Mechanistic insight of predictive biomarkers for antitumor PD‑1/PD‑L1 blockade: A paradigm shift towards immunome evaluation (Review)

Recent advances in biomarkers for predicting the efficacy of immunotherapy in non-small cell lung cancer

Lung cancer continues to be the primary cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all instances. Recently, immune checkpoint inhibitors (ICIs) have transformed the treatment approach for NSCLC, however, only a subset of patients experiences significant benefits. Therefore, identifying reliable biomarkers to forecast the efficacy of ICIs is crucial for ensuring the safety and effectiveness of treatments, becoming a major focus of current research efforts. This review highlights the recent advances in predictive biomarkers for the efficacy of ICIs in the treatment of NSCLC, including PD-L1 expression, tertiary lymphoid structures (TLS), tumor-infiltrating lymphocytes (TILs), tumor genomic alterations, transcriptional signatures, circulating biomarkers, and the microbiome. Furthermore, it underscores the pivotal roles of liquid biopsy, sequencing technologies, and digital pathology in biomarker discovery. Special attention is given to the predictive value of TLS, circulating biomarkers, and transcriptional signatures. The review concludes that the integration of multiple biomarkers holds promise for achieving more accurate efficacy predictions and optimizing personalized immunotherapy strategies. By providing a comprehensive overview of the current progress, this review offers valuable insights into biomarker-based precision medicine for NSCLC and outlines future research directions.

A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center study

BACKGROUND

To construct and assess a deep learning (DL) signature that employs computed tomography imaging to predict the expression status of programmed cell death ligand 1 in patients with bladder cancer (BCa).

METHODS

This retrospective study included 190 patients from two hospitals who underwent surgical removal of BCa (training set/external validation set, 127/63). We used convolutional neural network and radiomics machine learning technology to generate prediction models. We then compared the performance of the DL signature with the radiomics machine learning signature and selected the optimal signature to build a nomogram with the clinical model. Finally, the internal forecasting process of the DL signature was explained using Shapley additive explanation technology.

RESULTS

On the external validation set, the DL signature had an area under the curve of 0.857 (95% confidence interval: 0.745-0.932), and demonstrated superior prediction performance in comparison with the other models. SHAP expression images revealed that the prediction of PD-L1 expression status is mainly influenced by the tumor edge region, particularly the area close to the bladder wall.

CONCLUSIONS

The DL signature performed well in comparison with other models and proved to be a valuable, dependable, and interpretable tool for predicting programmed cell death ligand 1 expression status in patients with BCa.

Understanding the role of TNFR2 signaling in the tumor microenvironment of breast cancer

Breast cancer (BC) is the most frequently diagnosed malignancy among women. It is characterized by a high level of heterogeneity that emerges from the interaction of several cellular and soluble components in the tumor microenvironment (TME), such as cytokines, tumor cells and tumor-associated immune cells. Tumor necrosis factor (TNF) receptor 2 (TNFR2) appears to play a significant role in microenvironmental regulation, tumor progression, immune evasion, drug resistance, and metastasis of many types of cancer, including BC. However, the significance of TNFR2 in BC biology is not fully understood. This review provides an overview of TNFR2 biology, detailing its activation and its interactions with important signaling pathways in the TME (e.g., NF-κB, MAPK, and PI3K/Akt pathways). We discuss potential therapeutic strategies targeting TNFR2, with the aim of enhancing the antitumor immune response to BC. This review provides insights into role of TNFR2 as a major immune checkpoint for the future treatment of patients with BC.

CT Image-Based Radiomic Analysis for Detecting PD-L1 Expression Status in Bladder Cancer Patients

RATIONALE AND OBJECTIVES

The role of Programmed death-ligand 1 (PD-L1) expression is crucial in guiding immunotherapy selection. This study aims to develop and evaluate a radiomic model, leveraging Computed Tomography (CT) imaging, with the objective of predicting PD-L1 expression status in patients afflicted with bladder cancer.

MATERIALS AND METHODS

The study encompassed 183 subjects diagnosed with histologically confirmed bladder cancer, among which the PD-L1(+) cohort constituted 60.1% of the total population. Stratified random sampling was utilized at a 7:3 ratio. We employed five diverse machine learning algorithms-Decision Tree, Random Forest, Linear Support Vector Classification, Support Vector Machine, and Logistic Regression-to establish radiomic models on the training dataset. These models endeavored to predict PD-L1 expression status premised on radiomic features derived from region-of-interest segmentation. Subsequent to this, the predictive performance of these models was examined on a validation set employing the receiver operating characteristic (ROC) curve. The DeLong test was utilized to contrast ROC curves, thereby pinpointing the model with superior predictive accuracy.

