Obesity and immune-checkpoint inhibitors in advanced melanoma: A meta-analysis of survival outcomes from clinical studies

Clinical Outcomes of Immune Checkpoint Inhibitors in Unique Cohorts Underrepresented in Clinical Trials

Regulatory approval of immune checkpoint inhibitors (ICIs) was based on results of large, randomized clinical trials, resulting in limited outcomes data in patient cohorts typically underrepresented in such trials. The objective of this study was to evaluate the efficacy and safety of ICIs in these unique patient cohorts. This is a multicenter, retrospective analysis of real-world data at six academic and community clinics in the United States from 1 January 2011 to 1 April 2018. Patients were included if they had received at least one cycle of ICI treatment. Unique patient cohorts included age > 75 years, non-White race, positive smoking history, ECOG performance status (PS) ≥ 2, BMI ≥ 30 kg/m2, autoimmune diseases (AIDs), chronic viral infections (CVI), extensive prior lines of therapy (LOTs), or >three metastatic sites. Immune-related adverse events (irAEs), overall survival (OS), and time to treatment failure were evaluated in the entire cohort and in NSCLC patients treated with PD-(L)1 monotherapy. Outcomes and their association with unique patient cohorts were compared on univariate analysis and multivariate analysis to those without a particular characteristic in the entire NSCLC PD-(L)1 monotherapy cohorts. In total, 1453 patients were included: 56.5%-smokers, 30.4%-non-White, 22.8%-elderly, 20.8%-ECOG PS ≥ 2, 15.7%-history of AIDs, and 4.7%-history of CVI. The common ICIs were nivolumab (37.1%) and pembrolizumab (22.2%). Black patients, compared to White patients, experienced fewer irAEs (OR 0.54, p < 0.001). An ECOG PS of ≥2 (HR = 2.01, p < 0.001) and an increased number of previous LOTs were associated with poor OS (the median OS of 26.2 vs. 16.2 vs. 9.6 months for one vs. two vs. three prior LOTs, p < 0.001). The above results were confirmed in anti-PD-(L)1 monotherapy non-small cell lung cancer patients (n = 384). Overall, ICIs were safe and efficacious in these typically underrepresented patient cohorts. We noted ECOG PS ≥ 2 and an increased prior LOTs were associated with poor ICI efficacy, and Black patients, compared to White patients, experienced fewer irAEs.

The Effect of Body Mass Index on Melanoma Biology, Immunotherapy Efficacy, and Clinical Outcomes: A Narrative Review

Recent studies indicate that a higher body mass index (BMI) might correlate with improved responses to melanoma treatment, especially with immune checkpoint inhibitors (ICIs), despite the general association of obesity with an increased risk of cancer and higher mortality rates. This review examines the paradoxical relationship between BMI and clinical outcomes in melanoma patients by exploring molecular links, the efficacy of immunotherapy, and patient survival outcomes. Our comprehensive literature search across the PubMed and Embase databases revealed a consistent pattern: increased BMI is associated with a better prognosis in melanoma patients undergoing ICI treatment. This "obesity paradox" might be explained by the metabolic and immunological changes in obesity, which could enhance the effectiveness of immunotherapy in treating melanoma. The findings highlight the complexity of the interactions between obesity and melanoma, suggesting that adipose tissue may modulate the immune response and treatment sensitivity favorably. Our review highlights the need for personalized treatment strategies that consider the metabolic profiles of patients and calls for further research to validate BMI as a prognostic factor in clinical settings. This nuanced approach to the obesity paradox in melanoma could significantly impact treatment planning and patient management.

Effect of body mass index and cholesterol-rich apolipoprotein-B-containing lipoproteins on clinical outcome in NSCLC patients treated with immune checkpoint inhibitors-based therapy: A retrospective analysis

OBJECTIVES

Obesity and hypercholesterolemia are linked to unfavor clinical outcomes. Recent studies declared the paradox that high body mass index (BMI) and serum cholesterol were independently connected to better clinical outcome of immune checkpoint inhibitors (ICIs) monotherapy in non-small cell lung cancer (NSCLC). The aim of the study is to investigate the prognosis of BMI and serum cholesterol in ICIs-based therapy.

