Serum lactate dehydrogenase as an early marker for outcome in patients treated with anti-PD-1 therapy in metastatic melanoma

Biofluorescence imaging-guided spatial metabolic tracing: In vivo tracking of metabolic activity in circulating tumor cell-mediated multi-organ metastases

Circulating tumor cells (CTC) are considered metastatic precursors that are shed from the primary or metastatic deposits and navigate the bloodstream before undergoing extravasation to establish distant metastases. Metabolic reprogramming appears to be a hallmark of metastatic progression, yet current methods for evaluating metabolic heterogeneity within organ-specific metastases in vivo are limited. To overcome this challenge, we present Biofluorescence Imaging-Guided Spatial Metabolic Tracing (BIGSMT), a novel approach integrating in vivo biofluorescence imaging, stable isotope tracing, stain-free laser capture microdissection, and liquid chromatography-mass spectrometry. This innovative technology obviates the need for staining or intricate sample preparation, mitigating metabolite loss, and substantially enhances detection sensitivity and accuracy through chemical derivatization of polar metabolites in central carbon pathways. Application of BIGSMT to a preclinical CTC-mediated metastasis mouse model revealed significant heterogeneity in the in vivo carbon flux from glucose into glycolysis and the tricarboxylic acid (TCA) cycle across distinct metastatic sites. Our analysis indicates that carbon predominantly enters the TCA cycle through the enzymatic reaction catalyzed by pyruvate dehydrogenase. Thus, our spatially resolved BIGSMT technology provides fresh insights into the metabolic heterogeneity and evolution during melanoma CTC-mediated metastatic progression and points to novel therapeutic opportunities.

Genomic and molecular alterations associated with primary resistance to immune checkpoint inhibitors

The clinical response to immune checkpoint inhibitors may vary by tumor type and many tumors present with either primary or acquired resistance to immunotherapy. Improved understanding of the molecular and immunologic mechanisms underlying immunotherapy resistance is essential for developing biomarkers and for guiding the optimum approach to selecting treatment regimens and sequencing. This is increasingly important for tumors with primary resistance as effective biomarkers in this setting can guide clinicians about appropriate treatment regimen selection in the first-line setting. Multiple potential biological mechanisms of primary resistance have been proposed but most are yet to be validated in prospective clinical cohorts. Individual biomarkers have poor specificity and sensitivity, and the development of validated and integrated predictive models may guide which patient will benefit from monotherapy versus combination therapy. In this review, we discuss the emerging data identifying the molecular mechanisms of primary resistance to immunotherapy and explore potential therapeutic strategies to target these.

Advances in predictive biomarkers associated with immunotherapy in extensive-stage small cell lung cancer

Small cell lung cancer (SCLC) is a highly malignant and poor-prognosis cancer, with most cases diagnosed at the extensive stage (ES). Amidst a landscape marked by limited progress in treatment modalities for ES-SCLC over the past few decades, the integration of immune checkpoint inhibitors (ICIs) with platinum-based chemotherapy has provided a milestone approach for improving prognosis, emerging as the new standard for initial therapy in ES-SCLC. However, only a minority of SCLC patients can benefit from ICIs, which frequently come with varying degrees of immune-related adverse events (irAEs). Therefore, it is crucial to investigate predictive biomarkers to screen potential beneficiaries of ICIs, mitigate the risk of side effects, and improve treatment precision. This review summarized potential biomarkers for predicting ICI response in ES-SCLC, with a primary focus on markers sourced from tumor tissue or peripheral blood samples. The former mainly included PD-L1 expression, tumor mutational burden (TMB), along with cellular or molecular components related to the tumor microenvironment (TME) and antigen presentation machinery (APM), molecular subtypes of SCLC, and inflammatory gene expression profiles. Circulating biomarkers predominantly comprised circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), cytokines, plasma autoantibodies, inflammation-related parameters, and blood TMB. We synthesized and analyzed the research progress of these potential markers. Notably, investigations into PD-L1 expression and TMB have been the most extensive, exhibiting preliminary predictive efficacy in salvage immunotherapy; however, consistent conclusions have yet to be reached across studies. Additionally, novel predictive markers developed based on TME composition, APM, transcriptomic and genomic features provide promising tools for precision immunotherapy. Circulating biomarkers offer the advantages of convenience, non-invasiveness, and a comprehensive reflection of tumor molecular characteristics. They may serve as alternative options for predicting immunotherapy efficacy in SCLC. However, there is a scarcity of studies, and the significant heterogeneity in research findings warrants attention.

Pharmacologic LDH inhibition redirects intratumoral glucose uptake and improves antitumor immunity in solid tumor models

Tumor reliance on glycolysis is a hallmark of cancer. Immunotherapy is more effective in controlling glycolysis-low tumors lacking lactate dehydrogenase (LDH) due to reduced tumor lactate efflux and enhanced glucose availability within the tumor microenvironment (TME). LDH inhibitors (LDHi) reduce glucose uptake and tumor growth in preclinical models, but their impact on tumor-infiltrating T cells is not fully elucidated. Tumor cells have higher basal LDH expression and glycolysis levels compared with infiltrating T cells, creating a therapeutic opportunity for tumor-specific targeting of glycolysis. We demonstrate that LDHi treatment (a) decreases tumor cell glucose uptake, expression of the glucose transporter GLUT1, and tumor cell proliferation while (b) increasing glucose uptake, GLUT1 expression, and proliferation of tumor-infiltrating T cells. Accordingly, increasing glucose availability in the microenvironment via LDH inhibition leads to improved tumor-killing T cell function and impaired Treg immunosuppressive activity in vitro. Moreover, combining LDH inhibition with immune checkpoint blockade therapy effectively controls murine melanoma and colon cancer progression by promoting effector T cell infiltration and activation while destabilizing Tregs. Our results establish LDH inhibition as an effective strategy for rebalancing glucose availability for T cells within the TME, which can enhance T cell function and antitumor immunity.

Nomogram for predicting survival after first-line anti-PD-1-based immunotherapy in unresectable stage IV melanoma: a multicenter international study

BACKGROUND

The introduction of anti-programmed cell death protein 1 (PD-1) immunotherapy has revolutionized the treatment landscape for melanoma, enhancing both response rates and survival outcomes in patients with advanced stages of the disease. Despite these remarkable advances, a noteworthy subset of patients (40%-60%) does not derive advantage from this therapeutic approach. This study aims to identify key predictive factors and create a user-friendly predictive nomogram for stage IV melanoma patients receiving first-line anti-PD-1-based immunotherapy, improving treatment decisions.

MATERIALS AND METHODS

In this retrospective study, we included patients with unresectable stage IV melanoma who received first-line treatment with either anti-PD-1 monotherapy or anti-PD-1 plus anti-cytotoxic T-lymphocyte associated protein 4 between 2014 and 2018. We documented clinicopathological features and blood markers upon therapy initiation. By employing the random survival forest model and backward variable selection of the Cox model, we identified variables associated with progression-free survival (PFS) after the first-line anti-PD-1-based treatment. We developed and validated a predictive nomogram for PFS utilizing the identified variables. We assessed calibration and discrimination performance metrics as part of the evaluation process.

RESULTS

The study involved 719 patients, divided into a training cohort of 405 (56%) patients and a validation cohort of 314 (44%) patients. We combined findings from the random survival forest and the Cox model to create a nomogram that incorporates the following factors: lactate dehydrogenase (LDH), S100, melanoma subtype, neutrophil-to-lymphocyte ratio (NLR), body mass index, type of immune checkpoint inhibitor, and presence of liver or brain metastasis. The resultant model had a C-index of 0.67 in the training cohort and 0.66 in the validation cohort. Performance remained in different patient subgroups. Calibration analysis revealed a favorable correlation between predicted and actual PFS rates.

CONCLUSIONS

We developed and validated a predictive nomogram for long-term PFS in patients with unresectable stage IV melanoma undergoing first-line anti-PD-1-based immunotherapy.

Identification of peripheral blood test parameters predicting the response to palbociclib and endocrine therapy for metastatic breast cancer: a retrospective study in a single institution

PURPOSE

Cyclin-dependent kinase 4/6 inhibitors have been used in endocrine therapy for patients with estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer. Although randomized trials have shown that combined therapies prolong progression-free survival (PFS) in comparison to endocrine monotherapy, the predictors of efficacy are unknown. This study aimed to identify the blood test parameters to predict the effects of palbociclib and endocrine therapy.

METHODS

Seventy-nine patients treated with palbociclib and endocrine therapy between December 2017 and June 2022 were reviewed. We assessed PFS in patients according to factors evaluated based on patient characteristics and peripheral blood tests.

RESULTS

Patients in the C-reactive protein (CRP)-high, lactate dehydrogenase (LDH)-high, and albumin (Alb)-low groups had significantly shorter PFS than those in the normal group. A multivariate analysis revealed that high LDH and low Alb levels were independent factors that affected PFS. The Alb-low group had an inferior disease control rate. Patients in the CRP-high, LDH-high, and Alb-low groups who received these therapies as first- or second-line treatments showed poor PFS.

