and suggest that CD56dim CD16− NK cells are a unique non-cytolytic subset in melanoma patients that may associate with better patient outcome.