METHODS

This is a retrospective study of 95 NSCLC patients treated with ICIs-based therapy at the Department of Oncology and Lung Cancer Center of China-Japan Friendship Hospital. Treatment efficacy was assessed using durable clinical benefit (DCB) versus nondurable benefit (NDB), best response (active vs. nonactive), and progression-free survival (PFS). The prognostic value of BMI, LDL-C, and RC was determined by multivariate regression analyses, while controlling for confounding factors including age, gender, diabetes status, smoking history, and statin usage. BMI was considered a confounding factor in the analysis when examining the impact of lipoproteins.

RESULTS

In our study, we found that in the whole group, BMI ≥25 kg/m2 was linked to a higher risk of poor therapeutic response (OR = 5.92, 95% CI 1.99-19.51, p.val = 0.002) and shorter progression-free survival (HR = 3.00, 95% CI 1.59-5.68, p.val = 0.001). In addition, low levels of RC were associated with better therapeutic response (OR = 0.12, 95% CI 0.02-0.64, p.val = 0.019), while low levels of serum LDL-C were found to predict longer PFS (HR = 0.40, 95% CI 0.19-0.82, p.val = 0.012). These associations were consistent in advanced NSCLC patients receiving ICIs and chemotherapy.

CONCLUSIONS

Our study suggest that BMI ≥25 kg/m2 and elevated levels of apoB-containing lipoproteins, including LDL-C and RC, could potentially serve as useful prognostic markers for predicting poor treatment outcomes in advanced NSCLC patients treated with the combination of chemotherapy and ICIs.

Potential roles of sex-linked differences in obesity and cancer immunotherapy: revisiting the obesity paradox

Obesity, a condition of excess adiposity usually defined by a BMI > 30, can have profound effects on both metabolism and immunity, connecting the condition with a broad range of diseases, including cancer and negative outcomes. Obesity and cancer have been associated with increased incidence, progression, and poorer outcomes of multiple cancer types in part due to the pro-inflammatory state that arises. Surprisingly, obesity has also recently been demonstrated in both preclinical models and clinical outcomes to be associated with improved response to immune checkpoint inhibition (ICI). These observations have laid the foundation for what has been termed the "obesity paradox". The mechanisms underlying these augmented immunotherapy responses are still unclear given the pleiotropic effects obesity exerts on cells and tissues. Other important variables such as age and sex are being examined as further affecting the obesity effect. Sex-linked factors exert significant influences on obesity biology, metabolism as well as differential effects of different immune cell-types. Age can be another confounding factor contributing to the effects on both sex-linked changes, immune status, and obesity. This review aims to revisit the current body of literature describing the immune and metabolic changes mediated by obesity, the role of obesity on cancer immunotherapy, and to highlight questions on how sex-linked differences may influence obesity and immunotherapy outcome.

Decision model for durable clinical benefit from front- or late-line immunotherapy alone or with chemotherapy in non-small cell lung cancer

BACKGROUND

Predictive biomarkers and models of immune checkpoint inhibitors (ICIs) have been extensively studied in non-small cell lung cancer (NSCLC). However, evidence for many biomarkers remains inconclusive, and the opaqueness of machine learning models hinders practicality. We aimed to provide compelling evidence for biomarkers and develop a transparent decision tree model.

METHODS

We consolidated data from 3,288 ICI-treated patients with NSCLC across real-world multicenter, public cohorts and the Choice-01 trial (ClinicalTrials.gov: NCT03856411). Over 50 features were examined for predicting durable clinical benefits (DCBs) from ICIs. Noteworthy biomarkers were identified to establish a decision tree model. Additionally, we explored the tumor microenvironment and peripheral CD8+ programmed death-1 (PD-1)+ T cell receptor (TCR) profiles.

FINDINGS

Multivariate logistic regression analysis identified tumor histology, PD-ligand 1 (PD-L1) expression, tumor mutational burden, line, and regimen of ICI treatment as significant factors. Mutation subtypes of EGFR, KRAS, KEAP1, STK11, and disruptive TP53 mutations were associated with DCB. The decision tree (DT10) model, using the ten clinicopathological and genomic markers, showed superior performance in predicting DCB in the training set (area under the curve [AUC] = 0.82) and consistently outperformed other models in test sets. DT10-predicted-DCB patients manifested longer survival, an enriched inflamed tumor immune phenotype (67%), and higher peripheral TCR diversity, whereas the DT10-predicted-NDB (non-durable benefit) group showed an enriched desert immune phenotype (86%) and higher peripheral TCR clonality.