CONCLUSIONS

Several predictors of the efficacy of palbociclib and endocrine therapy were identified in the peripheral blood test parameters of patients with ER-positive and HER2-negative subtypes of metastatic breast cancer.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Gut Mycobiota Dysbiosis Is Associated with Melanoma and Response to Anti-PD-1 Therapy

Recent research indicates that gut microbiota may be vital in the advancement of melanoma. In this study, we found that melanoma patients exhibited a distinct gut mycobiota structure compared with healthy participants. Candida albicans, Candida dubliniensis, and Neurospora crassa were more abundant in samples from patients with melanoma, whereas Saccharomyces cerevisiae and Debaryomyces hansenii were less abundant. During anti-PD-1 treatment, the relative amount of Malassezia restricta and C. albicans increased. A higher level of Saccharomyces paradoxus was associated with a positive response to anti-PD-1 treatment, whereas a higher level of Tetrapisispora blattae was associated with a lack of clinical benefits. High levels of M. restricta and C. albicans, elevated serum lactate dehydrogenase, and being overweight were linked to increased risk of melanoma progression and poorer response to anti-PD-1 treatment. Thus, this study has revealed melanoma-associated mycobiome dysbiosis, characterized by altered fungal composition and fungi species associated with a higher risk of melanoma progression, identifying a role for the gut mycobiome in melanoma progression.

Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning

Pretreatment serum lactate dehydrogenase (LDH) levels have been associated with poor prognosis in several types of cancer, including metastatic colorectal cancer (mCRC). However, very few models link survival to longitudinal LDH measured repeatedly over time during treatment. We investigated the prognostic value of on-treatment LDH dynamics in mCRC. Using data from two large phase III studies (2L and 3L+ mCRC settings, n = 824 and 210, respectively), we found that integrating longitudinal LDH data with baseline risk factors significantly improved survival prediction. Current LDH values performed best, enhancing discrimination ability (area under the receiver operating characteristic curve) by 4.5~15.4% and prediction accuracy (Brier score) by 3.9~15.0% compared with baseline variables. Combining all longitudinal LDH markers further improved predictive performance. After controlling for baseline covariates and other longitudinal LDH indicators, current LDH levels remained a significant risk factor in mCRC, increasing mortality risk by over 90% (P < 0.001) in 2L patients and 60-70% (P < 0.01) in 3L+ patients per unit increment in current log (LDH). Machine-learning techniques, like functional principal component analysis (FPCA), extracted informative features from longitudinal LDH data, capturing over 99% of variability and allowing prediction of survival. Unsupervised clustering based on the extracted FPCA features stratified patients into three groups with distinct LDH dynamics and survival outcomes. Hence, our approaches offer a valuable and cost-effective way for risk stratification and improves survival prediction in mCRC using LDH trajectories.

The relationship between lactate dehydrogenase to albumin ratio and all-cause mortality during ICU stays in patients with sepsis: A retrospective cohort study with propensity score matching

Background

Sepsis is a prevalent and severe medical condition which is frequently observed in the intensive care unit (ICU). Although numerous biomarkers have been identified to predict the prognosis of sepsis, the lactate dehydrogenase to albumin ratio (LDH/ALB ratio) has not been extensively investigated. The principal objective of this study is to assess the relationship between LDH/ALB ratio and all-cause mortality in patients with sepsis.

Methods

This study included all adult critically ill patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.0) database. Propensity score matching (PSM) analysis was conducted to mitigate bias, and Kaplan-Meier curves were performed to evaluate the cumulative survival across different groups. The association between the LDH/ALB ratio and mortality was examined through restricted cubic spline (RCS) analysis and Cox regression analysis. The robustness of the findings was confirmed through subgroup analyses. Additionally, the prognostic capability of the LDH/ALB ratio was further evaluated using receiver operating characteristic (ROC) curve analysis.

Results

There were 6059 adult patients with sepsis enrolled in the final analysis. RCS revealed a non-linear relationship between the LDH/ALB ratio and an increased risk of ICU all-cause mortality (χ2 = 46.900, P < 0.001). Following PSM analysis, 1553 matched pairs were obtained. As comparison to the low LDH/ALB ratio group, the mortality rate in the high LDH/ALB ratio group was significantly higher (P < 0.001). Kaplan-Meier curves, both before and after PSM, revealed that the ICU cumulative survival rate for patients with sepsis was significantly lower in the high LDH/ALB ratio group compared to the low LDH/ALB ratio group (χ2 = 93.360, P < 0.001; χ2 = 14.400, P < 0.001). Even after adjusting for a range of potential confounders, multivariate Cox regression analysis indicated that an elevated LDH/ALB ratio was a significant predictor of all-cause mortality in these patients. ROC curve analysis demonstrated that the LDH/ALB ratio had an area under the ROC curve (AUC) of 0.688 for predicting ICU mortality, with a sensitivity of 69.2% and a specificity of 58.6%.

Conclusions

An elevated LDH/ALB ratio (≥10.57) was associated with all-cause mortality in critically ill patients with sepsis, and it might serve as a prognostic marker. Clinicians should pay closer attention to sepsis patients presenting with an LDH/ALB ratio of 10.57 or higher.

Pre-treatment 18F-FDG-PET/CT parameters as biomarkers for progression free survival, best overall response and overall survival in metastatic melanoma patients undergoing first-line immunotherapy

BACKGROUND

Checkpoint inhibitors have drastically improved the therapy of patients with advanced melanoma. 18F-FDG-PET/CT parameters might act as biomarkers for response and survival and thus can identify patients that do not benefit from immunotherapy. However, little literature exists on the association of baseline 18F-FDG-PET/CT parameters with progression free survival (PFS), best overall response (BOR), and overall survival (OS).

MATERIALS AND METHODS

Using a whole tumor volume segmentation approach, we investigated in a retrospective registry study (n = 50) whether pre-treatment 18F-FDG-PET/CT parameters of three subgroups (tumor burden, tumor glucose uptake and non-tumoral hematopoietic tissue metabolism), can act as biomarkers for the primary endpoints PFS and BOR as well as for the secondary endpoint OS.

RESULTS

Compared to the sole use of clinical parameters, baseline 18F-FDG-PET/CT parameters did not significantly improve a Cox proportional-hazard model for PFS (C-index/AIC: 0.70/225.17 and 0.68/223.54, respectively; p = 0.14). A binomial logistic regression analysis for BOR was not statistically significant (χ2(15) = 16.44, p = 0.35), with a low amount of explained variance (Nagelkerke's R2 = 0.38). Mean FDG uptake of the spleen contributed significantly to a Cox proportional-hazard model for OS (HR 3.55, p = 0.04).

CONCLUSIONS

The present study could not confirm the capability of the pre-treatment 18F-FDG-PET/CT parameters tumor burden, tumor glucose uptake and non-tumoral hematopoietic tissue metabolism to act as biomarkers for PFS and BOR in metastatic melanoma patients receiving first-line immunotherapy. The documented potential of 18F-FDG uptake by immune-mediating tissues such as the spleen to act as a biomarker for OS has been reproduced.

Sequential immunotherapy and targeted therapy for metastatic BRAF V600 mutated melanoma: 4-year survival and biomarkers evaluation from the phase II SECOMBIT trial

No prospective data were available prior to 2021 to inform selection between combination BRAF and MEK inhibition versus dual blockade of programmed cell death protein-1 (PD-1) and cytotoxic T lymphocyte antigen-4 (CTLA-4) as first-line treatment options for BRAFV600-mutant melanoma. SECOMBIT (NCT02631447) was a randomized, three-arm, noncomparative phase II trial in which patients were randomized to one of two sequences with immunotherapy or targeted therapy first, with a third arm in which an 8-week induction course of targeted therapy followed by a planned switch to immunotherapy was the first treatment. BRAF/MEK inhibitors were encorafenib plus binimetinib and checkpoint inhibitors ipilimumab plus nivolumab. Primary outcome of overall survival was previously reported, demonstrating improved survival with immunotherapy administered until progression and followed by BRAF/MEK inhibition. Here we report 4-year survival outcomes, confirming long-term benefit with first-line immunotherapy. We also describe preliminary results of predefined biomarkers analyses that identify a trend toward improved 4-year overall survival and total progression-free survival in patients with loss-of-function mutations affecting JAK or low baseline levels of serum interferon gamma (IFNy). These long-term survival outcomes confirm immunotherapy as the preferred first-line treatment approach for most patients with BRAFV600-mutant metastatic melanoma, and the biomarker analyses are hypothesis-generating for future investigations of predictors of durable benefit with dual checkpoint blockade and targeted therapy.

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

Metabolic predictors of response to immune checkpoint blockade therapy

Metabolism of immune cells in the tumor microenvironment (TME) plays a critical role in cancer patient response to immune checkpoint inhibitors (ICI). Yet, a metabolic characterization of immune cells in the TME of patients treated with ICI is lacking. To bridge this gap we performed a semi-supervised analysis of ∼1700 metabolic genes using single-cell RNA-seq data of > 1 million immune cells from ∼230 samples of cancer patients treated with ICI. When clustering cells based on their metabolic gene expression, we found that similar immunological cellular states are found in different metabolic states. Most importantly, we found metabolic states that are significantly associated with patient response. We then built a metabolic predictor based on a dozen gene signature, which significantly differentiates between responding and non-responding patients across different cancer types (AUC = 0.8-0.92). Taken together, our results demonstrate the power of metabolism in predicting patient response to ICI.

