Personalised medicine: Development and external validation of a prognostic model for metastatic melanoma patients treated with ipilimumab

Platelet Concentration and Platelet/Lymphocyte Ratio as Prognostic Indicators in Luminal Breast Cancer

Ratios between the blood cells are indirect measures of the imbalance in the pro-inflammatory status observed in carcinogenesis and have been proposed as accessible and feasible biomarkers to predict cancer prognosis. We aim to evaluate the prognostic significance of neutrophil/lymphocyte (NLR), monocyte/lymphocyte (MLR), and platelet/lymphocyte (PLR) ratios in Brazilian patients with luminal breast cancer (LBC) treated with tamoxifen. A retrospective cohort of 72 operable LBC patients. Preoperative leukocyte and platelet absolute values permitted to calculate NLR, MLR, and PLR. Area under curve (ROC) determined the cutoff value associated with relapse and death. Univariate and multivariate analyses were used to assess the relationship of the platelet and PLR to disease-free survival (DFS) and overall survival (OS). Lower DFS was associated with >297 × 103/mm3 (54 vs. 60.9 months in <297, p = 0.04). Platelet > 279 × 103/mm3 are related to higher OS (p = 0.03). Univariate analysis revealed that platelet concentration was associated with DFS (p = 0.04) and OS (p = 0.04), but not as an independent factor (HR = 1.31, 95%CI: 0.42–4.07, p = 0.65) and OS (HR = 1.64, 95%CI: 0.28–9.52, p = 0.58). Both univariate (p = 0.01) and multivariate analysis revealed that PLR < 191.5 was a significant independent predictor of higher OS/better prognosis (HR = 16.16, 95%CI: 2.83–109.25, p = 0.00). Pretreatment platelet indices (absolute count and PLR) are prognosis predictors in LBC patients. Platelet > 279 × 103/mm3 and PRL < 191.5 was associated with a higher OS, with the PRL being an independent predictor of higher OS.

Stress and cancer: The mechanisms of immune dysregulation and management

Advances in the understanding of psychoneuroimmunology in the past decade have emphasized the notion that stress and cancer are interlinked closely. Durable chronic stress accelerated tumorigenesis and progression, which is unfavorable for clinical outcomes of cancer patients. Available evidence has provided unprecedented knowledge about the role and mechanisms of chronic stress in carcinogenesis, the most well-known one is dysfunction of the hypothalamus-pituitary-adrenal (HPA) axis and the sympathetic nervous system (SNS). With abnormal activation of neuroendocrine system, stress-related hormones contribute to increased oncogenes expression, exacerbated chronic inflammation and impaired immunologic function. In addition, accumulating studies have demonstrated that diverse stress interventions including pharmacological approaches, physical exercises and psychological relaxation have been administered to assist in mental disorders reduction and life quality improvement in cancer patients. In this review, we systematically summarize the connection and mechanisms in the stress-immune-cancer axis identified by animal and clinical studies, as well as conclude the effectiveness and deficiencies of existing stress management strategies.

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 novel pretreatment immune prognostic index discriminates survival outcomes in locally advanced non-operative esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy: a 6-year retrospective study

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dNLR and LDH were correlated with OS and PFS in locally advanced ESCC patients received dCRT.

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The EIPI, a novel inflammatory-based and immune-related prognostic score, was an independent prognostic indicator in locally advanced ESCC.

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The risk stratification of EIPI can help set individualized treatment strategies and intensities for different subgroups of ESCC patients.

Objective

We aimed to construct risk stratification to help set individualized treatment strategies and intensities for different subgroups of patients.

Methods

The Esophagus Immune Prognostic Index (EIPI) scores were constructed according to the levels of derived neutrophil-to-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) before treatment, and the patients were divided into low-, medium-, and high-risk groups. Finally, restricted cubic splines (RCS) were used to explore the relationship between dNLR, LDH, and survival outcomes.

Results

The median follow-up period of overall survival (OS) and progression-free survival (PFS) were 25.2 and 17.6 months, respectively. Multivariate Cox regression analysis showed dNLR were the independent prognostic factors that were associated with OS and PFS. The 3-year OS and PFS rates in the low-, medium-, and high-risk groups were 44.4% and 38.2%, 26.1% and 23.6%, and 10.5% and 5.3%, respectively. Patients who received chemotherapy had better OS and PFS than those who did not receive chemotherapy in low-risk and medium/high-risk groups (all p < 0.05). Besides, the results also revealed significant differences for patients with clinical T, N, and TNM stage groups of the OS and PFS in different risk groups. Finally, RCS analysis indicated a nonlinear relationship between the dNLR, LDH, and survival for esophageal squamous cell carcinoma (ESCC) patients. The death hazard ratios of dNLR and LDH sharply increased at 1.97 and 191, respectively.

Conclusions

In summary, the EIPI, a novel inflammatory-based and immune-related prognostic score, is an independent prognostic indicator in locally advanced ESCC patients undergoing definitive chemoradiotherapy (dCRT).