CONCLUSIONS

The model effectively predicted DCB after front-/subsequent-line ICI treatment, with or without chemotherapy, for squamous and non-squamous lung cancer, offering clinicians valuable insights into efficacy prediction using cost-effective variables.

FUNDING

This study was supported by the National Key R&D Program of China.

Prognostic biomarkers in melanoma: a 2023 update from clinical trials in different therapeutic scenarios

INTRODUCTION

Over the past decade, significant advancements in the field of melanoma have included the introduction of a new staging system and the development of immunotherapy and targeted therapies, leading to changes in substage classification and impacting patient prognosis. Despite these strides, early detection remains paramount. The quest for dependable prognostic biomarkers is ongoing, given melanoma's unpredictable nature, especially in identifying patients at risk of relapse. Reliable biomarkers are critical for informed treatment decisions.

AREAS COVERED

This review offers a comprehensive review of prognostic biomarkers in the context of clinical trials for immunotherapy and targeted therapy. It explores different clinical scenarios, including adjuvant, metastatic, and neo-adjuvant settings. Key findings suggest that tumor mutational burden, PD-L1 expression, IFN-γ signature, and immune-related factors are promising biomarkers associated with improved treatment responses.

EXPERT OPINION

Identifying practical prognostic factors for melanoma therapy is challenging due to the tumor's heterogeneity. Promising biomarkers include tumor mutational burden (TMB), circulating tumor DNA, and those characterizing the tumor microenvironment, especially the immune component. Future research should prioritize large-scale, prospective studies to validate and standardize these biomarkers, emphasizing clinical relevance and real-world applicability. Easily accessible biomarkers have the potential to enhance the precision and effectiveness of melanoma management.

Advances in the pharmacological management of cutaneous T-cell lymphoma

INTRODUCTION

Current treatment guidelines for cutaneous T cell lymphoma (CTCL) advocate a stage-driven approach, considering clinical presentation, symptom burden, and patient comorbidities. Therapy selection hinges on factors like disease subtype, severity, and treatment availability. The primary goal is to enhance the quality of life by mitigating symptoms, as achieving lasting complete remission is infrequent.

AREAS COVERED

Over the past decade (2013-2023), the therapeutic landscape of CTCL has experienced substantial transformation with the introduction of innovative therapies. This review explores the main pivotal developments in traditional treatment schedules and recently introduced drugs, aiming to offer clinicians and researchers a thorough perspective on the decade's progress in the field.

EXPERT OPINION

Despite the progress made in CTCL therapeutics, ranging from topical chemotherapeutics to immunomodulatory agents, several unmet needs persist. Firstly, there is a pressing need for the incorporation of readily available predictors for treatment response, encompassing clinical, pathological, and molecular features. Secondly, a more profound comprehension of the tumor microenvironment is imperative to optimize the landscape of targetable molecules. Lastly, the undertaking of studies on combination regimens should be encouraged as it enhances therapy efficacies by synergistically combining agents with diverse modes of action.

Impact of body mass index on the prognosis of unresectable HCC patients receiving first-line Lenvatinib or atezolizumab plus bevacizumab

INTRODUCTION

Overweight is a negative prognostic factor in the general population in the long term. However, the role of body mass index (BMI) in the short-mid term in advanced tumours is unclear. The present analysis investigates the role of BMI weight classes in a large sample of patients affected by HCC and receiving atezolizumab plus bevacizumab or lenvatinib as first-line treatment.

METHODS AND MATERIAL

The cohort included consecutive patients affected by BCLC-c and BCLC-B HCC patients from a multicenter international study group who received atezolizumab plus bevacizumab or lenvatinib as first-line therapy. Population was stratified according to the BMI in under-, over- and normal-weight according to the conventional thresholds. The primary objective of the study was to evaluate the prognostic and predictive impact of BMI in patients affected by advanced or intermediate HCC. Survival curves were estimated using the product-limit method of Kaplan-Meier. The role of stratification factors was analysed with log-rank tests.