Innate lymphoid cells and tumor-derived lactic acid: novel contenders in an enduring game

Aerobic glycolysis, also known as the Warburg effect, has for a prolonged period of time been perceived as a defining feature of tumor metabolism. The redirection of glucose utilization towards increased production of lactate by cancer cells enables their rapid proliferation, unceasing growth, and longevity. At the same time, it serves as a significant contributor to acidification of the tumor microenvironment, which, in turn, imposes substantial constraints on infiltrating immune cells. Here, we delve into the influence of tumor-derived lactic acid on innate lymphoid cells (ILCs) and discuss potential therapeutic approaches. Given the abundance of ILCs in barrier tissues such as the skin, we provide insights aimed at translating this knowledge into therapies that may specifically target skin cancer.

Development and Validation of a Prognostic Risk Model for Patients with Advanced Melanoma Treated with Immune Checkpoint Inhibitors

BACKGROUND

Risk stratification tools for patients with advanced melanoma (AM) treated with immune checkpoint inhibitors (ICI) are lacking. We identified a new prognostic model associated with overall survival (OS).

PATIENTS AND METHODS

A total of 318 treatment naïve patients with AM receiving ICI were collected from a multi-centre retrospective cohort study. LASSO Cox regression identified independent prognostic factors associated with OS. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel's C-index was calculated and internally validated to outline the model's discriminatory performance. External validation was carried out in 142 advanced melanoma patients receiving ICI in later lines.

RESULTS

High white blood cell count (WBC), high lactate dehydrogenase (LDH), low albumin, Eastern Cooperative Oncology Group (ECOG) performance status ≥1, and the presence of liver metastases were included in the model. Patients were parsed into 3 risk groups: favorable (0-1 factors) OS of 52.9 months, intermediate (2-3 factors) OS 13.0 months, and poor (≥4 factors) OS 2.7 months. The C-index of the model from the discovery cohort was 0.69. External validation in later-lines (N = 142) of therapy demonstrated a c-index of 0.65.

CONCLUSIONS

Liver metastases, low albumin, high LDH, high WBC, and ECOG≥1 can be combined into a prognostic model for AM patients treated with ICI.

Prognostic value of the Lung Immune Prognostic Index for HER-2-negative metastatic gastric cancer

Background: The aim of this study was to explore whether the Lung Immune Prognostic Index (LIPI) is associated with clinical outcomes in patients with metastatic gastric cancer (MGC) treated with anti-PD-1 and chemotherapy. Methods: Patients with MGC treated with an anti-PD-1 therapy or chemotherapy were enrolled. This study was composed of two cohorts including 266 patients in the anti-PD-1-treated group and 139 patients in the chemotherapy-treated group. Results: Patients treated with anti-PD-1 therapy that also showed a good LIPI showed a longer median progression-free survival and median overall survival in patients with an intermediate or poor LIPI. These outcomes were not observed in the chemotherapy cohort. Conclusion: Good LIPI correlated with better outcomes for patients with MGC in the anti-PD-1-treated group but not in the chemotherapy-treated group.

Association of the pretreatment lung immune prognostic index with immune checkpoint inhibitor outcomes in patients with advanced hepatocellular carcinoma

OBJECTIVE

To evaluate whether the pretreatment Lung Immune Prognostic Index (LIPI) is associated with outcomes in advanced hepatocellular carcinoma (HCC) patients under ICI.

METHODS

A two-center retrospective study of patients with HCC treated with immune checkpoint inhibitors (ICIs) between January 2018 and January 2021 was performed. Based on pretreatment derived neutrophils/ (leukocytes minus neutrophils) ratio (dNLR) greater than 3 and a lactate dehydrogenase (LDH) level greater than the normal value, patients were stratified into three groups (good LIPI:0 risk factor, intermediate LIPI: 1 risk factor, and poor LIPI: 2 risk factors). The primary endpoints were overall survival (OS) and progression-free survival (PFS). The second endpoints were disease control rate (DCR) and objective response rate (ORR).

RESULTS

In the pooled cohort (n = 224), 80 (35.7%) had a good LIPI (zero factor), 91 (40.6%) had intermediate LIPI (one factor), and 53 (23.7%) had poor LIPI (two factors). The median follow-up was 25.1 months. Median OS was 16.8 months, 12.5 months, and 9.5 months for the good, intermediate, and poor LIPI groups, respectively (P < 0.0001). Median PFS was 11.8 months, 7.8 months, and 4.0 months for the good, intermediate, and poor LIPI groups, respectively (P < 0.0001). Multivariate analysis indicated that the intermediate LIPI and poor LIPI both were independently associated with OS, PFS, and ORR, DCR (P < 0.05), as risk factors.

CONCLUSION

Pretreatment LIPI was correlated with worse outcomes for ICIs suggesting that LIPI could be promising biomarker for advanced HCC patients under ICIs.

Ipilimumab plus nivolumab in patients with symptomatic melanoma brain metastasis requiring corticosteroids

STUDY AIM

To investigate the efficacy of PD-1-directed antibody-based therapy in patients with symptomatic melanoma brain metastases (MBM) and concurrent treatment with corticosteroids.

METHODS

This retrospective cohort study included patients with cutaneous melanoma with symptomatic MBM and concurrent treatment with corticosteroids who received PD-1-directed antibody-based treatment at the Royal Marsden Hospital London between 2016 and 2021. The primary outcome was overall survival (OS), secondary outcomes were intracranial response rate (ORR) and duration of response (DOR). We used the Kaplan-Meier method to describe survival.

RESULTS

Between 2016 and 2021, 256 patients presented with metastatic melanoma, of whom 29 were eligible with symptomatic MBM requiring corticosteroids and receiving ipilimumab plus nivolumab. Median age was 54 (interquartile range 44, 66). Median OS was 5.45months (95% confidence interval (CI) 2.89, 29.40), with 21% of patients (95% CI 9%, 47%) alive after 3years. ORR was 28% (8/29) and DOR was 7.85months (95% CI 7.85, not estimably [NE]). Responding patients had a median OS of 56.4months (95% CI 46.03, NE). Elevated lactate dehydrogenase and Eastern Cooperative Oncology Group PS> 2 were associated with poorer outcomes (median OS 29.4 versus 3.12months and 6.44 versus 5.13months), no such association was observed for corticosteroid dose, number of lesions, or line of treatment.

CONCLUSION

Patients with symptomatic MBM derive only modest benefit from combination immunotherapy treatment. Nevertheless, those with disease response have the potential to derive long-term benefit, justifying ipilimumab plus nivolumab in this group in the absence of other more effective treatment options.

A Survival Tree of Advanced Melanoma Patients with Brain Metastases Treated with Immune Checkpoint Inhibitors

The efficacy of immune checkpoint inhibitors (ICIs) in patients with advanced melanoma that develop brain metastases (BM) remains unpredictable. In this study, we aimed to identify prognostic factors in patients with melanoma BM who are treated with ICIs. Data from advanced melanoma patients with BM treated with ICIs in any line between 2013 and 2020 were obtained from the Dutch Melanoma Treatment Registry. Patients were included from the time of the treatment of BM with ICIs. Survival tree analysis was performed with clinicopathological parameters as potential classifiers and overall survival (OS) as the response variable. In total, 1278 patients were included. Most patients were treated with ipilimumab-nivolumab combination therapy (45%). The survival tree analysis resulted in 31 subgroups. The median OS ranged from 2.7 months to 35.7 months. The strongest clinical parameter associated with survival in advanced melanoma patients with BM was the serum lactate dehydrogenase (LDH) level. Patients with elevated LDH levels and symptomatic BM had the worst prognosis. The clinicopathological classifiers identified in this study can contribute to optimizing clinical studies and can aid doctors in giving an indication of the patients' survival based on their baseline and disease characteristics.

Machine Learning Improves the Prediction of Responses to Immune Checkpoint Inhibitors in Metastatic Melanoma

Pretreatment LDH is a standard prognostic biomarker for advanced melanoma and is associated with response to ICI. We assessed the role of machine learning-based radiomics in predicting responses to ICI and in complementing LDH for prognostication of metastatic melanoma. From 2008-2022, 79 patients with 168 metastatic hepatic lesions were identified. All patients had arterial phase CT images 1-month prior to initiation of ICI. Response to ICI was assessed on follow-up CT at 3 months using RECIST criteria. A machine learning algorithm was developed using radiomics. Maximum relevance minimum redundancy (mRMR) was used to select features. ROC analysis and logistic regression analyses evaluated performance. Shapley additive explanations were used to identify the variables that are the most important in predicting a response. mRMR selection revealed 15 features that are associated with a response to ICI. The machine learning model combining both radiomics features and pretreatment LDH resulted in better performance for response prediction compared to models that included radiomics or LDH alone (AUC of 0.89 (95% CI: [0.76-0.99]) vs. 0.81 (95% CI: [0.65-0.94]) and 0.81 (95% CI: [0.72-0.91]), respectively). Using SHAP analysis, LDH and two GLSZM were the most predictive of the outcome. Pre-treatment CT radiomic features performed equally well to serum LDH in predicting treatment response.

