Predicting Toxicity and Response to Pembrolizumab Through Germline Genomic HLA Class 1 Analysis

Life-threatening toxicities upon Pembrolizumab intake: could pharmacokinetics be the bad guy?

PURPOSE

We report the case of an adult patient diagnosed with Hodgkin's lymphoma who was scheduled for Pembrolizumab after failure of standard therapy. After three well-tolerated courses of Pembrolizumab, a PET scan showed a favorable outcome and a fourth course of Pembrolizumab was started. Unexpectedly, extremely severe toxicities (i.e., autoimmune peripheral hypothyroidism, rhabdomyolysis and severe acute renal failure) occurred after this last course, requiring transfer to the intensive care unit.

METHODS

Therapeutic drug monitoring was performed to measure residual Pembrolizumab levels at intervals from the last dose (i.e., 120 and then 170 days), as well as pharmacogenetics investigations on the FCγR gene.

RESULTS

Pembrolizumab plasma concentrations that were still pharmacologically active months after the last administration, suggesting impaired elimination of Pembrolizumab in this patient. Further pharmacokinetic modeling based on the population approach showed that both half-life (47.8 days) and clearance (0.12 L/day) values were significantly different from the standard values usually reported in patients. Further in silico simulations showed that pharmacologically active concentrations of Pembrolizumab were maintained for up to 136 days after the last dose. The search for possible polymorphisms affecting the genes coding for FCγR (i.e., rs1801274 on FCGR2A and rs396991 on FCGR3A gene) was negative. Further TDM showed that Pembrolizumab could be detected up to 263 days after the last administration.

CONCLUSION

This case report suggests that persistent overexposure in plasma could lead to life-threatening toxicities with Pembrolizumab.

Germline homozygosity and allelic imbalance of HLA-I are common in esophagogastric adenocarcinoma and impair the repertoire of immunogenic peptides

BACKGROUND

The individual HLA-I genotype is associated with cancer, autoimmune diseases and infections. This study elucidates the role of germline homozygosity or allelic imbalance of HLA-I loci in esophago-gastric adenocarcinoma (EGA) and determines the resulting repertoires of potentially immunogenic peptides.

METHODS

HLA genotypes and sequences of either (1) 10 relevant tumor-associated antigens (TAAs) or (2) patient-specific mutation-associated neoantigens (MANAs) were used to predict good-affinity binders using an in silico approach for MHC-binding (www.iedb.org). Imbalanced or lost expression of HLA-I-A/B/C alleles was analyzed by transcriptome sequencing. FluoroSpot assays and TCR sequencing were used to determine peptide-specific T-cell responses.

RESULTS

We show that germline homozygosity of HLA-I genes is significantly enriched in EGA patients (n=80) compared with an HLA-matched reference cohort (n=7605). Whereas the overall mutational burden is similar, the repertoire of potentially immunogenic peptides derived from TAAs and MANAs was lower in homozygous patients. Promiscuity of peptides binding to different HLA-I molecules was low for most TAAs and MANAs and in silico modeling of the homozygous to a heterozygous HLA genotype revealed normalized peptide repertoires. Transcriptome sequencing showed imbalanced expression of HLA-I alleles in 75% of heterozygous patients. Out of these, 33% showed complete loss of heterozygosity, whereas 66% had altered expression of only one or two HLA-I molecules. In a FluoroSpot assay, we determined that peptide-specific T-cell responses against NY-ESO-1 are derived from multiple peptides, which often exclusively bind only one HLA-I allele.

CONCLUSION

The high frequency of germline homozygosity in EGA patients suggests reduced cancer immunosurveillance leading to an increased cancer risk. Therapeutic targeting of allelic imbalance of HLA-I molecules should be considered in EGA.

Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer

Immune checkpoint inhibitors (ICI) are important treatment options for metastatic non-small cell lung cancer (mNSCLC). However, not all patients benefit from ICIs and can experience immune-related adverse events (irAEs). Limited understanding exists for germline determinants of ICI efficacy and toxicity, but Human Leukocyte Antigen (HLA) genes have emerged as a potential predictive biomarker. We performed HLA typing on 85 patients with mNSCLC, on ICI therapy and analyzed the impact of HLA Class II genotype on progression free survival (PFS), overall survival (OS), and irAEs. Most patients received pembrolizumab (83.5%). HLA-DRB4 genotype was seen in 34/85 (40%) and its presence correlated with improved OS in both univariate (p = 0.022; 26.3 months vs 10.2 months) and multivariate analysis (p = 0.011, HR 0.49, 95% CI [0.29, 0.85]). PFS did not reach significance (univariate, p = 0.12, 8.2 months vs 5.1 months). Eleven patients developed endocrine irAEs. HLA-DRB4 was the predominant genotype among these patients (9/11, 81.8%). Cumulative incidence of endocrine irAEs was higher in patients with HLA-DRB4 (p = 0.0139). Our study is the first to suggest that patients with metastatic NSCLC patients on ICI therapy with HLA-DRB4 genotype experience improved survival outcomes. Patients with HLA-DRB4 had the longest median OS (26.3 months). Additionally, we found a correlation between HLA-DRB4 and the occurrence of endocrine irAEs.

Review - The impact of pharmacogenetics on the outcome of immune checkpoint inhibitors

The development of immune checkpoint inhibitors (ICIs) has a tremendous effect on the treatment options for multiple types of cancer. Nonetheless, there is a large interpatient variability in response, survival, and the development of immune-related adverse events (irAEs). Pharmacogenetics is the general term for germline genetic variations, which may cause the observed interindividual differences in response or toxicity to treatment. These genetic variations can either be single-nucleotide polymorphisms (SNPs) or structural variants, such as gene deletions, amplifications or rearrangements. For ICIs, pharmacogenetic variation in the human leukocyte antigen molecules has also been studied with regard to treatment outcome. This review presents a summary of the literature regarding the pharmacogenetics of ICI treatment, discusses the most important known genetic variations and offers recommendations on the application of pharmacogenetics for ICI treatment.