Novel Biomarkers and Druggable Targets in Advanced Melanoma

Immunotherapy with Ipilimumab or antibodies against programmed death (ligand) 1 (anti-PD1/PDL1), targeted therapies with BRAF-inhibitors (anti-BRAF) and their combinations significantly changed melanoma treatment options in both primary, adjuvant and metastatic setting, allowing for a cure, or at least long-term survival, in most patients. However, up to 50% of those with advance or metastatic disease still have no significant benefit from such innovative therapies, and clinicians are not able to discriminate in advance neither who is going to respond and for how long nor who is going to develop collateral effects and which ones. However, druggable targets, as well as affordable and reliable biomarkers are needed to personalize resources at a single-patient level. In this manuscript, different molecules, genes, cells, pathways and even combinatorial algorithms or scores are included in four biomarker chapters (molecular, immunological, peripheral and gut microbiota) and reviewed in order to evaluate their role in indicating a patient’s possible response to treatment or development of toxicities.

Predictive Biomarkers for Outcomes of Immune Checkpoint Inhibitors (ICIs) in Melanoma: A Systematic Review

Immune checkpoint inhibitors (ICIs) have strongly improved the survival of melanoma patients. However, as durable response to ICIs are only seen in a minority, there is an unmet need to identify biomarkers that predict response. Therefore, we provide a systematic review that evaluates all biomarkers studied in association with outcomes of melanoma patients receiving ICIs. We searched Pubmed, COCHRANE Library, Embase, Emcare, and Web of Science for relevant articles that were published before June 2020 and studied blood, tumor, or fecal biomarkers that predicted response or survival in melanoma patients treated with ICIs. Of the 2536 identified reports, 177 were included in our review. Risk of bias was high in 40%, moderate in 50% and low in 10% of all studies. Biomarkers that correlated with response were myeloid-derived suppressor cells (MDSCs), circulating tumor cells (CTCs), CD8+ memory T-cells, T-cell receptor (TCR) diversity, tumor-infiltrating lymphocytes (TILs), gene expression profiling (GEP), and a favorable gut microbiome. This review shows that biomarkers for ICIs in melanoma patients are widely studied, but heterogeneity between studies is high, average sample sizes are low, and validation is often lacking. Future studies are needed to further investigate the predictive utility of some promising candidate biomarkers.

Deep Learning-Based Body Composition Analysis Predicts Outcome in Melanoma Patients Treated with Immune Checkpoint Inhibitors

Previous studies suggest an impact of body composition on outcome in melanoma patients. We aimed to determine the prognostic value of CT-based body composition assessment in patients receiving immune checkpoint inhibitor therapy for treatment of metastatic disease using a deep learning approach. One hundred seven patients with staging CT examinations prior to initiation of checkpoint inhibition between January 2013 and August 2019 were retrospectively evaluated. Using an automated deep learning-based body composition analysis pipeline, parameters for estimation of skeletal muscle mass (skeletal muscle index, SMI) and adipose tissue compartments (visceral adipose tissue index, VAI; subcutaneous adipose tissue index, SAI) were derived from staging CT. The cohort was binarized according to gender-specific median cut-off values. Patients below the median were defined as having low SMI, VAI, or SAI, respectively. The impact on outcome was assessed using the Kaplan-Meier method with log-rank tests. A multivariable logistic regression model was built to test the impact of body composition parameters on 3-year mortality. Patients with low SMI displayed significantly increased 1-year (25% versus 9%, p = 0.035), 2-year (32% versus 13%, p = 0.017), and 3-year mortality (38% versus 19%, p = 0.016). No significant differences with regard to adipose tissue compartments were observed (3-year mortality: VAI, p = 0.448; SAI, p = 0.731). On multivariable analysis, low SMI (hazard ratio (HR), 2.245; 95% confidence interval (CI), 1.005-5.017; p = 0.049), neutrophil-to-lymphocyte ratio (HR, 1.170; 95% CI, 1.076-1.273; p < 0.001), and Karnofsky index (HR, 0.965; 95% CI, 0.945-0.985; p = 0.001) remained as significant predictors of 3-year mortality. Lowered skeletal muscle index as an indicator of sarcopenia was associated with worse outcome in patients with metastatic melanoma receiving immune checkpoint inhibitor therapy.

Overcoming Resistance to Immunotherapy in Advanced Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (CSCC) is the second most frequent cancer in humans, and is now responsible for as many deaths as melanoma. Immunotherapy has changed the therapeutic landscape of advanced CSCC after the FDA approval of anti-PD1 molecules for the treatment of locally advanced and metastatic CSCC. However, roughly 50% of patients will not respond to this systemic treatment and even those who do respond can develop resistance over time. The etiologies of primary and secondary resistance to immunotherapy involve changes in the neoplastic cells and the tumor microenvironment. Indirect modulation of immune system activation with new therapies, such as vaccines, oncolytic viruses, and new immunotherapeutic agents, and direct modulation of tumor immunogenicity using other systemic treatments or radiotherapy are now under evaluation in combined regimens. The identification of predictors of response is an important area of research. In this review, we focus on the features associated with the response to immunotherapy, and the evaluation of combination treatments and new molecules, a more thorough knowledge of which is likely to improve the survival of patients with advanced CSCC.