Association between lung immune prognostic index and survival of patients with metastatic urothelial carcinoma treated with pembrolizumab

INTRODUCTION AND OBJECTIVE

Lung immune prognostic index score (LIPI), calculated using the derived neutrophil-lymphocyte ratio and lactate dehydrogenase level, is reported for use in numerous malignancies, while its role on metastatic urothelial carcinoma (mUC) treated with pembrolizumab remains limited. We aimed to investigate association between LIPI and outcomes in this setting.

METHODS

We retrospectively evaluated 90 patients with mUC treated with pembrolizumab at four institutions. The associations between three LIPI groups and progression-free survival (PFS), overall survival (OS), objective response rates (ORRs) or disease control rates (DCRs) were assessed.

RESULTS

Based on the LIPI, good, intermediate, and poor groups were observed in 41 (45.6%), 33 (36.7%), and 16 (17.8%) patients, respectively. The PFS and OS were significantly correlated with the LIPI (median PFS: 21.2 vs. 7.0 vs. 4.0 months, p = 0.001; OS: 44.3 vs. 15.0 vs. 4.2 months, p < 0.001 in the LIPI good vs. intermediate vs. poor groups). Multivariable analysis further revealed that LIPI good (vs. intermediate or poor, hazard ratio: 0.44, p = 0.004) and performance status = 0 (p = 0.015) were independent predictors of a longer PFS. In addition, LIPI good (hazard ratio: 0.29, p < 0.001) were shown to be associated with a longer OS together with performance status = 0 (p < 0.001). The ORRs tended to be different among patients with Good LIPI compared with Poor, and DCRs were significantly different among the three groups.

CONCLUSIONS

LIPI, a simple and convenient score, could be a significant prognostic biomarker of OS, PFS, and DCRs for mUC treated with pembrolizumab.

Long-term clinical evidence of comparable efficacy and toxicity of nivolumab and pembrolizumab in advanced melanoma treatment

Pembrolizumab and nivolumab (anty-PD-1 antibody) are commonly used for the treatment of melanoma patients. However, their efficacy and safety have never been directly compared, leaving little guidance for clinicians to select the best therapy. The study included patients with inoperable or metastatic melanoma treated in first line with anti-PD-1 immunotherapy (nivolumab or pembrolizumab). In total 1037 patients were enrolled in the study, 455 (44%) patients were treated with pembrolizumab and 582 (56%) with nivolumab. The estimated median overall survival (OS) in the pembrolizumab and nivolumab groups was 17.4 and 20.0 months [P = 0.2323; hazard ratio (HR), 1.1; 95% confidence interval (CI), 0.94-1.28], respectively, whereas the median progression-free survival (PFS) was 5.6 and 7.5 months (P = 0.0941; HR, 1.13; 95% CI, 0.98-1.29), respectively. The estimated 2- and 3-year OS in the pembrolizumab and nivolumab groups were 42/34% and 47/37%, respectively, and the PFS was 25/21% and 29/23%, respectively. There were 391 (49%) immune-related adverse events (irAEs) of any grade during treatment, including 133 (42%) related to pembrolizumab treatment and 258 (53%) to nivolumab treatment. A total of 72 (9.6%) irAEs were in G3 or G4, including during pembrolizumab 29 (9%) and nivolumab 48 (11%). There were no differences in OS, PFS and overall response rates between nivolumab and pembrolizumab therapy in previously untreated patients with advanced/metastatic melanoma. There were no differences in the frequency of G1/G2 or G3/G4 irAEs. The choice of treatment should be based on the preferences of the patient and the clinician.

Myeloid-Derived Suppressor Cells (MDSC) in Melanoma Patients Treated with Anti-PD-1 Immunotherapy

Myeloid-derived suppressor cells (MDSC) are a subset of immature myeloid cells with suppressive activity well described in the context of cancer. They inhibit anti-tumour immunity, promote metastasis formation and can lead to immune therapy resistance. In a retrospective study, blood probes of 46 advanced melanoma patients were analysed before the first administration of anti-PD-1 immunotherapy and in the third month of treatment for MDSC, immature monocytic (ImMC), monocytic MDSC (MoMDSC) and granulocytic MDSC (GrMDSC) by multi-channel flow cytometry. Cell frequencies were correlated with response to immunotherapy, progression-free survival (PFS) and lactate dehydrogenase (LDH) serum level. Responders to anti-PD-1 therapy had higher MoMDSC levels (4.1 ± 1.2%) compared to non-responders (3.0 ± 1.2%) (p = 0.0333) before the first administration of anti-PD-1. No significant changes in MDSCs frequencies were observed in the groups of patients before and in the third month of therapy. The cut-off values of MDSCs, MoMDSCs, GrMDSCs and ImMCs for favourable 2- and 3-year PFS were established. Elevated LDH level is a negative prognostic factor of response to the treatment and is related to an elevated ratio of GrMDSCs and ImMCs level compared to patients' LDH level below the cut-off. Our data may provide a new perspective for more careful consideration of MDSCs, and specially MoMDSCs, as a tool for monitoring the immune status of melanoma patients. Changes in MDSC levels may have a potential prognostic value, however a correlation with other parameters must be established.

Prognostic value of pretreatment immune inflammation indices in patients with immune-related tumors

BACKGROUND

Pretreatment high levels of lactate dehydrogenase (LDH), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), modified Glasgow prognostic scores (mGPS), prognostic nutritional index (PNI), and other prognostic biomarkers have been associated with poor overall survival (OS) in immune-related tumor types. Therefore, we explored a simple, inexpensive and effective method for cancer prognosis.

METHODS

Between March 2017 and June 2022, 111 individuals who had immunotherapy were retrospectively examined. Oncologic outcomes of patients with immune-related tumor types, include OS and progression-free survival (PFS), and response rates (RR).

RESULTS

Pretreatment ECOG (Eastern Cooperative Oncology Group) performance quality was independently linked with poor OS ECOG ≥2 (HR 4.80, 95% CI 2.57-8.96, p < .001) and inferior PFS (HR 3.31, 95% CI 2.023-5.445, p < .001). Additionally, a high LDH status prior to therapy was independently linked to an inferior OS (HR 1.004, 95% CI 1.001-1.007, p = .003) and inferior PFS (HR 1.004, 95% CI 1.002-1.006, p < .001). Higher MLR at baseline was a prognostic factor for both shorter PFS (HR = 3.691, 95% CI 1.582-8.610, p = .003) and OS (HR = 2.876, 95% CI 1.127-7.342, p = .027).

CONCLUSIONS

In our cohort, elevated pre-treatment MLR, LDH and ECOG ≥2 were associated with poor OS and PFS. Prospective studies need to determine the utility of them.

Mechanisms of resistance to immune checkpoint inhibitors in melanoma: What we have to overcome?

Marching into the second decade after the approval of ipilimumab, it is clear that immune checkpoint inhibitors (ICIs) have dramatically improved the prognosis of melanoma. Although the current edge is already high, with a 4-year OS% of 77.9% for adjuvant nivolumab and a 6.5-year OS% of 49% for nivolumab/ipilimumab combination in the metastatic setting, a high proportion of patients with advanced melanoma have no benefit from immunotherapy, or experience an early disease relapse/progression in the first few months of treatment, surviving much less. Reasonably, the primary and acquired resistance to ICIs has entered into the focus of clinical research with positive (e.g., nivolumab and relatlimab combination) and negative feedbacks (e.g., nivolumab with pegylated-IL2, pembrolizumab with T-VEC, nivolumab with epacadostat, and combinatorial triplets of BRAF/MEK inhibitors with immunotherapy). Many intrinsic (intracellular or intra-tumoral) but also extrinsic (systematic) events are considered to be involved in the development of this resistance to ICIs: i) melanoma cell immunogenicity (e.g., tumor mutational burden, antigen-processing machinery and immunogenic cell death, neoantigen affinity and heterogeneity, genomic instability, melanoma dedifferentiation and phenotypic plasticity), ii) immune cell trafficking, T-cell priming, and cell death evasion, iii) melanoma neovascularization, cellular TME components(e.g., T_regs, CAFs) and extracellular matrix modulation, iv) metabolic antagonism in the TME(highly glycolytic status, upregulated CD39/CD73/adenosine pathway, iDO-dependent tryptophan catabolism), v) T-cell exhaustion and negative immune checkpoints, and vi) gut microbiota. In the present overview, we discuss how these parameters compromise the efficacy of ICIs, with an emphasis on the lessons learned by the latest melanoma studies; and in parallel, we describe the main ongoing approaches to overcome the resistance to immunotherapy. Summarizing this information will improve the understanding of how these complicated dynamics contribute to immune escape and will help to develop more effective strategies on how anti-tumor immunity can surpass existing barriers of ICI-refractory melanoma.

Identification of prognostic factors and nomogram model for patients with advanced lung cancer receiving immune checkpoint inhibitors

Background and aim

Some patients with lung cancer can benefit from immunotherapy, but the biomarkers that predict immunotherapy response were not well defined. Baseline characteristic of patients may be the most convenient and effective markers. Therefore, our study was designed to explore the association between baseline characteristics of patients with lung cancer and the efficacy of immunotherapy.