RESULTS

1292 consecutive patients with HCC were analysed. 466 (36%) patients were treated with lenvatinib and 826 (64%) patients were treated with atezolizumab plus bevacizumab. In the atezolizumab plus bevacizumab arm, 510 (62%) patients were normal-weight, 52 (6%) underweight and 264 (32%) overweight. At the univariate analysis for OS, underweight patients had significantly shorter OS compared to normal-weight patients, whereas no differences were found between normal-weight versus overweight. Multivariate analysis confirmed that underweight patients had significantly shorter OS compared to normal-weight patients (HR: 1.7; 95% CI: 1.0-2.8; p = .0323). In the lenvatinib arm, 26 patients (5.6%) were categorized as underweight, 256 (54.9%) as normal-weight, and 184 (39.5%) as overweight. At the univariate analysis for OS, no significant differences were found between normal-weight versus underweight and between normal-weight versus overweight, which was confirmed at multivariate analysis.

CONCLUSION

Our analysis highlighted a prognostic role of BMI in a cohort of patients with advanced HCC who received atezolizumab plus bevacizumab, while no prognostic role for low BMI was apparent in patients who received lenvatinib.

Immunotherapy in cutaneous melanoma and biologics in psoriatic disease: similarities and differences from a clinical multidisciplinary perspective

INTRODUCTION

Immunomodulating therapies harness the power of the immune system to combat disease. In advanced melanoma, immune checkpoint inhibitors have significantly improved survival outcomes by activating the immune system to recognize and eliminate cancer cells. In psoriasis, interleukin inhibitors effectively suppress inflammation and improve disease symptoms.

AREAS COVERED

We provide a meta-opinion-based consensus paper on the analogies and differences in treatment mechanisms, duration, frequency between immunotherapy for advanced melanoma and biologics for psoriasis. Combining the current scientific evidence with expert insights, we provide valuable guidance for future research and decision-making processes.

EXPERT OPINION

The development of immunological treatments in melanoma and psoriasis has revolutionized dermatology, but the quest for tailored therapies that maximize efficacy continues. Managing cutaneous exacerbations during melanoma immunotherapy in psoriatic patients remains challenging. Similarly, treating oncologic psoriasis patients resistant to traditional therapies requires individualized approaches. Research is needed to identify response predictors in both conditions and address the sustainability of healthcare systems due to the high cost of biologics. Drug delay studies for psoriasis and longer follow-up evaluations after immunotherapy discontinuation in melanoma are essential for optimizing treatment outcomes and resource allocation.

A Narrative Review of Current Knowledge on Cutaneous Melanoma

Cutaneous melanoma is a public health problem. Efforts to reduce its incidence have failed, as it continues to increase. In recent years, many risk factors have been identified. Numerous diagnostic systems exist that greatly assist in early clinical diagnosis. The histopathological aspect illustrates the grim nature of these cancers. Currently, pathogenic pathways and the tumor microclimate are key to the development of therapeutic methods. Revolutionary therapies like targeted therapy and immune checkpoint inhibitors are starting to replace traditional therapeutic methods. Targeted therapy aims at a specific molecule in the pathogenic chain to block it, stopping cell growth and dissemination. The main function of immune checkpoint inhibitors is to boost cellular immunity in order to combat cancer cells. Unfortunately, these therapies have different rates of effectiveness and side effects, and cannot be applied to all patients. These shortcomings are the basis of increased incidence and mortality rates. This study covers all stages of the evolutionary sequence of melanoma. With all these data in front of us, we see the need for new research efforts directed at therapies that will bring greater benefits in terms of patient survival and prognosis, with fewer adverse effects.

Obesity and lung cancer - is programmed death ligand-1 (PD-1L) expression a connection?

Introduction

In this retrospective study, the authors evaluated whether obesity-induced immunomodulation impacts the expression of programmed death ligand-1 (PD-1L) in lung cancer cells.Methods: A retrospective cross-sectional study was performed. The study included 67 patients. The data did not have a normal distribution.

Results

For women, using ANOVA test (p = 0.050) with post-hoc analysis, a statistically significant difference in expression was found between women with overweight and women with normal weight (p = 0.040).

Conclusions

Apart from the above, the authors did not find any statistically significant correlation between PD-1L expression on lung cancer cells and body mass index, either in the whole group or in histological subgroups.