Novel Prognostic Models Predicting the Cancer-Specific Survival in Patients with Cutaneous Melanoma Based on Metastatic Lymph Node Status

BACKGROUND

In cutaneous melanoma (CM), the present methods of lymph node (LN) staging have not sufficiently utilized the prognostic information of metastatic LNs. In this study, we aimed to construct prognostic nomograms based on the number of positive LNs (PLNs) and other clinicopathologic characteristics of CM patients.

METHODS

Two prognostic models were constructed in the none/single PLN (PLN_none/single) and multiple PLN (PLN_multiple) cohorts, respectively. Independent prognostic predictors associated with cancer-specific survival (CSS) in the above two cohorts were integrated to construct two nomograms for predicting the probability of 2-, 4-, and 6-year CSS in the PLN_none/single and PLN_multiple cohorts. The nomograms were evaluated by the area under the receiver operating characteristic curves (AUC), the calibration plots, and the decision curve analyses (DCAs).

RESULTS

A total of 31,065 CM cases were included in this study. Factors included in the prognostic nomogram for patients in the PLN_none/single cohort were age, sex, race, marital status, insurance, primary tumor site, T stage, and number of PLNs, while factors included in the nomogram for cases in the PLN_multiple cohort included age, sex, marital status, insurance, primary tumor site, T stage, and number of PLNs. The AUC values for 2-, 4-, and 6-year CSS in the validation group of the PLN_none/single cohort were 0.833, 0.811, and 0.818, respectively, while in the validation group of the PLN_multiple cohort, the AUC values for 2-, 4,- and 6-year CSS were 0.720, 0.723, and 0.745, respectively. Compared with the American Joint Committee on Cancer 7th edition staging system, our two nomograms showed better predictive values. Additionally, the calibration plots and DCA curves for 2-, 4-, and 6-year CSS prediction demonstrated good coordination and net benefit in both the PLN_none/single and PLN_multiple cohorts.

CONCLUSION

Our nomograms, based on the number of PLNs and other clinicopathologic characteristics, showed good predictive ability for predicting the survival of CM patients.

Prognostic Significance of Baseline Neutrophil Count and Lactate Dehydrogenase Level in Patients With Esophageal Squamous Cell Cancer Treated With Radiotherapy

Background: This present study aimed to explore the prognostic value of pretreatment neutrophil and lactate dehydrogenase (LDH) and to develop a prognostic risk scoring model to predict prognosis in esophageal squamous cell cancer (ESCC) patients treated with definitive radiotherapy.

Methods: Retrospectively collected data of patients who received definitive radiotherapy for ESCC at Shantou Central Hospital between January 2009 and December 2015 were included for the analysis. The association between the level of LDH and neutrophil and clinicopathological characteristics were analyzed. We performed univariate and multivariate analyses to identify the prognostic predictors for patients with ESCC. Based on the results, we also developed a prognostic risk scoring model and assessed its predictive ability in the subgroups.

Results: A total of 567 patients who received definitive radiotherapy for ESCC were included in the present study. The optimal cutoff values were 4.5 × 10⁹/L, 3.25, and 220 U/L for neutrophil, neutrophil-to-lymphocyte ratio (NLR), and LDH, respectively. A high level of LDH was significantly associated with advanced N stage (p = 0.031), and neutrophil count was significantly associated with gender (p = 0.001), T stage (p < 0.001), N stage (p = 0.019), clinical stage (p < 0.001), and NLR (p < 0.001). Multivariate survival analysis identified gender (p = 0.006), T stage (p < 0.001), N stage (p = 0.008), treatment modality (p < 0.001), LDH level (p = 0.012), and neutrophil count (p = 0.038) as independent prognostic factors for overall survival. Furthermore, a new prognostic risk scoring (PRS) model based on six prognostic factors was developed, in which the patients were divided into three groups with distinct prognosis (χ2 = 67.94, p < 0.0001).

Conclusions: Elevated baseline LDH level and neutrophil count predicted poor prognosis for ESCC patients treated with definitive radiotherapy. A PRS model comprised of LDH, neutrophil count, and other prognostic factors would help identify the patients who would benefit the most from definitive radiotherapy.