Methods

A total of 216 lung cancer patients from Tianjin Medical University Cancer Institute & Hospital who received immunotherapy between 2017 and 2021 were included in the retrospective analysis. All baseline characteristic data were collected and then univariate log-rank analysis and multivariate COX regression analysis were performed. Kaplan-Meier analysis was used to evaluate patients' progression-free survival (PFS). A nomogram based on significant biomarkers was constructed to predict PFS rate of patients receiving immunotherapy. We evaluated the prediction accuracy of nomogram using C-indices and calibration curves.

Results

Univariate analysis of all collected baseline factors showed that age, clinical stage, white blood cell (WBC), lymphocyte (LYM), monocyte (MON), eosinophils (AEC), hemoglobin (HB), lactate dehydrogenase (LDH), albumin (ALB) and treatment line were significantly associated with PFS after immunotherapy. Then these 10 risk factors were included in a multivariate regression analysis, which indicated that age (HR: 1.95, 95% CI [1.01-3.78], P = 0.048), MON (HR: 1.74, 95% CI [1.07-2.81], P = 0.025), LDH (HR: 0.59, 95% CI [0.36-0.95], P = 0.030), and line (HR: 0.57, 95% CI [0.35-0.94], P = 0.026) were significantly associated with PFS in patients with lung cancer receiving immunotherapy. Patients with higher ALB showed a greater trend of benefit compared with patients with lower ALB (HR: 1.58, 95% CI [0.94-2.66], P = 0.084). Patients aged ≥51 years, with high ALB, low LDH, first-line immunotherapy, and high MON had better response rates and clinical benefits. The nomogram based on age, ALB, MON, LDH, line was established to predict the prognosis of patients treated with immune checkpoint inhibitor (ICI). The C-index of training cohort and validation cohort were close, 0.71 and 0.75, respectively. The fitting degree of calibration curve was high, which confirmed the high prediction value of our nomogram.

Conclusion

Age, ALB, MON, LDH, line can be used as reliable predictive biomarkers for PFS, response rate and cancer control in patients with lung cancer receiving immunotherapy. The nomogram based on age, ALB, MON, LDH, line was of great significance for predicting 1-year-PFS, 2-year-PFS and 3-year-PFS in patients with advanced lung cancer treated with immunotherapy.

Targeting T-cell metabolism to boost immune checkpoint inhibitor therapy

Immune checkpoint inhibitors (ICIs) have shown promising therapeutic effects in the treatment of advanced solid cancers, but their overall response rate is still very low for certain tumor subtypes, limiting their clinical scope. Moreover, the high incidence of drug resistance (including primary and acquired) and adverse effects pose significant challenges to the utilization of these therapies in the clinic. ICIs enhance T cell activation and reverse T cell exhaustion, which is a complex and multifactorial process suggesting that the regulatory mechanisms of ICI therapy are highly heterogeneous. Recently, metabolic reprogramming has emerged as a novel means of reversing T-cell exhaustion in the tumor microenvironment; there is increasing evidence that T cell metabolic disruption limits the therapeutic effect of ICIs. This review focuses on the crosstalk between T-cell metabolic reprogramming and ICI therapeutic efficacy, and summarizes recent strategies to improve drug tolerance and enhance anti-tumor effects by targeting T-cell metabolism alongside ICI therapy. The identification of potential targets for altering T-cell metabolism can significantly contribute to the development of methods to predict therapeutic responsiveness in patients receiving ICI therapy, which are currently unknown but would be of great clinical significance.

Current Status and Future Perspectives of Lactate Dehydrogenase Detection and Medical Implications: A Review

The demand for glucose uptake and the accompanying enhanced glycolytic energy metabolism is one of the most important features of cancer cells. Unlike the aerobic metabolic pathway in normal cells, the large amount of pyruvate produced by the dramatic increase of glycolysis in cancer cells needs to be converted to lactate in the cytoplasm, which cannot be done without a large amount of lactate dehydrogenase (LDH). This explains why elevated serum LDH concentrations are usually seen in cancer patient populations. LDH not only correlates with clinical prognostic survival indicators, but also guides subsequent drug therapy. Besides their role in cancers, LDH is also a biomarker for malaria and other diseases. Therefore, it is urgent to develop methods for sensitive and convenient LDH detection. Here, this review systematically summarizes the clinical impact of lactate dehydrogenase detection and principles for LDH detection. The advantages as well as limitations of different detection methods and the future trends for LDH detection were also discussed.

Serum parameters as prognostic biomarkers in a real world cancer patient population treated with anti PD-1/PD-L1 therapy

BACKGROUND

Immune checkpoint inhibitors (ICI) are regarded as a standard of care in multiple malignancies. We hypothesized that serum parameters are of prognostic value in ICI treated patients suffering from solid tumours.

METHODS

Data from 114 patients treated with ICIs for solid malignancies from 2015 to 2019 at the Medical University of Vienna were collected retrospectively. Data included baseline characteristics, cancer type, serum parameters such as lactate dehydrogenase (LDH), C-reactive protein (CRP), albumin (Alb) and lymphocyte counts as well as overall survival (OS) and progression free survival. Additionally, the Gustave Roussy Immune Score (GRIm score) and the Glasgow prognostic score (GPS) were calculated. Cox regression models including time-dependent effects and strata for tumour type were used. Prognostic factors were pre-selected using a relaxed LASSO approach.

RESULTS

The majority of patients were male (64.9%). The most common cancer types were non-small cell lung cancer (30.7%) and renal cell carcinoma (21.9%). Increased LDH and CRP were associated with poor 6-month OS (Hazard ratios (HR)=1.16 and 1.06 per 20% LDH/CRP increase; 95% CI 1.07-1.26 and 95% CI 1.03-1.09, respectively; p < .001). Both GRIm Score and GPS had a significant influence on OS (GRIm: HR = 2.84, 95% CI 1.72-4.69; p < .001 for high vs. low; GPS HR 3.57, 95% CI 1.76-7.25; p < .001 for poor vs. good). The proportion of explained variation (PEV) of our full multivariable model was significantly higher compared to the GRIm and GPS (PEV = 29.5% vs. 14.8% and 14.65%). When grouped into quartiles according to the individual 8-weeks change, both increased LDH and CRP correlated with poor OS (LDH (p=.001) and CRP (p < .001)).

CONCLUSION

The results of this analysis suggest that serum parameters might have prognostic value for the outcome of cancer patients treated with ICI, regardless of the tumour type.Key messagesIn this retrospective analysis, 114 patients with solid tumours were included. The results of this analysis point out that pre-treatment LDH, CRP and albumin levels are strongly prognostic for a poor 6-month OS.In addition to that, a high GRIm-score and poor GPS were associated with a worse OS (GRIm: HR = 2.84, 95% CI 1.72-4.69; p < .001 for high vs. low; GPS HR = 3.57, 95% CI 1.76-7.25; p < .001 for poor vs. good).Pre-treatment serum parameters might have prognostic value for the outcome of cancer patients treated with ICI, regardless of the tumour type.

Fibroblast growth factor receptor family mutations as a predictive biomarker for immune checkpoint inhibitors and its correlation with tumor immune microenvironment in melanoma

BACKGROUND

The emergence of immune checkpoint inhibitors (ICIs) has significantly improved the clinical outcomes of patients with metastatic melanoma. However, survival benefits are only observed in a subset of patients. The fibroblast growth factor receptor (FGFR) family genes are frequently mutated in melanoma, yet their impacts on the efficacy of ICIs remain unclear. Our study aimed to explore the association of FGFR mutations with ICIs efficacy in metastatic melanoma.

METHODS

The Cancer Genome Atlas (TCGA) data (PanCancer Atlas, skin cutaneous melanoma (SKCM), n = 448) in cBioPortal were collected as a TCGA cohort to investigate the association between FGFR mutations and prognosis of melanoma patients. To explore the impact of FGFR mutations on the efficacy of ICIs in melanoma, clinical and tumor whole-exome sequencing (WES) data of four ICI-treated studies from cBioPortal were consolidated as an ICIs-treated cohort. Moreover, the relationship between FGFR mutations and immunogenicity (tumor mutation burden (TMB), neo-antigen load (NAL), mismatch repair (MMR)-related genes and DNA damage repair (DDR)-related genes) of melanoma was evaluated utilizing data from the ICIs-treated cohort. The influence of FGFR mutations on the tumor immune microenvironment (TIME) of melanoma was also analyzed using the TCGA cohort.

RESULTS

In the TCGA cohort, survival in melanoma patients with or without FGFR mutations was nearly equivalent. In the ICIs-treated cohort, patients with FGFR mutations had better survival than those without (median overall survival: 60.00 vs. 31.00 months; hazard ratio: 0.58, 95% CI: 0.42-0.80; P = 0.0051). Besides, the objective response rate was higher for patients harboring FGFR mutations (55.56%) compared to wild-type patients (22.40%) (P = 0.0076). Mechanistically, it was revealed that FGFR mutations correlated with increased immunogenicity (e.g., TMB, NAL, MMR-related gene mutations and DDR-related gene mutations). Meanwhile, FGFR mutant melanoma tended to exhibit an enhanced antitumor TIME compared with its wild-type counterparts.

CONCLUSIONS

Our study demonstrated that FGFR mutations is a promising biomarker in stratifying patients with advanced melanoma who might benefit from ICIs therapy.