RESULTS

16 features were chosen for the model construction. All five models revealed strong performance in the training set (AUC, 0.920-1) and commendable predictive ability in the validation set (AUC, 0.753-0.766). As per the DeLong test, no statistically significant disparities were observed among any of the models (P > 0.05) in the validation set. Additional verification through the calibration curve and decision curve analysis indicated that the Logistic Regression model exhibited extraordinary precision and practicality.

CONCLUSION

Our machine learning model, grounded on radiomic features, demonstrated its proficiency in accurately distinguishing bladder cancer patients with high PD-L1 expression. Future research, incorporating more exhaustive datasets, could potentially augment the predictive efficiency of radiomic algorithms, thereby advancing their clinical utility.

Reprogramming the Intrahepatic Cholangiocarcinoma Immune Microenvironment by Chemotherapy and CTLA-4 Blockade Enhances Anti-PD-1 Therapy

Intrahepatic cholangiocarcinoma (ICC) has limited therapeutic options and a dismal prognosis. Adding blockade of the anti-programmed cell death protein (PD)-1 pathway to gemcitabine/cisplatin chemotherapy has recently shown efficacy in biliary tract cancers but with low response rates. Here, we studied the effects of anti-cytotoxic T lymphocyte antigen (CTLA)-4 when combined with anti-PD-1 and gemcitabine/cisplatin in orthotopic murine models of ICC. This combination therapy led to substantial survival benefits and reduction of morbidity in two aggressive ICC models that were resistant to immunotherapy alone. Gemcitabine/cisplatin treatment increased tumor-infiltrating lymphocytes and normalized the ICC vessels and, when combined with dual CTLA-4/PD-1 blockade, increased the number of activated CD8+Cxcr3+IFNγ+ T cells. CD8+ T cells were necessary for the therapeutic benefit because the efficacy was compromised when CD8+ T cells were depleted. Expression of Cxcr3 on CD8+ T cells is necessary and sufficient because CD8+ T cells from Cxcr3+/+ but not Cxcr3-/- mice rescued efficacy in T cell‒deficient mice. Finally, rational scheduling of anti-CTLA-4 "priming" with chemotherapy followed by anti-PD-1 therapy achieved equivalent efficacy with reduced overall drug exposure. These data suggest that this combination approach should be clinically tested to overcome resistance to current therapies in ICC patients.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

Five years after PACIFIC: update on multimodal treatment efficacy based on real-world reports

INTRODUCTION

The growing body of real-life data on maintenance treatment with durvalumab suggests that immunological markers of the cancer host interplay may have significant effects on the efficacy of multimodal therapy in patients with unresectable stage III NSCLC.

AREAS COVERED

We summarize real-world clinical data regarding this new tri-modal approach and report on potential biomarker landscape.

EXPERT OPINION

The obvious question posed in this context of a very heterogeneous inoperable stage III NSCLC disease is: How can we augment an ability to predict checkpoint inhibition success or failure? Which tools and biomarkers, which clinical metadata and genetic background are relevant and feasible? No single biomarker will ever fully dominate the unresectable stage III NSCLC space, so we advocate multilevel and multivariate analysis of biomarkers. In this particular opinion piece, we explore the impact of PD-L1 expression on tumor cells, neutrophil-to-lymphocyte ratio, EGFR and STK11 mutational status, interferon-gamma signature, and tumor-infiltrating lymphocytes among others.

Reprogramming Intrahepatic Cholangiocarcinoma Immune Microenvironment by Chemotherapy and CTLA-4 Blockade Enhances Anti-PD1 Therapy