Biomarkers Associated with Clinical Outcome of Advanced Melanoma Patients Treated with Ipilimumab

Ipilimumab was the first immunotherapy approved for metastatic melanoma in decades and is currently registered as a second-line treatment. However, new immunotherapies, in combination with ipilimumab, offer even better clinical outcomes for patients compared with single-agent treatments, at the expense of improved toxicity. The aim of this study was to evaluate the feasibility of ipilimumab outside the clinical trials and to identify survival predictors for treatment benefit. Data were collected on 47 advanced melanoma patients treated with ipilimumab between 2010 and 2015 at a single center. Association of clinical characteristics (including primary tumor characteristics), serum lactate dehydrogenase (LDH), erythrocyte sedimentation rate, absolute eosinophil, lymphocyte, and neutrophil count, neutrophil/lymphocyte and eosinophil/lymphocyte ratio with toxicity and clinical outcome were assessed using univariate and multivariate analysis. Median progression-free survival at a median follow-up of 10 months was 2.7 months and median overall survival was 9.8 months. Objective response was observed in 17% of patients and the disease control rate at week 24 was 40%. The 1- and 2-year survival rates documented were 40 and 28%, respectively. Significant association between high LDH level (>1.5× upper limit of normal) and decreased overall survival was demonstrated in uni- and multivariate analysis (hazard ratio [HR]: 3.554, 95% CI: 1.225-10.306, p = 0.019). Neither biomarkers nor clinical outcome were associated with toxicity. Using baseline serum LDH to identify patients most likely to benefit from ipilimumab therapy could serve as a simple and inexpensive biomarker of clinical outcome.

Prognostic Value of Peripheral Inflammatory Markers in Preoperative Mucosal Melanoma: A Multicenter Retrospective Study

Background: Peripheral neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) have been widely reported prognostic predictors for many cancers. However, data predicting prognosis on mucosal melanoma is currently limited. This study aimed to identify the value of these inflammatory markers in predicting prognosis in preoperative mucosal melanoma.

Methods: In this multicenter retrospective study, we assessed patients with preoperative mucosal melanoma for 7 years. Connection between baseline inflammatory markers (NLR, PLR, and LMR) and overall survival (OS) and progression-free survival (PFS) was analyzed by Kaplan–Meier curve with a log-rank test. Then, NLR, PLR, and LMR, along with characteristics of patients, were included in the univariate and multivariate Cox hazards regression model to examine the correlation with OS and PFS. The optimal cutoff value of these inflammatory markers was stratified by receiver operating characteristic (ROC) curve.

Results: Patients with baseline NLR > 3.07, PLR > 118.70, or LMR ≤ 7.38 had significantly poorer OS and PFS according to Kaplan–Meier curve with a log-rank test. Univariate analysis indicated that surgery, alkaline phosphatase (ALP), NLR, PLR, and LMR were statistically connected to both OS and PFS. In multivariate analysis, LMR (hazard ratio [HR] = 0.113; 95% CI: 0.017–0.772; P = 0.026) and surgery (HR = 0.166; 95% CI: 0.033–0.846; P = 0.031) maintained significant relevance with OS.

Conclusions: This research revealed that a higher NLR and PLR and a lower LMR than the cutoff point was associated with a worse prognosis of preoperative mucosal melanoma. Thus, we assumed that NLR, PLR, and especially LMR were potential prognostic predictors of preoperative mucosal melanoma.

Novel Biomarkers for Personalized Cancer Immunotherapy

Cancer immunotherapy has emerged as a novel and effective treatment strategy for several types of cancer. Immune checkpoint inhibitors (ICIs) have recently demonstrated impressive clinical benefit in some advanced cancers. Nonetheless, in the majority of patients, the successful use of ICIs is limited by a low response rate, high treatment cost, and treatment-related toxicity. Therefore, it is necessary to identify predictive and prognostic biomarkers to select the patients who are most likely to benefit from, and respond well to, these therapies. In this review, we summarize the evidence for candidate biomarkers of response to cancer immunotherapy.

Precision Medicine and its Role in the Treatment of Sepsis: A Personalised View

In recent years, a new form of medicine has become increasingly significant, namely, personalised medicine (PM). PM is a form of care in which treatment is tailored for an individual patient.

PM is about using multiple data sets to create a digital human mapping. A person’s biological traits are determined by the interactions of hundreds of genes and gene networks, as well as external factors such as diet and exercise. Combining and then investigating these multiple databases with powerful statistical tools, allows a new understanding of how genetic intricacy drives health and disease and so leads to a closer personalised medical approach that targets each individual’s unique genetic make-up.

Sepsis is a systemic inflammatory response to infection, ranging from systemic inflammatory response syndrome (SIRS) to septic shock and multiple organ dysfunction syndromes (MODS). Sepsis is the most common cause of death in intensive care patients. Treatments in an ICU may need to be adapted to the continuous and rapid changes of the disease, making it challenging to identify a single target. PM is thus seen as the future of sepsis treatment in the ICU.

The fact that individual patients respond differently to treatment should be regarded as a starting point in the approach to providing treatment. The disease itself comes secondary to this concept.