Breaking the mold: Overcoming resistance to immune checkpoint inhibitors

Immune checkpoint blockade-based therapies are effective against a sorts of cancers. However, drug resistance is a problem that cannot be ignored. This review intends to elucidate the mechanisms underlying drug tolerance induced by PD-1/PD-L1 inhibitors, as well as to outline proposed mechanism-based combination therapies and small molecule drugs that target intrinsic immunity and immune checkpoints. According to the differences of patients and types of cancer, the optimization of individualized combination therapy will help to enhance PD-1/PD-L1-mediated immunoregulation, reduce chemotherapy resistance, and provide new ideas for chemotherapy-resistant cancer.

Multifaceted effects of obesity on cancer immunotherapies: Bridging preclinical models and clinical data

Obesity, defined by excessive body fat, is a highly complex condition affecting numerous physiological processes, such as metabolism, proliferation, and cellular homeostasis. These multifaceted effects impact cells and tissues throughout the host, including immune cells as well as cancer biology. Because of the multifaceted nature of obesity, common parameters used to define it (such as body mass index in humans) can be problematic, and more nuanced methods are needed to characterize the pleiotropic metabolic effects of obesity. Obesity is well-accepted as an overall negative prognostic factor for cancer incidence, progression, and outcome. This is in part due to the meta-inflammatory and immunosuppressive effects of obesity. Immunotherapy is increasingly used in cancer therapy, and there are many different types of immunotherapy approaches. The effects of obesity on immunotherapy have only recently been studied with the demonstration of an "obesity paradox", in which some immune therapies have been demonstrated to result in greater efficacy in obese subjects despite the direct adverse effects of obesity and excess body fat acting on the cancer itself. The multifactorial characteristics that influence the effects of obesity (age, sex, lean muscle mass, underlying metabolic conditions and drugs) further confound interpretation of clinical data and necessitate the use of more relevant preclinical models mirroring these variables in the human scenario. Such models will allow for more nuanced mechanistic assessment of how obesity can impact, both positively and negatively, cancer biology, host metabolism, immune regulation, and how these intersecting processes impact the delivery and outcome of cancer immunotherapy.

Utility of 18F-FDG uptake in predicting major pathological response to neoadjuvant immunotherapy in patients with resectable non‑small cell lung cancer

PURPOSE

The aim of present study was to investigate the efficiency of ¹⁸F-FDG uptake in predicting major pathological response (MPR) in resectable non-small cell lung cancer (NSCLC) patients with neoadjuvant immunotherapy.

METHODS

A total of 104 patients with stage I-IIIB NSCLC were retrospectively derived from National Cancer Center of China, of which 36 cases received immune checkpoint inhibitors (ICIs) monotherapy (I-M) and 68 cases with ICI combination therapy (I-C). ¹⁸F-FDG PET-CT scans were performed at baseline and after neoadjuvant therapy (NAT). Receiver-operating characteristic (ROC) curve analyses were conducted and area under ROC curve (AUC) was calculated for biomarkers including maximum standardized uptake value (SUVmax), inflammatory biomarkers, tumor mutation burden (TMB), PD-L1 tumor proportion score (TPS) and iRECIST.

RESULTS

Fifty-four resected NSCLC tumors achieved MPR (51.9%, 54/104). In both neoadjuvant I-M and I-C cohorts, post-NAT SUVmax and the percentage changes of SUVmax (ΔSUVmax%) were significantly lower in the patients with MPR versus non-MPR (p < 0.01), and were also negatively correlated with the degree of pathological regression (p < 0.01). The AUC of ΔSUVmax% for predicting MPR was respectively 1.00 (95% CI: 1.00-1.00) in neoadjuvant I-M cohort and 0.94 (95% CI: 0.86-1.00) in I-C cohort. Baseline SUVmax had a statistical prediction value for MPR only in I-M cohort, with an AUC up to 0.76 at the threshold of 17.0. ΔSUVmax% showed an obvious advantage in MPR prediction over inflammatory biomarkers, TMB, PD-L1 TPS and iRECIST.

CONCLUSION

¹⁸F-FDG uptake can predict MPR in NSCLC patients with neoadjuvant immunotherapy.