Intrahepatic cholangiocarcinoma (ICC) has limited therapeutic options and a dismal prognosis. Anti-PD-L1 immunotherapy combined with gemcitabine/cisplatin chemotherapy has recently shown efficacy in biliary tract cancers, but responses are seen only in a minority of patients. Here, we studied the roles of anti-PD1 and anti-CTLA-4 immune checkpoint blockade (ICB) therapies when combined with gemcitabine/cisplatin and the mechanisms of treatment benefit in orthotopic murine ICC models. We evaluated the effects of the combined treatments on ICC vasculature and immune microenvironment using flow cytometry analysis, immunofluorescence, imaging mass cytometry, RNA-sequencing, qPCR, and in vivo T-cell depletion and CD8+ T-cell transfer using orthotopic ICC models and transgenic mice. Combining gemcitabine/cisplatin with anti-PD1 and anti-CTLA-4 antibodies led to substantial survival benefits and reduction of morbidity in two aggressive ICC models, which were ICB-resistant. Gemcitabine/cisplatin treatment increased the frequency of tumor-infiltrating lymphocytes and normalized the ICC vessels, and when combined with dual CTLA-4/PD1 blockade, increased the number of activated CD8+Cxcr3+IFN-γ+ T-cells. Depletion of CD8+ but not CD4+ T-cells compromised efficacy. Conversely, CD8+ T-cell transfer from Cxcr3-/- versus Cxcr3+/+ mice into Rag1-/- immunodeficient mice restored the anti-tumor effect of gemcitabine/cisplatin/ICB combination therapy. Finally, rational scheduling of the ICBs (anti-CTLA-4 "priming") with chemotherapy and anti-PD1 therapy achieved equivalent efficacy with continuous dosing while reducing overall drug exposure. In summary, gemcitabine/cisplatin chemotherapy normalizes vessel structure, increases activated T-cell infiltration, and enhances anti-PD1/CTLA-4 immunotherapy efficacy in aggressive murine ICC. This combination approach should be clinically tested to overcome resistance to current therapies in ICC patients.

Quantifying the contribution of transcription factor activity, mutations and microRNAs to CD274 expression in cancer patients

Immune checkpoint inhibitors targeting the programmed cell death protein 1 (PD-1)/programmed cell death protein ligand 1 (PD-L1) axis have been remarkably successful in inducing tumor remissions in several human cancers, yet a substantial number of patients do not respond to treatment. Because this may be partially due to the mechanisms giving rise to high PD-L1 expression within a patient, it is highly relevant to fully understand these mechanisms. In this study, we conduct a bioinformatic analysis to quantify the relative importance of transcription factor (TF) activity, microRNAs (miRNAs) and mutations in determining PD-L1 (CD274) expression at mRNA level based on data from the Cancer Genome Atlas. To predict individual CD274 levels based on TF activity, we developed multiple linear regression models by taking the expression of target genes of the TFs known to directly target PD-L1 as independent variables. This analysis showed that IRF1, STAT1, NFKB and BRD4 are the most important regulators of CD274 expression, explaining its mRNA levels in 90–98% of the patients. Because the remaining patients had high CD274 levels independent of these TFs, we next investigated whether mutations associated with increased CD274 mRNA levels, and low levels of miRNAs associated with negative regulation of CD274 expression could cause high CD274 levels in these patients. We found that mutations or miRNAs offered an explanation for high CD274 levels in 81–100% of the underpredicted patients. Thus, CD274 expression is largely explained by TF activity, and the remaining unexplained cases can largely be explained by mutations or low miRNA abundance.

Immunotherapy and Vaccination in Surgically Resectable Non-Small Cell Lung Cancer (NSCLC)

Early-stage NSCLC (stages I and II, and some IIIA diseases) accounts for approximately 30% of non-small cell lung cancer (NSCLC) cases, with surgery being its main treatment modality. The risk of disease recurrence and cancer-related death, however, remains high among NSCLC patients after complete surgical resection. In previous studies on the long-term follow-up of post-operative NSCLC, the results showed that the five-year survival rate was about 65% for stage IB and about 35% for stage IIIA diseases. Platinum-based chemotherapy with or without radiation therapy has been used as a neoadjuvant therapy or post-operative adjuvant therapy in NSCLC, but the improvement of survival is limited. Immune checkpoint inhibitors (ICIs) have effectively improved the 5-year survival of advanced NSCLC patients. Cancer vaccination has also been explored and used in the prevention of cancer or reducing disease recurrence in resected NSCLC. Here, we review studies that have focused on the use of immunotherapies (i.e., ICIs and vaccination) in surgically resectable NSCLC. We present the results of completed clinical trials that have used ICIs as neoadjuvant therapies in pre-operative NSCLC. Ongoing clinical trials investigating ICIs as neoadjuvant and adjuvant therapies are also summarized.