Prognostic and predictive role of elevated lactate dehydrogenase in patients with melanoma treated with immunotherapy and BRAF inhibitors: a systematic review and meta-analysis

Levels of serum lactate dehydrogenase (LDH) are a recognized prognostic factor in malignant melanoma (MM). It is relevant to confirm its prognostic role in patients treated with targeted therapies [BRAF inhibitors (BRAFi) and MEK inhibitors (MEKi)] and immunotherapy (IT). Furthermore, its role as a predictive marker in patients treated with these drugs had still not been investigated. We performed an electronic search for studies reporting information on overall survival (OS) or progression-free survival (PFS) according to LDH levels and on their predictive effect in patients treated with targeted therapies (BRAFi and MEKi) and IT. Data were pooled using hazard ratios (HRs) for OS and HRs for PFS according to a fixed-effect or a random-effect model. For predictive analysys, effect of new agents versus standard therapy was evaluated in LDH high population. A total of 71 publications were retrieved for a total of 16 159 patients. Overall, elevated LDH levels were associated with an HR for OS of 1.72 [95% confidence interval (CI): 1.6-1.85; P<0.0001]. Similarly, HR for PFS was 1.83 (95% CI: 1.53-2.2; P<0.0001). In the LDH elevated subgroup, new agents improved OS significantly (HR: 0.71; 95% CI: 0.62-0.82; P<0.0001) and PFS (HR: 0.63; 95% CI: 0.55-0.72; P<0.0001). In advanced MM treated with IT or BRAFi±MEKi, elevated LDH level at baseline represents a poor prognostic factor. However, patients with increased LDH levels and treated with these drugs gain significant benefits in terms of PFS and OS.

Lactate dehydrogenase and baseline markers associated with clinical outcomes of advanced esophageal squamous cell carcinoma patients treated with camrelizumab (SHR-1210), a novel anti-PD-1 antibody

Background

A small proportion of patients with advanced esophageal squamous cell carcinoma (ESCC) could benefit from immune checkpoint inhibitors; however, reliable peripheral blood biomarkers for outcomes of anti‐PD‐1 immunotherapy in ESCC have not been identified.

Methods

The data of 43 patients in the ESCC cohort of a phase I trial at our center were retrospectively reviewed. All patients were administered intravenous camrelizumab (SHR‐1210), a novel anti‐PD‐1 antibody, at doses of 60 mg, 200 mg, or 400 mg (4‐week interval after first dose followed by a 2‐week schedule) until disease progression or intolerable toxicity. Associations between lactate dehydrogenase (LDH) and other peripheral blood biomarkers at baseline and the efficacy of camrelizumab were also investigated.

Results

After median follow‐up of 19.6 months, the overall response rate was 25.6% (11/43), including one complete response. Median progression‐free and overall survival rates were 2.0 and 8.0 months, respectively. Patients with an elevated baseline LDH had lower tumor response rates (P = 0.02) and shorter progression‐free (P = 0.002) and overall (P < 0.0001) survival than patients with normal LDH levels. An increase in LDH levels during treatment was significantly associated with disease progression. Multivariate Cox analysis identified LDH (hazard ratio [HR] 0.18), CRP (HR 0.27), the number of organs involved (HR 0.31), absolute monocyte count (HR 0.33), and Eastern Cooperative Oncology Group performance status (HR 0.36) as independent prognostic factors.

Conclusions

Serum LDH, which is readily available in routine clinical practice, is a potential marker for response and a powerful independent factor for survival in advanced ESCC patients treated with anti‐PD‐1 therapy.

Checkpoint inhibitor-associated autoimmunity

Checkpoint inhibitors (CI) have revolutionized the management of many cancers but can result in immune-related adverse events (IRAE). In this chapter, we review the clinical manifestations and management of the most common IRAE, plus less common IRAE, such as inflammatory arthritis, of particular interest to rheumatologists. We review the mechanism of action of CI, predictors of IRAE, and the impact of IRAE on cancer outcomes. The study of IRAE is in its infancy; there are very few prospective studies and virtually no treatment trials. Where possible, we have drawn estimates of IRAE incidence from meta-analyses of randomized controlled trials. Clinical descriptions are derived from case series and case reports. Readers are encouraged to refer to consensus guidelines for IRAE management published by the American Society of Clinical Oncology and the Society for Immunotherapy of Cancer.

Tumor-derived microRNAs induce myeloid suppressor cells and predict immunotherapy resistance in melanoma

The accrual of myeloid-derived suppressor cells (MDSCs) represents a major obstacle to effective immunotherapy in cancer patients, but the mechanisms underlying this process in the human setting remain elusive. Here, we describe a set of microRNAs (miR-146a, miR-155, miR-125b, miR-100, let-7e, miR-125a, miR-146b, miR-99b) that are associated with MDSCs and resistance to treatment with immune checkpoint inhibitors in melanoma patients. The miRs were identified by transcriptional analyses as being responsible for the conversion of monocytes into MDSCs (CD14+HLA-DRneg cells) mediated by melanoma extracellular vesicles (EVs) and were shown to recreate MDSC features upon transfection. In melanoma patients, these miRs were increased in circulating CD14+ monocytes, plasma, and tumor samples, where they correlated with the myeloid cell infiltrate. In plasma, their baseline levels clustered with the clinical efficacy of CTLA-4 or programmed cell death protein 1 (PD-1) blockade. Hence, MDSC-related miRs represent an indicator of MDSC activity in cancer patients and a potential blood marker of a poor immunotherapy outcome.

