Uncovering the flip side of immune checkpoint inhibitors: a comprehensive review of immune-related adverse events and predictive biomarkers

Abstract

Immune checkpoint inhibitors (ICIs) have generated considerable excitement as a novel class of immunotherapeutic agents due to their remarkable efficacy in treating various types of cancer. However, the widespread use of ICIs has brought about a number of safety concerns, especially the development of immune-related adverse events (irAEs). These serious complications could result in treatment discontinuation and even life-threatening consequences, making it critical to identify high-risk groups and predictive markers of irAEs before initiating therapy. To this end, the current article examines several potential predictive markers of irAEs in important organs affected by ICIs. While retrospective studies have yielded some promising results, limitations such as small sample sizes, variable patient populations, and specific cancer types and ICIs studied make it difficult to generalize the findings. Therefore, prospective cohort studies and real-world investigations are needed to validate the potential of different biomarkers in predicting irAEs risk. Overall, identifying predictive markers of irAEs is a crucial step towards improving patient safety and enhancing the management of irAEs. With ongoing research efforts, it is hoped that more accurate and reliable biomarkers will be identified and incorporated into clinical practice to guide treatment decisions and prevent the development of irAEs in susceptible patients.

Keywords: Cancer; Immune Checkpoint Inhibitors; Immune-Related Adverse Effects; Immunotherapy; Markers.

Figure 1

Mechanism of immune checkpoint inhibitors. Monoclonal antibodies targeting CTLA-4 and PD-1 receptors, as well as PD-L1, are ICIs that regulate T cell activation. During the priming phase, antigen presentation by MHC class II molecules on antigen-presenting cells triggers T cell activation by the T-cell receptor (TCR) recognizing antigen, followed by CD28 receptor binding with B7 (CD80 or CD86). The surface receptor of CTLA-4 on T cells inhibits T cell activation through competing with CD28 for CD80 or CD86 binding. The use of CTLA-4 inhibitor antibodies blocks the CTLA-4-CD80 or CTLA-4-CD86 binding, thus promoting T cell activation (indicated by a dashed line). During the effector phase, PD-1 expressed by T cells interacts with PD-L1 expressed by tumor and myeloid cells, promoting apoptosis of antigen-specific T cells while reducing regulatory T cell apoptosis. Under normal circumstances, this mechanism serves to protect against autoimmune disorders. However, cancer cells take advantage of it by increasing the expression of PD-L1, which helps them evade the immune system. To counteract this, inhibitors of PD-1 and PD-L1 can be used to block their interaction and promote activation of T-cells.

Figure 2

LAG-3 expression and ligands. (A) LAG-3 is not initially present on primary T cells but can be induced upon antigen stimulation on both CD4+ and CD8+ T cells. It is also expressed in a particular subset of CD4+ T cells with suppressive capabilities. LAG-3 can selectively bind to stable pMHCII7, distinguishing the conformation of pMHCII. (B) Additionally, FGL1 protein is a significant functional ligand for LAG-3. Upregulation of FGL1 expression by tumor cells can regulate the inhibitory function of LAG-3, thereby affecting T cell immune activity . Furthermore, Galectin-3 and LSECtin can interact with the glycans on LAG-3 , .

Figure 3

A bibliometric analysis of adverse events related to immune checkpoint inhibitors. (A) The overview of adverse events related to immune checkpoint inhibitors in WOSCC by 'Bibiometrix' package. (B) Analysis of annual publication trends in the field of adverse events related to immune checkpoint inhibitors. (C) World map of Conutries's scientific production. (D) A geographical distribution of scholarly papers originating from various nations, elucidated through bibliographic coupling analysis facilitated by VOSviewer (version 1.6.18). Every circle symbolizes a nation, with the circle's magnitude corresponding to the volume of scholarly production from that nation. The connecting lines imply inter-country collaborations; the thicker the line, the more intimate the cooperation. Various hues signify distinct clusters. € An elucidation of the distribution of scholarly output emanating from different institutions, facilitated via bibliographic coupling analysis using VOSviewer (version 1.6.18). Every circle represents an institution, and the circle's magnitude embodies the volume of scholarly output from that institution. Interconnecting lines suggest institutional collaborations; the broader the line, the more intimate the association. Diverse shades indicate distinct clusters. (F) A VOSviewer visualization chart of bibliographic coupling sources. Each circle embodies a journal, with the circle's size reflecting the volume of publications in that particular journal as per the bibliographic coupling analysis. The greater the circle, the more voluminous the publications. Lines connecting the circles signify inter-journal relationships, and differently hued connection networks suggest cooperative clusters between distinct journals. Diverse shades represent different clusters . (G) A VOSviewer visualization diagram of cited manuscripts. Each circle represents a manuscript, with the circle's size mirroring the citation count in the citation analysis. The greater the circle, the more citations. Interconnecting lines illustrate relationships between manuscripts, and distinctively hued connection networks indicate collaborative clusters between different documents. Various colors symbolize different clusters. (H) A word cloud representing the frequency of authors' keywords within the realm of unfavorable outcomes linked to immune checkpoint inhibitors. The more prominent the font, the greater its prevalence.

Figure 4

Common immune-related adverse events and possible mechanisms. ICI therapy may result in adverse events in any organ. This diagram shows the most common irAEs encountered by clinicians in patients treated with ICIs and their possible mechanisms.