Solving the puzzle of what makes immunotherapies work

The rapid adoption of immune checkpoint blockade (ICB) therapies has led to a need to understand the mechanistic drivers of efficacy and the identification of novel biomarkers that enrich for patients who benefit from ICB therapy. Here, we provide a perspective on emerging biomarker candidates, their underlying biological mechanisms, and how they may fit into the current landscape of ICB biomarkers. We discuss new frameworks to identify and evaluate biomarker candidates and review the opportunities and challenges of utilizing biomarker-derived models to facilitate the development of new immunotherapies.

A composite indicator of derived neutrophil-lymphocyte ratio and lactate dehydrogenase correlates with outcomes in pancreatic carcinoma patients treated with PD-1 inhibitors

BACKGROUND

There are currently no established biomarkers that can predict whether advanced pancreatic carcinoma (PC) patients would benefit from immune checkpoint inhibitors (ICIs). Our study investigated whether the pretreatment composite biomarker of derived neutrophil-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) can be used as a reliable prognostic factor for the survival of PC patients receiving PD-1 inhibitor therapy.

METHODS

Patients with advanced PC treated with PD-1 inhibitors at a single center from September 2015 to September 2020 were included. The high levels of dNLR (≥3) and LDH (≥250 U/L) were considered to be risk factors. Based on these two risk factors, patients in this study were categorized into two risk groups: the good dNLR-LDH group, without risk factors, and the intermediate/poor dNLR-LDH group, with one to two risk factors. Overall survival (OS) and progression-free survival (PFS) served as this study's primary and secondary endpoints. Cox regression models were used to identify independent prognostic factors for survival benefit.

RESULTS

There were 98 patients in our study. The good group included 61 (62.2%) patients and the intermediate/poor group included 37 (37.8%). The overall patients with PC who received immunotherapy had a median OS of 12.1 months, and the good dNLR-LDH group had a significantly longer OS compared with the intermediate/poor dNLR-LDH group (44.2 vs. 6.4 months; p < 0.010); median PFS was 3.7 and 2.5 months (p = 0.010). The number of metastatic sites >2 and immunotherapy as third-line or later was associated with worse PFS, and the line of immunotherapy and the dNLR-LDH indicator were independent prognostic factors for OS, according to multivariate analysis.

CONCLUSION

The pretreatment composite biomarker of dNLR and LDH can be used as a prognostic biomarker in patients with advanced PC treated with PD-1 inhibitors.

The multiple roles of LDH in cancer

High serum lactate dehydrogenase (LDH) levels are typically associated with a poor prognosis in many cancer types. Even the most effective drugs, which have radically improved outcomes in patients with melanoma over the past decade, provide only marginal benefit to those with high serum LDH levels. When viewed separately from the oncological, biochemical, biological and immunological perspectives, serum LDH is often interpreted in very different ways. Oncologists usually see high serum LDH only as a robust biomarker of a poor prognosis, and biochemists are aware of the complexity of the various LDH isoforms and of their key roles in cancer metabolism, whereas LDH is typically considered to be oncogenic and/or immunosuppressive by cancer biologists and immunologists. Integrating these various viewpoints shows that the regulation of the five LDH isoforms, and their enzymatic and non-enzymatic functions is closely related to key oncological processes. In this Review, we highlight that serum LDH is far more than a simple indicator of tumour burden; it is a complex biomarker associated with the activation of several oncogenic signalling pathways as well as with the metabolic activity, invasiveness and immunogenicity of many tumours, and constitutes an extremely attractive target for cancer therapy.

The relationship between objective measures of physical function and serum lactate dehydrogenase in older adults with cancer prior to treatment

BACKGROUND

Lactate dehydrogenase (LDH) reflects tumor burden and is a prognosticator of all-cause mortality in patients with cancer. Objective measures of physical function are associated with clinically relevant outcomes in older adults with cancer. However, whether physical function is associated with LDH in geriatric oncology is unknown. The objective of this study was to assess the relationship between objective measures of physical function and serum LDH in older adults with cancer prior to treatment.

METHODS

Data from older adults with cancer prior to treatment were retrieved from an institutional database and medical records within a tertiary cancer centre. Physical function measures involved muscle strength and physical performance. Muscle strength and physical performance were assessed through grip strength and the Short Physical Performance Battery (SPPB), respectively. LDH was log transformed using the natural logarithm. Multivariable logistic regression was used to examine the relationship between objective measures of physical function and LDH prior to treatment in all participants. Stratified analyses were performed for participants with solid and hematological cancers.

RESULTS

A total of 257 participants (mean age: 80.2y) were included in the analysis. Most participants were females (50.6%) and were diagnosed with locally advanced (26.8%), gastrointestinal disease (35.0%). The multivariable analysis indicated that SPPB was inversely associated with LDH in all participants (B = -0.019, 95%CI = -0.036 to -0.002, p = 0.028). Notably, the inverse relationship between SPPB and LDH persisted only in patients with hematological malignancies in the multivariable model of the stratified analysis (B = -0.049, 95%CI = -0.087 to -0.011, p = 0.013). Neither grip strength alone nor the combination of low grip strength and/or SPPB were associated with LDH. Compared to participants with metastatic disease, those with localized or locally advanced disease had lower serum LDH.

CONCLUSION

Physical performance is inversely associated with serum LDH in older adults with hematological cancers prior to treatment.

Liquid Biopsy: A Multi-Parametric Analysis of Mutation Status, Circulating Tumor Cells and Inflammatory Markers in EGFR-Mutated NSCLC

The liquid biopsy has the potential to improve patient care in the diagnostic and therapeutic setting in non-small cell lung cancer (NSCLC). Consented patients with epidermal growth factor receptor (EGFR) positive disease (n = 21) were stratified into two cohorts: those currently receiving EGFR tyrosine kinase inhibitor (TKI) therapy (n = 9) and newly diagnosed EGFR TKI treatment-naïve patients (n = 12). Plasma genotyping of cell-free DNA was carried out using the FDA-approved cobas® EGFR mutation test v2 and compared to next generation sequencing (NGS) cfDNA panels. Circulating tumor cell (CTC) numbers were correlated with treatment response and EGFR exon 20 p.T790M. The prognostic significance of the neutrophil to lymphocyte ratio (NLR) and lactate dehydrogenase (LDH) was also investigated. Patients in cohort 1 with an EGFR exon 20 p.T790M mutation progressed more rapidly than those with an EGFR sensitizing mutation, while patients in cohort 2 had a significantly longer progression-free survival (p = 0.04). EGFR exon 20 p.T790M was detected by liquid biopsy prior to disease progression indicated by computed tomography (CT) imaging. The cobas® EGFR mutation test detected a significantly greater number of exon 20 p.T790M mutations (p = 0.05). High NLR and derived neutrophil to lymphocyte ratio (dNLR) were associated with shorter time to progression and worse survival outcomes (p < 0.05). High LDH levels were significantly associated with shorter time to disease progression (p = 0.03). These data support the use of liquid biopsy for monitoring EGFR mutations and inflammatory markers as prognostic indicators in NSCLC.

Disease Recurrence during Adjuvant Immune Checkpoint Inhibitor Treatment in Metastatic Melanoma: Clinical, Laboratory, and Radiological Characteristics in Patients from a Single Tertiary Referral Center

Despite the dramatic improvements in recurrence-free survival in patients with metastatic melanoma treated with immune checkpoint inhibitors (ICI), a number of patients develop metastases during adjuvant therapy. It is not currently possible to predict which patients are most likely to develop disease recurrence due to a lack of reliable biomarkers. Thus, we retrospectively analyzed the case records of all patients who commenced adjuvant ICI therapy between January 2018 and December 2021 in a single university skin cancer center (n = 46) (i) to determine the rates of disease recurrence, (ii) to examine the utility of established markers, and (iii) to examine whether re-challenge with immunotherapy resulted in clinical response. Twelve out of forty-six (26%) patients developed a relapse on adjuvant immunotherapy in our cohort, and the median time to relapse was 139 days. Adjuvant immunotherapy was continued in three patients. Of the twelve patients who developed recurrence during adjuvant immunotherapy, seven had further disease recurrence within the observation period, with a median time of 112 days after the first progress. There was no significant difference comparing early recurrence (<180 days after initiation) on adjuvant immunotherapy to late recurrence (>180 days after initiation) on adjuvant immunotherapy. Classical tumor markers, including serum lactate dehydrogenase (LDH) and S-100, were unreliable for the detection of disease recurrence. Baseline lymphocyte and eosinophil counts and those during immunotherapy were not associated with disease recurrence. Interestingly, patients with NRAS mutations were disproportionately represented (60%) in the patients who developed disease recurrence, suggesting that these patients should be closely monitored during adjuvant therapy.

Unveiling the tumor immune microenvironment of organ-specific melanoma metastatic sites

Background

The liver is a known site of resistance to immunotherapy and the presence of liver metastases is associated with shorter progression-free and overall survival (OS) in melanoma, while lung metastases have been associated with a more favorable outcome. There are limited data available regarding the immune microenvironment at different anatomical sites of melanoma metastases. This study sought to characterize and compare the tumor immune microenvironment of liver, brain, lung, subcutaneous (subcut) as well as lymph node (LN) melanoma metastases.