Lymphocyte-to-monocyte ratio is associated with survival in pembrolizumab-treated metastatic melanoma patients

The peripheral blood lymphocyte-to-monocyte ratio (LMR) has been associated with prognosis in many malignancies including metastatic melanoma. However, it has not been studied in patients treated with immune checkpoint inhibitors. In this study, we analyzed the baseline LMR with progression-free survival (PFS) and overall survival (OS) in metastatic melanoma patients treated with pembrolizumab. A total of 133 patients with metastatic melanoma treated with pembrolizumab were included in this retrospective study. LMR was calculated from pretherapy peripheral blood counts and the optimal cutoff value was determined by a receiver operator characteristic curve. PFS and OS were evaluated using the Kaplan-Meier method and multivariate Cox proportional hazard modeling. Patients with an LMR of at least 1.7 showed improved PFS (hazard ratio=0.55; 95% confidence interval: 0.34-0.92; P=0.024) and OS (hazard ratio=0.29; 95% confidence interval: 0.15-0.59; P=0.0007). The baseline LMR is associated with PFS and OS in metastatic melanoma patients treated with pembrolizumab, and could represent a convenient and cost-effective prognostic biomarker. Validation of these findings in an independent cohort is needed.

S100B and LDH as early prognostic markers for response and overall survival in melanoma patients treated with anti-PD-1 or combined anti-PD-1 plus anti-CTLA-4 antibodies

Background

Immunotherapy with PD-1 antibodies has greatly increased prognosis of patients with advanced melanoma. Identifying biomarkers that predict overall survival (OS) and response to immunotherapy is important.

Methods

OS and best overall response according to RECIST version 1.1 were analysed, and S100B and lactate dehydrogenase (LDH) serum levels were assessed retrospectively in 152 patients treated with anti-PD-1, and in 86 patients treated with anti-PD-1 plus anti-CTLA-4 antibodies at University Hospital Tuebingen, Germany.

Results

In the pembrolizumab group, patients with elevated baseline S100B or LDH exhibited significantly impaired OS compared with patients with normal S100B (1-year OS: 51.1% vs 83.1%, log-rank P < .0001) and normal LDH (1-year OS: 44.4% vs 80.8%, P = .00022), respectively. LDH increases of >25% and S100B increases of >145% compared to baseline were significantly associated with impaired OS (both P < .0001). In patients treated with ipilimumab and nivolumab, baseline S100B and increasing S100B levels of >145% as well as baseline LDH were associated with impaired OS (P < .0001, P = .00060, and P = .0050, respectively), whereas increasing LDH of >25% was not (P = .64).

Conclusions

S100B could serve as a strong baseline marker for OS in melanoma patients receiving anti-PD-1 therapy. Rising S100B levels during the first weeks of therapy could help guide treatment decisions.

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

Background

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

Methods

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

Results

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

Conclusion

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

Sex and interleukin-6 are prognostic factors for autoimmune toxicity following treatment with anti-CTLA4 blockade

Background

Ipilimumab is a licensed immunotherapy for metastatic melanoma patients and, in the US, as adjuvant treatment for high risk melanoma radically resected. The use of ipilimumab is associated with a typical but unpredictable pattern of side effects. The purpose of this study was to identify clinical features and blood biomarkers capable of predicting ipilimumab related toxicity.

Methods

We performed a prospective study aimed at analyzing potential clinical and biological markers associated with immune-related toxicity in patients treated with ipilimumab (3 mg/kg, q3w). We enrolled 140 consecutive melanoma patients treated with ipilimumab for metastatic disease. The following prospectively collected data were utilized: patient characteristics, previous therapies, level of circulating biomarkers associated with tumour burden or immune-inflammation status (lactic dehydrogenase, C-reactive protein, β2-microglobulin, vascular endothelial growth factor, interleukin-2, interleukin-6, S-100, alkaline phosphatase, transaminases) and blood cells subsets (leukocyte and lymphocyte subpopulations). Logistic regression was used for multivariate analysis of data.

Results

Out of 140 patients, 36 (26%) experienced a severe adverse event, 33 (24%) discontinued treatment for severe toxicity. Among the immune-profile biomarkers analyzed, only interleukin-6 was associated with the risk of toxicity. Female patients had a further increase of immune-related adverse events. Low baseline interleukin-6 serum levels (OR = 2.84, 95% CI 1.34–6.03, P = 0.007) and sex female (OR = 1.5, 95% CI 1.06–2.16 P = 0.022) and were significant and independent risk factors for immune related adverse events.

Conclusions

Baseline IL6 serum levels and female sex were significantly and independently associated with higher risk of severe toxicity and could be exploited in clinical practice to personalize toxicity surveillance in patients treated with ipilimumab.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1467-x) contains supplementary material, which is available to authorized users.