TGF-β inhibition can overcome cancer primary resistance to PD-1 blockade: A mathematical model

Immune checkpoint inhibitors have demonstrated, over the recent years, impressive clinical response in cancer patients, but some patients do not respond at all to checkpoint blockade, exhibiting primary resistance. Primary resistance to PD-1 blockade is reported to occur under conditions of immunosuppressive tumor environment, a condition caused by myeloid derived suppressor cells (MDSCs), and by T cells exclusion, due to increased level of T regulatory cells (Tregs). Since TGF-β activates Tregs, TGF-β inhibitor may overcome primary resistance to anti-PD-1. Indeed, recent mice experiments show that combining anti-PD-1 with anti-TGF-β yields significant therapeutic improvements compared to anti-TGF-β alone. The present paper introduces two cancer-specific parameters and, correspondingly, develops a mathematical model which explains how primary resistance to PD-1 blockade occurs, in terms of the two cancer-specific parameters, and how, in combination with anti-TGF-β, anti-PD-1 provides significant benefits. The model is represented by a system of partial differential equations and the simulations are in agreement with the recent mice experiments. In some cancer patients, treatment with anti-PD-1 results in rapid progression of the disease, known as hyperprogression disease (HPD). The mathematical model can also explain how this situation arises, and it predicts that HPD may be reversed by combining anti-TGF-β to anti-PD-1. The model is used to demonstrate how the two cancer-specific parameters may serve as biomarkers in predicting the efficacy of combination therapy with PD-1 and TGF-β inhibitors.

PD-L1 expression and immune cells in anaplastic carcinoma and poorly differentiated carcinoma of the human thyroid gland: A retrospective study

Anaplastic thyroid carcinoma (ATC) and poorly differentiated thyroid carcinoma (PDTC) have limited treatment options, and immune profiling may help select patients for immunotherapy. The prevalence and relevance of programmed death-1 ligand (PD-L1) expression and the presence of immune cells in ATC and PDTC has not yet been well established. The present study investigated PD-L1 expression (clone 22C3) and cells in the tumor microenvironment (TME), including tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs) and dendritic cells, in whole tissue sections of 15 cases of ATC and 13 cases of PDTC. Immunohistochemical PD-L1 expression using a tumor proportion score (TPS) with a 1% cut-off was detected in 9/15 (60%) of ATC cases and 1/13 (7.7%) of PDTC cases (P=0.006). PD-L1 expression in TILs was limited to the ATC group (73.3 vs. 0% in ATC and PDTC, respectively). In the ATC group, the TPS for tumor positive PD-L1 expression revealed a non-significant trend towards worse survival, but no difference was observed when investigating PD-L1 expression in TILs and TAMs. In addition to increased PD-L1 expression, all ATC cases exhibited significantly increased CD3⁺ and CD8⁺ T cells, CD68⁺ and CD163⁺ macrophages, and S100⁺ dendritic cells compared with the PDTC cases. Loss of mutL homolog 1 and PMS1 homolog 2 expression was observed in one ATC case with the highest PD-L1 expression, as well as in the only PDTC case positive for PD-L1. Notably, the latter was the only PDTC case exhibiting positivity for p53 and a cellular microenvironment similar to ATC. The current results indicated that PD-L1 expression was frequent in ATC, but rare in PDTC. In addition to PD-L1, the present study suggested that microsatellite instability may serve a role in both the TME and the identification of immunotherapy candidates among patients with PDTC.

Checkpoint Molecules in Rheumatology-or the Benefits of Being Exhausted

PURPOSE OF REVIEW

This review will focus on the most common co-inhibitory molecules, emphasizing the importance of these in relation to rheumatic disease.

RECENT FINDINGS

Checkpoint molecules are pivotal in determining the outcome of antigen activation. Checkpoint molecules consist of co-stimulatory and co-inhibitory molecules, where the first activates and the latter inhibits the antigen presentation process. Studies show that increased activity of co-inhibitory molecules is associated with a good prognosis in rheumatic diseases. Opposite, when cancer patients are treated with antibodies blocking the inhibitory pathways, autoimmune diseases, including arthritis, develop as immune-related adverse events (IrAE). This emphasizes the importance of these pathways in autoimmune disease. Co-inhibitory molecules are becoming increasingly interesting as future treatment targets in rheumatic conditions. Treatments with antibodies blocking these pathways result in IrAE, often manifesting as autoimmune rheumatic diseases. Therefore, a need to get acquainted with these molecules is growing so we can cope with future challenges in rheumatic diseases.

Advanced Melanoma: Resistance Mechanisms to Current Therapies

Novel therapeutic agents introduced over the past decade, including immune checkpoint inhibitors and targeted therapies, have revolutionized the management of metastatic melanoma and significantly improved patient outcomes. Although robust and durable responses have been noted in some cases, treatment is often limited by innate or acquired resistance to these agents. This article provides an overview of known and suspected mechanisms involved with acquired resistance to BRAF/MEK inhibitors as well as developing insights into innate and acquired resistance to checkpoint inhibitors in patients with melanoma.