Methods

We analyzed OS in 1924 systemic treatment-naïve patients with AJCC (American Joint Committee on Cancer) stage IV melanoma with a solitary site of organ metastasis. In an independent cohort we analyzed and compared immune cell densities, subpopulations and spatial distribution in tissue from liver, lung, brain, LN or subcut sites from 130 patients with stage IV melanoma.

Results

Patients with only liver, brain or bone metastases had shorter OS compared to those with lung, LN or subcutaneous and soft tissue metastases. Liver and brain metastases had significantly lower T-cell infiltration than lung (p=0.0116 and p=0.0252, respectively) and LN metastases (p=0.0116 and p=0.0252, respectively). T cells were further away from melanoma cells in liver than lung metastases (p=0.0335). Liver metastases displayed unique T-cell profiles, with a significantly lower proportion of programmed cell death protein-1+ T cells compared to all other anatomical sites (p<0.05), and a higher proportion of TIM-3+ T cells compared to LN (p=0.0004), subcut (p=0.0082) and brain (p=0.0128) metastases. Brain metastases had a lower macrophage density than subcut (p=0.0105), liver (p=0.0095) and lung (p<0.0001) metastases. Lung metastases had the highest proportion of programmed death ligand-1+ macrophages of the total macrophage population, significantly higher than brain (p<0.0001) and liver metastases (p=0.0392).

Conclusions

Liver and brain melanoma metastases have a significantly reduced immune infiltrate than lung, subcut and LN metastases, which may account for poorer prognosis and reduced immunotherapy response rates in patients with liver or brain metastases. Increased TIM-3 expression in liver metastases suggests TIM-3 inhibitor therapy as a potential therapeutic opportunity to improve patient outcomes.

High IGKC-Expressing Intratumoral Plasma Cells Predict Response to Immune Checkpoint Blockade

Resistance to Immune Checkpoint Blockade (ICB) constitutes the current limiting factor for the optimal implementation of this novel therapy, which otherwise demonstrates durable responses with acceptable toxicity scores. This limitation is exacerbated by a lack of robust biomarkers. In this study, we have dissected the basal TME composition at the gene expression and cellular levels that predict response to Nivolumab and prognosis. BCR, TCR and HLA profiling were employed for further characterization of the molecular variables associated with response. The findings were validated using a single-cell RNA-seq data of metastatic melanoma patients treated with ICB, and by multispectral immunofluorescence. Finally, machine learning was employed to construct a prediction algorithm that was validated across eight metastatic melanoma cohorts treated with ICB. Using this strategy, we have unmasked a major role played by basal intratumoral Plasma cells expressing high levels of IGKC in efficacy. IGKC, differentially expressed in good responders, was also identified within the Top response-related BCR clonotypes, together with IGK variants. These results were validated at gene, cellular and protein levels; CD138+ Plasma-like and Plasma cells were more abundant in good responders and correlated with the same RNA-seq-defined fraction. Finally, we generated a 15-gene prediction model that outperformed the current reference score in eight ICB-treated metastatic melanoma cohorts. The evidenced major contribution of basal intratumoral IGKC and Plasma cells in good response and outcome in ICB in metastatic melanoma is a groundbreaking finding in the field beyond the role of T lymphocytes.

Peripheral blood indices to predict PFS/OS with anlotinib as a subsequent treatment in advanced small-cell lung cancer

OBJECTIVE

In the phase II ALTER-1202 (NCT03059797) trial, anlotinib significantly improved progression-free survival (PFS) and overall survival (OS) in patients with advanced small-cell lung cancer (SCLC) who underwent at least 2 previous chemotherapy cycles, when compared with a placebo group. To identify potential factors for predicting efficacy and prognosis with anlotinib treatment, we analyzed hematological indices at baseline and adverse events (AEs) over the course of anlotinib treatment.

METHODS

Data were collected from March 2017 to April 2019 from a randomized, double-blind, placebo-controlled, multicenter, phase II trial of anlotinib. Eligible patients were randomly assigned 2:1 to receive anlotinib or placebo until disease progression, intolerable toxicity, or withdrawal of consent. The patients received anlotinib (12 mg) or an analogue capsule (placebo) orally once daily for 14 days every 3 weeks. The hematological indices at baseline and AEs that occurred in the initial 2 treatment cycles were recorded. The Kaplan-Meier test and Cox regression model were used to assess survival differences.

RESULTS

A total of 82 patients (81 patients with complete data) were randomly assigned to receive anlotinib, with 38 receiving a placebo as a control. Multivariate analysis indicated that an elevated neutrophil to lymphocyte ratio > 7.75 and lactate dehydrogenase > 254.65 U/L at baseline were independent risk factors for PFS; basal elevated aspartate aminotransferase > 26.75 U/L, neuron specific enolase > 18.64 ng/mL, and fibrinogen > 4.645 g/L were independent risk factors for OS. During treatment, elevated γ glutamyltransferase and hypophosphatemia were independent predictors for a poor PFS, and elevated γ-glutamyl transferase and hypercholesterolemia were independent factors for OS.

CONCLUSIONS

Our study preliminarily defined potential factors that affected the PFS and OS at baseline and during anlotinib treatment in patients with advanced SCLC. Our findings provide a basis for screening the dominant population and for dynamic efficacy monitoring with anlotinib therapy.

Prognostic value of neutrophil-lymphocyte ratio and lactate dehydrogenase in melanoma patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) showed promising therapeutic efficacy on melanoma. Neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (LDH) showed predictive values on prognosis of various tumors, but not on melanoma yet. This meta-analysis was conducted to investigate the prognostic role of NLR and LDH levels in melanoma treated with ICIs.

METHODS

A search was conducted for all reports published till March 2020 in PubMed, Web of Science, Cochrane Library, EMBASE, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform (ICTRP). Studies were included if they investigated the association between pretreatment NLR/LDH and prognosis in melanoma patients treated with ICIs. Subgroup analysis, publication bias, and meta-regression were conducted to investigate heterogeneity.

RESULTS

A total of 6817 melanoma patients were included. Overall, high pretreatment NLR and LDH were associated with poor overall survival (OS) (P < .001) and PFS (P < .001). Subgroup analyses revealed that elevated NLR and LDH levels were associated with poor OS and PFS in patients treated with anti-CTLA-4 or anti-PD-1/PD-L1 alone. NLR level was superior in predicting OS if compared with LDH level in patients treated with anti-PD-1/PD-L1 + anti-CTLA-4. In subgroup analysis stratified by cutoff value, high NLR level was associated with poor OS and PFS regardless of cutoff value, but LDH works when cutoff value = upper normal limit (UNL). The predictive value of NLR and LDH levels on OS and PFS was partially compromised in the Asian populations, compared with the Western countries.

CONCLUSION

Blood NLR and LDH levels showed great potential to be used as early prognostic biomarkers in melanoma patients treated with ICIs.

The Prognostic Value of Gastric Immune Prognostic Index in Gastric Cancer Patients Treated With PD-1/PD-L1 Inhibitors

Objective: This study aimed to investigate the prognostic value of the gastric immune prognostic index (GIPI) in gastric cancer patients treated with programmed death 1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors.

Methods: This study was conducted to elucidate the role of GIPI using the data from 146 gastric cancer patients treated with PD-1/PD-L1 inhibitors between August 2016 and December 2020 in Harbin Medical University Cancer Hospital. The GIPI calculation was based on dNLR and LDH. Patients were categorized into three groups: 1) GIPI good (LDH ≤250 U/L and dNLR ≤3); 2) GIPI intermediate (LDH &gt;250 U/L and NLR &gt;3); 3) GIPI poor (LDH &gt;250 U/L and dNLR &gt;3). The correlations between GIPI and clinicopathologic characteristics were determined by the Chi-square test or the Fisher’s exact test. The Kaplan–Meier analysis and log-rank test were used to calculate and compare progression-free survival (PFS) and overall survival (OS). The univariate and multivariate Cox proportional hazards regression model was used to detect prognostic and predictive factors of PFS and OS.

Results: 146 patients treated with PD-1/PD-L1 inhibitors were included in this study, of which, 72.6% were GIPI good, 23.3% were GIPI intermediate, and 4.1% were GIPI poor. The GIPI was associated with the common blood parameters, including neutrophils and lymphocytes. The multivariate analysis showed that platelet, TNM stage, and treatment were the independent prognostic factors for PFS and OS. Patients with GIPI intermediate/poor were associated with shorter PFS (median: 24.63 vs. 32.50 months; p = 0.078) and OS (median: 28.37 months vs. not reached; p = 0.033) than those with GIPI good. GIPI intermediate/poor was correlated with shorter PFS and OS than GIPI good, especially in subgroups of patients with ICI treatment and patients with PD-1/PD-L1 positive status.

Conclusions: The GIPI correlated with poor outcomes for PD-1/PD-L1 expression status and may be useful for identifying gastric cancer patients who are unlikely to benefit from treatment.

Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy

Simple Summary

The use of immunotherapeutic agents significantly improved stage-IV melanoma patients’ overall progression-free survival. To identify patients who do not benefit from immunotherapy, both clinical parameters and experimental biomarkers such as radiomics are currently being evaluated. However, no radiomic biomarker is widely accepted for routine clinical use. In a large cohort of 262 stage-IV melanoma patients given first-line immunotherapy treatment, we investigated whether radiomics—based on the segmentation of all baseline metastases in the whole body—in combination with clinical parameters offered added value compared to the usage of clinical parameters alone in a machine-learning prediction model. The primary endpoints were response at three months, and survival rates at six and twelve months. The study indicated a potential, but non-significant, added value of radiomics for six-month and twelve-month survival prediction, thus underlining the relevance of clinical parameters.

Abstract

Background: This study investigated whether a machine-learning-based combination of radiomics and clinical parameters was superior to the use of clinical parameters alone in predicting therapy response after three months, and overall survival after six and twelve months, in stage-IV malignant melanoma patients undergoing immunotherapy with PD-1 checkpoint inhibitors and CTLA-4 checkpoint inhibitors. Methods: A random forest model using clinical parameters (demographic variables and tumor markers = baseline model) was compared to a random forest model using clinical parameters and radiomics (extended model) via repeated 5-fold cross-validation. For this purpose, the baseline computed tomographies of 262 stage-IV malignant melanoma patients treated at a tertiary referral center were identified in the Central Malignant Melanoma Registry, and all visible metastases were three-dimensionally segmented (n = 6404). Results: The extended model was not significantly superior compared to the baseline model for survival prediction after six and twelve months (AUC (95% CI): 0.664 (0.598, 0.729) vs. 0.620 (0.545, 0.692) and AUC (95% CI): 0.600 (0.526, 0.667) vs. 0.588 (0.481, 0.629), respectively). The extended model was not significantly superior compared to the baseline model for response prediction after three months (AUC (95% CI): 0.641 (0.581, 0.700) vs. 0.656 (0.587, 0.719)). Conclusions: The study indicated a potential, but non-significant, added value of radiomics for six-month and twelve-month survival prediction of stage-IV melanoma patients undergoing immunotherapy.

Diagnostic performance of early increase in S100B or LDH as outcome predictor for non-responsiveness to anti-PD-1 monotherapy in advanced melanoma

As a subset of advanced melanoma patients derive long-term benefit from anti-PD-1 therapy, early identification of non-responsiveness would enable an early switch to next line therapies. This study assessed if an early increase in S100B or lactate dehydrogenase (LDH) could be predictive for non-responsiveness to anti-PD-1. We retrospectively analysed advanced melanoma patients treated with anti-PD-1 monotherapy. Serum S100B and LDH levels were measured at baseline and before every infusion. Non-response was defined as progression or death at 6 months. Marker cut-offs were defined based on > 95% specificity and feasibility in clinical practice. For validation an independent cohort was analysed. In total, 313 patients were included (166 patients in training cohort, 147 patients in validation cohort). Increase of > 50% in LDH or > 100% in S100B above upper limit of normal at week 6 compared to baseline was determined as criterion to positively test for non-responsiveness. In the validation cohort, obtained specificity of the combination test was > 95% with a positive predictive value of 82%; obtained sensitivity was lower (21%), with a negative predictive value of 55%. Early increase in S100B or LDH is a strong parameter for non-responsiveness to anti-PD-1 in advanced melanoma. Prospective confirmation is needed before clinical implementation.

Hematological Prognostic Scoring System Can Predict Overall Survival and Can Indicate Response to Immunotherapy in Patients With Osteosarcoma

Osteosarcoma is the most common primary malignant bone tumor with a high metastatic potential. Nowadays, there is a lack of new markers to identify prognosis of osteosarcoma patients with response to medical treatment. Recent studies have shown that hematological markers can reflect to some extent the microenvironment of an individual with the potential to predict patient prognosis. However, most of the previous studies have studied the prognostic value of a single hematological index, and it is difficult to comprehensively reflect the tumor microenvironment of patients. Here, we comprehensively collected 16 hematological markers and constructed a hematological prognostic scoring system (HPSS) using LASSO cox regression analysis. HPSS contains many indicators such as immunity, inflammation, coagulation and nutrition. Our results suggest that HPSS is an independent prognostic factor for overall survival in osteosarcoma patients and is an optimal addition to clinical characteristics and well suited to further identify high-risk patients from clinically low-risk patients. HPSS-based nomograms have good predictive ability. Finally, HPSS also has some hints for immunotherapy response in osteosarcoma patients.

Classification and Staging of Melanoma in the Head and Neck

The rates of melanoma continue to rise, with recent estimates have shown that 18% to 22% of new melanoma cases occur within the head and neck in the United States each year. The mainstay of treatment of nonmetastatic primary melanomas of the head and neck includes the surgical resection and management of regional disease as indicated. Thorough knowledge of the classification and staging of melanoma is paramount to evaluate prognosis, determine the appropriate surgical intervention, and assess eligibility for adjuvant therapy and clinic trials. The traditional clinicopathologic classification of melanoma is based on morphologic aspects of the growth phase and distinguishes 4 of the most common subtypes as defined by the World Health Organization: superficial spreading, nodular, acral lentiginous, and lentigo maligna melanoma. The data used to derive the AJCC TNM Categories are based on superficial spreading melanoma and nodular subtypes. Melanoma is diagnosed histopathologically following initial biopsy that will assist with classifying the tumor to guide treatment. Classification is based on tumor thickness and ulceration (T stage, Breslow Staging), Regional Lymph Node Involvement (N Stage), and presence of metastasis (M Stage). Tumor thickness (Breslow thickness) and ulceration are 2 independent prognostic factors that have been shown to be the strongest predictors of survival and outcome. Clark level of invasion and mitotic rate are no longer incorporated into the current AJCC staging system, but still have shown to be important prognostic factors for cutaneous melanoma. For patients with metastatic (Stage IV) disease Lactate Dehydrogenase remains an independent predictor of survival. The Maxillofacial surgeon must remain up to date on the most current management strategies in this patient population. Classification systems and staging provide the foundation for clinical decision making and prognostication for the Maxillofacial surgeon when caring for these patients.

A B-cell or a key player? The different roles of B-cells and antibodies in melanoma

The B‐cell system plays an important role in the melanoma immune response; however, consensus has yet to be reached in many facets. Here, we comprehensively review human studies only, due to fundamental differences in the humoral response with animal models. Tumour‐infiltrating B‐cells are associated with contradictory prognostic values, reflecting a lack of agreement between studies on cell subset classification and differences in the markers used, particularly the common use of a single marker not differentiating multiple subsets. Tertiary lymphoid structures (TLS) organise T‐cells and B‐cells within tumours to generate a local anti‐tumour response and TLS presence associates with improved survival in response to immune checkpoint blockade, in late‐stage disease. Autoantibody production is increased in melanoma patients and has been proposed as biomarkers for diagnosis, prognosis and treatment/toxicity response; however, no consistent targets are yet identified. The function of antibodies in an anti‐tumour response is determined by its isotype and subclass; IgG₄ is immune‐suppressive and robustly correlate with poor patient survival in melanoma. We conclude that the current B‐cell literature needs careful interpretation based on the methods used and that we need a consensus of markers to define B‐cells and associated lymphoid organs. Furthermore, future studies need to not only examine antibody targets, but also isotypes when considering functional roles.

Vitiligo-specific soluble biomarkers as early indicators of response to immune checkpoint inhibitors in metastatic melanoma patients

Immunotherapy with checkpoint inhibitors (CPIs) strongly improved the outcome of metastatic melanoma patients. However, not all the patients respond to treatment and identification of prognostic biomarkers able to select responding patients is currently of outmost importance. Considering that development of vitiligo-like depigmentation in melanoma patients represents both an adverse event of CPIs and a favorable prognostic factor, we analyzed soluble biomarkers of vitiligo to validate them as early indicators of response to CPIs. Fifty-seven metastatic melanoma patients receiving CPIs were enrolled and divided according to the best overall response to treatment. Patient sera were evaluated at pre-treatment and after 1 and 3 months of therapy. We found that basal CD25 serum levels were higher in stable and responding patients and remained higher during the first 3 months of CPI therapy compared to non-responders. CXCL9 was absent in non-responding patients before therapy beginning. Moreover, an increase of CXCL9 levels was observed at 1 and 3 months of therapy for all patients, although higher CXCL9 amounts were present in stable and responding compared to non-responding patients. Variations in circulating immune cell subsets was also analyzed, revealing a reduced number of regulatory T lymphocytes in responding patients. Altogether, our data indicate that a pre-existing and maintained activation of the immune system could be an indication of response to CPI treatment in melanoma patients.

Fluorescence determination of lactate dehydrogenase activity based on silicon quantum dots

Silicon quantum dots (SiQDs) synthesized based on 3-aminopropyltrimethoxysilane (ATPMS) as silicon source were used to detect the activity of lactate dehydrogenase (LDH) through changes of fluorescence intensity of SiQDs. In this system, the fluorescence of SiQDs was first quenched by nicotinamide adenine dinucleotide (NADH), and then recovered with the addition of LDH, as NADH was consumed by catalytic reaction of LDH. A linear calibration chart of LDH is obtained in the range of 0.77-385 U/mL. The assay displays high selectivity towards LDH detection, and was successfully applied to the analysis of LDH in human serum samples. This assay has great prospects for the diagnosis and prognosis of various diseases, especially melanoma.