Emerging Biomarkers in Cutaneous Melanoma

Earlier identification of aggressive melanoma remains a goal in the field of melanoma research. With new targeted and immune therapies that have revolutionized the care of patients with melanoma, the ability to predict progression and monitor or predict response to therapy has become the new focus of research into biomarkers in melanoma. In this review, promising biomarkers are highlighted. These biomarkers have been used to diagnose melanoma as well as predict progression to advanced disease and response to therapy. The biomarkers take various forms, including protein expression at the level of tissue, genetic mutations of cancer cells, and detection of circulating DNA. First, a brief description is provided about the conventional tissue markers used to stage melanoma, including tumor depth. Next, protein biomarkers, which provide both diagnostic and prognostic information, are described. This is followed by a discussion of important genetic mutations, microRNA, and epigenetic modifications that can provide therapeutic and prognostic material. Finally, emerging serologic biomarkers are reviewed, including circulating melanoma cells and exosomes. Overall the goal is to identify biomarkers that aid in the earlier identification and improved treatment of aggressive melanoma.

Current status and perspectives in immunotherapy for metastatic melanoma

Metastatic melanoma was the first malignancy in which immune checkpoint inhibitors demonstrated their successful efficacy. Currently, the knowledge on the interaction between the immune system and malignant disease is steadily increasing and new drugs and therapeutic strategies are overlooking in the clinical scenario. To provide a comprehensive overview of immune modulating drugs currently available in the treatment of melanoma as well as to discuss of possible future strategies in the metastatic melanoma setting, the present review aims at analyzing controversial aspects about the optimal immunomodulating treatment sequences, the search for biomarkers of efficacy of immunocheckpoint inhibitors, and innovative combinations of drugs currently under investigation.

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

Background

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

Objectives

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

Methods

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

Results

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

Conclusion

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

Predicting response and toxicity to immune checkpoint inhibitors using routinely available blood and clinical markers

Immune checkpoint inhibitors (ICI) are an important development in the treatment of advanced cancer. A substantial proportion of patients treated with ICI do not respond, and additionally patients discontinue treatment due to adverse effects. While many novel biological markers related to the specific mechanisms of ICI actions have been investigated, there has also been considerable research to identify routinely available blood and clinical markers that may predict response to ICI therapy. If validated, these markers have the advantage of being easily integrated into clinical use for nominal expense. Several markers have shown promise, including baseline and post-treatment changes in leucocyte counts, lactate dehydrogenase and C-reactive protein. While promising, the results between studies have been inconsistent due to small sample sizes, follow-up time and variability in the assessed markers. To date, research on routinely available blood and clinical markers has focussed primarily on ICI use in melanoma, the use of ipilimumab and on univariate associations, but preliminary evidence is emerging for other cancer types, other ICIs and for combining markers in multivariable clinical prediction models.

Depression in cancer: The many biobehavioral pathways driving tumor progression

Major Depressive Disorder (MDD) is common among cancer patients, with prevalence rates up to four-times higher than the general population. Depression confers worse outcomes, including non-adherence to treatment and increased mortality in the oncology setting. Advances in the understanding of neurobiological underpinnings of depression have revealed shared biobehavioral mechanisms may contribute to cancer progression. Moreover, psychosocial stressors in cancer promote: (1) inflammation and oxidative/nitrosative stress; (2) a decreased immunosurveillance; and (3) a dysfunctional activation of the autonomic nervous system and of the hypothalamic-pituitaryadrenal axis. Consequently, the prompt recognition of depression among patients with cancer who may benefit of treatment strategies targeting depressive symptoms, cognitive dysfunction, fatigue and sleep disturbances, is a public health priority. Moreover, behavioral strategies aiming at reducing psychological distress and depressive symptoms, including addressing unhealthy diet and life-style choices, as well as physical inactivity and sleep dysfunction, may represent important strategies not only to treat depression, but also to improve wider cancer-related outcomes. Herein, we provide a comprehensive review of the intertwined biobehavioral pathways linking depression to cancer progression. In addition, the clinical implications of these findings are critically reviewed.

Relevance of serum biomarkers associated with melanoma during follow-up of anti-CTLA-4 immunotherapy

Metastatic melanoma is a rapidly spreading cancer whose prognosis remains poor although important therapy advances in recent years. Ipilimumab, an anti-CTLA-4 immunotherapy used in advanced melanoma, is an effective immunotherapy alone or combined with other agents but with few predictive biomarkers of response. Here, we sought to analyze the potential of S100B, MIA, soluble MICA, anti-MICA antibodies and LDH as serum biomarkers of response and survival in a cohort of 77 advanced melanoma patients subjected to ipilimumab. Lower levels of S100B, and LDH at baseline and at weeks 3 and 6 correlated to a better response and survival. After multivariate analysis LDH maintained its independence at baseline and week 6, whereas S100B might be a useful tool for anti-CTLA-4 treatment monitoring after the first two doses of ipilimumab (W6). In addition, higher sMICA serum levels at baseline were associated with less frequency of irAEs.