Role of next generation sequencing-based liquid biopsy in advanced non-small cell lung cancer patients treated with immune checkpoint inhibitors: impact of STK11, KRAS and TP53 mutations and co-mutations on outcome

BACKGROUND

Characterization of tumor-related genetic alterations is promising for the screening of new predictive markers in non-small cell lung cancer (NSCLC). Aim of the study was to evaluate prognostic and predictive role of most frequent tumor-associated genetic alterations detected in plasma before starting immune checkpoint inhibitors (ICIs).

METHODS

Between January 2017 and October 2019, advanced NSCLC patients were prospectively screened with plasma next-generation sequencing (NGS) while included in two trials: VISION (NCT02864992), using Guardant360® test, and MAGIC (Monitoring Advanced NSCLC through plasma Genotyping during Immunotherapy: Clinical feasibility and application), using Myriapod NGS-IL 56G Assay. A control group of patients not receiving ICIs was analyzed.

RESULTS

A total of 103 patients receiving ICIs were analyzed: median overall survival (OS) was 20.8 (95% CI: 16.7-24.9) months and median immune-related progression free disease (irPFS) 4.2 (95% CI: 2.3-6.1) months. TP53 mutations in plasma negatively affected OS both in patients treated with ICIs and in control group (P=0.001 and P=0.009), indicating a prognostic role. STK11 mutated patients (n=9) showed a trend for worse OS only if treated with ICIs. The presence of KRAS/STK11 co-mutation and KRAS/STK11/TP53 co-mutation affected OS only in patients treated with ICIs (HR =10.936, 95% CI: 2.337-51.164, P=0.002; HR =17.609, 95% CI: 3.777-82.089, P<0.001, respectively), indicating a predictive role.

CONCLUSIONS

Plasma genotyping demonstrated prognostic value of TP53 mutations and predictive value of KRAS/STK11 and KRAS/STK11/TP53 co-mutations.

PD-L1 Expression in 65 Conjunctival Melanomas and Its Association with Clinical Outcome

Conjunctival melanoma (CM) iss a rare and aggressive tumour that is increasing in frequency. The prognostic value of PD-L1 expression, alone or in combination with CD8 and PD-1 expression and the BRAF and NRAS status, has not been determined in CM to date. We evaluated the expression of PD-L1, CD8, PD-1 in CM and investigated whether there was an association between the expression of these markers and the BRAF and NRAS molecular profile as well as some clinico-pathological criteria. A total of sixty-five CM were assessed for PD-L1, PD-1, and CD8 expression by immunohistochemistry (IHC) and for BRAF and NRAS genomic alterations using molecular biology techniques and anti-BRAF and anti-NRAS antibodies. PD-L1 expression in tumour cells (TC) was very low or absent but detected in tumour-infiltrating immune cells (IC). A correlation was observed between the expression of PD-L1, CD8, and PD-1 in IC. No correlation between PD-L1 expression (in tumour and/or immune cells) and BRAF or NRAS mutations was observed. PD-L1 expression in IC correlated with a higher pTNM stage and PD-L1 expression in TC with worse disease-specific survival. PD-L1 expression is a potential prognostic biomarker that correlates with poor prognosis in CM patients.

An Overview of Promising Biomarkers in Cancer Screening and Detection

Applications of biomarkers have been proved in oncology screening, diagnosis, predicting response to treatment as well as monitoring the progress of the disease. Considering the crucial role played by them during different disease stages, it is extremely important to evaluate, validate, and assess them to incorporate them into routine clinical care. In this review, the role of few most promising and successfully used biomarkers in cancer detection, i.e. PD-L1, E-Cadherin, TP53, Exosomes, cfDNA, EGFR, mTOR with regard to their structure, mode of action, and reports signifying their pathological significance, are addressed. Also, an overview of some successfully used biomarkers for cancer medicine has been presented. The study also summarizes biomarker-driven personalized cancer therapy i.e., approved targets and indications, as per the US FDA. The review also highlights the increasingly prominent role of biomarkers in drug development at all stages, with particular reference to clinical trials. The increasing utility of biomarkers in clinical trials is clearly evident from the trend shown, wherein ~55 percent of all oncology clinical trials in 2019 were seen to involve biomarkers, as opposed to ~ 15 percent in 2001, which clearly proves the essence and applicability of biomarkers for synergizing clinical information with tumor progression. Still, there are significant challenges in the implementation of these possibilities with strong evidence in cost-- effective manner.