The full blood count as a biomarker of outcome and toxicity in ipilimumab-treated cutaneous metastatic melanoma

Ipilimumab produces durable responses in some metastatic melanoma patients. Neutrophil, platelet, and eosinophil to lymphocyte ratios (NLR, PLR, and ELR) may be associated with the immune response in cancer thereby acting as biomarkers of toxicity and efficacy in ipilimumab-treated patients. Data were collected on clinical characteristics and lactate dehydrogenase (LDH), NLR, PLR, and ELR at baseline, post cycle 2 and at the end of treatment for 183 patients treated with ipilimumab between 2008 and 2015 at the Princess Margaret Cancer Centre. Associations between clinical characteristics, LDH, NLR, PLR, and ELR with toxicity or survival outcomes of progression-free (PFS) and overall survival (OS) were assessed using univariable and multivariable analysis. Prognostic models of outcome at each time point were determined. Of the 183 patients included, the median age was 58, 85% had M1c disease, 58% were performance status 1, and 64% received ipilimumab as second line therapy. Median follow up was 7.5 months (range: 0.3-49.5), median PFS was 2.8 months (95% confidence intervals (CI): 2.8-3.2), and median OS was 9.6 months (95% CI: 7.9-13.2). Prognostic factors for OS by multivariable analysis were LDH and NLR at all-time points. Prognostic models using LDH (× 2 upper limit of normal) and NLR 4) differentiated patients into high, moderate, and low risk of death prior to or on ipilimumab treatment (P < 0.0001 for each model). No factors were associated with toxicity. Prognostic models based on NLR and LDH values at baseline and on treatment differentiate patients into good, intermediate, and poor prognostic groups and may be relevant in patient management.

Emerging Tissue and Blood-Based Biomarkers that may Predict Response to Immune Checkpoint Inhibition

The immune system plays an essential role in the surveillance and eradication of neoplastic cells. This interaction is modulated via immunologic regulators (checkpoints). Antibodies that block the checkpoints cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), and the programmed cell death protein 1 pathway (PD1/PD-L1) have demonstrated efficacy in a number of malignancies. However, response rates are variable, and administration of these antibodies can be associated with immune-related adverse events. Therefore, researchers are engaged in an effort to discover biomarkers that may predict response to these agents. This review focuses on potential blood and tumor-based biomarkers that have been assessed in patients treated with these checkpoint-blocking antibodies.

Immunotherapy for advanced melanoma: future directions

As calculated by the meta-analysis of Korn et al., the prognosis of metastatic melanoma in the pretarget and immunological therapy era was poor, with a median survival of 6.2 and a 1-year life expectancy of 25.5%. Nowadays, significant advances in melanoma treatment have been gained, and immunotherapy is one of the promising approaches to get to durable responses and survival improvement. The aim of the present review is to highlight the recent innovations in melanoma immunotherapy and to propose a critical perspective of the future directions of this enthralling oncology subspecialty.

Baseline Peripheral Blood Biomarkers Associated with Clinical Outcome of Advanced Melanoma Patients Treated with Ipilimumab

PURPOSE

To identify baseline peripheral blood biomarkers associated with clinical outcome following ipilimumab treatment in advanced melanoma patients.

EXPERIMENTAL DESIGN

Frequencies of myeloid-derived suppressor cells (MDSC) and regulatory T cells (Treg), serum lactate dehydrogenase (LDH), routine blood counts, and clinical characteristics were assessed in 209 patients. Endpoints were overall survival (OS) and best overall response. Statistical calculations were done by Kaplan-Meier and Cox regression analysis, including calibration and discrimination by C-statistics.

RESULTS

Low baseline LDH, absolute monocyte counts (AMC), Lin(-)CD14(+)HLA-DR(-/low)-MDSC frequencies, and high absolute eosinophil counts (AEC), relative lymphocyte counts (RLC), and CD4(+)CD25(+)FoxP3(+)-Treg frequencies were significantly associated with better survival, and were considered in a combination model. Patients (43.5%) presenting with the best biomarker signature had a 30% response rate and median survival of 16 months. In contrast, patients with the worst biomarkers (27.5%) had only a 3% response rate and median survival of 4 months. The occurrence of adverse events correlated with neither baseline biomarker signatures nor the clinical benefit of ipilimumab. In another model, limited to the routine parameters LDH, AMC, AEC, and RLC, the number of favorable factors (4 vs. 3 vs. 2-0) was also associated with OS (P < 0.001 for all pairwise comparisons) in the main study and additionally in an independent validation cohort.

CONCLUSIONS

A baseline signature of low LDH, AMC, and MDSCs as well as high AEC, Tregs, and RLC is associated with favorable outcome following ipilimumab. Prospective investigation of the predictive impact of these markers following ipilimumab and other treatments, e.g., PD-1 antibodies, is warranted. Clin Cancer Res; 22(12); 2908-18. ©2016 AACR.