Translation of AI into oncology clinical practice

Artificial intelligence (AI) is a transformative technology that is capturing popular imagination and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the potential to break through existing barriers in oncology research and practice such as automating workflow processes, personalizing care, and reducing healthcare disparities. Emerging applications of AI/ML in the literature include screening and early detection of cancer, disease diagnosis, response prediction, prognosis, and accelerated drug discovery. Despite this excitement, only few AI/ML models have been properly validated and fewer have become regulated products for routine clinical use. In this review, we highlight the main challenges impeding AI/ML clinical translation. We present different clinical use cases from the domains of radiology, radiation oncology, immunotherapy, and drug discovery in oncology. We dissect the unique challenges and opportunities associated with each of these cases. Finally, we summarize the general requirements for successful AI/ML implementation in the clinic, highlighting specific examples and points of emphasis including the importance of multidisciplinary collaboration of stakeholders, role of domain experts in AI augmentation, transparency of AI/ML models, and the establishment of a comprehensive quality assurance program to mitigate risks of training bias and data drifts, all culminating toward safer and more beneficial AI/ML applications in oncology labs and clinics.

The tumor microbiome as a predictor of outcomes in patients with metastatic melanoma treated with immune checkpoint inhibitors

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICIs). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA-seq was conducted on the formalin-fixed paraffin-embedded (FFPE) tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The 71 patients with metastatic melanoma ranged in age from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy responsive versus non-responsive tumors. Responders showed significant enrichment of several microbes including Fusobacterium nucleatum, and non-responders showed enrichment of fungi, as well as several bacteria. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.

Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

Systematic evaluation of the predictive gene expression signatures of immune checkpoint inhibitors in metastatic melanoma

Advances in immunotherapy, including immune checkpoint inhibitors (ICIs), have transformed the standard of care for many types of cancer including melanoma. ICIs have improved the overall outcome of melanoma patients; however, a significant proportion of patients suffer from primary or secondary tumor resistance. Therefore, there is an urgent need to develop predictive biomarkers to better select patients for ICI therapy. Numerous biomarkers that predict the response of melanoma to ICIs have been investigated, including biomarker signatures based on genomics or transcriptomics. Most of these predictive biomarkers have not been systematically evaluated across different cohorts to determine the reproducibility of these signatures in metastatic melanoma. We evaluated 28 previously published predictive biomarkers of ICIs based on gene expression signatures in eight previously published studies with available RNA-sequencing data in public repositories. We found that signatures related to IFN-γ-responsive genes, T and B cell markers, and chemokines in the tumor immune microenvironment are generally predictive of response to ICIs in these patients. In addition, we identified that these predictive biomarkers have higher predictive values in on-treatment samples as compared to pretreatment samples in metastatic melanoma. The most frequently overlapping genes among the top 18 predictive signatures were CXCL10, CXCL9, PRF1, RANTES, IFNG, HLA-DRA, GZMB, and CD8A. From gene set enrichment analysis and cell type deconvolution, we estimated that the tumors of responders were enriched with infiltrating cytotoxic T-cells and other immune cells and the upregulation of genes related to interferon-γ signaling. Conversely, the tumors of non-responders were enriched with stromal-related cell types such as fibroblasts and myofibroblasts, as well as enrichment with T helper 17 cell types across all cohorts. In summary, our approach of validating and integrating multi-omics data can help guide future biomarker development in the field of ICIs and serve the quest for a more personalized therapeutic approach for melanoma patients.

Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity

Immune checkpoint inhibitor (ICI) therapy has revolutionised the treatment of various cancer types. ICIs reinstate T-cell function to elicit an anti-cancer immune response. The resulting immune response can however have off-target effects which manifest as autoimmune type serious immune-related adverse events (irAE) in ~10-55% of patients treated. It is currently challenging to predict both who will experience irAEs and to what severity. Identification of patients at high risk of serious irAE would revolutionise patient care. While the pathogenesis driving irAE development is still unclear, host genetic factors are proposed to be key determinants of these events. This review presents current evidence supporting the role of the host genome in determining risk of irAE. We summarise the spectrum and timing of irAEs following treatment with ICIs and describe currently reported germline genetic variation associated with expression of immuno-modulatory factors within the cancer immunity cycle, development of autoimmune disease and irAE occurrence. We propose that germline genetic determinants of host immune function and autoimmune diseases could also explain risk of irAE development. We also endorse genome-wide association studies of patients being treated with ICIs to identify genetic variants that can be used in polygenic risk scores to predict risk of irAE.

Impact of germline HLA genotypes on clinical outcomes in patients with urothelial cancer treated with pembrolizumab

Human leukocyte antigen class I (HLA-I) genotypes are suggested to influence the cancer response to checkpoint blockade immunotherapy. This study assessed the impact of germline HLA genotypes on clinical outcomes in patients with chemoresistant advanced urothelial cancer (UC) treated with pembrolizumab. Zygosity, supertypes, evolutionary divergency, and specific alleles of germline HLA-I and -II were evaluated using the Luminex technique in 108 patients with chemoresistant metastatic or locally advanced UC treated with pembrolizumab. Among the 108 patients, 69 died and 83 showed radiographic progression during follow-up. Homozygous for at least one HLA-I locus, absence of the HLA-A03 supertype, and high HLA-I evolutionary divergence were associated with a radiographic response, but were not associated with survival outcomes. Patients with the HLA-DQB1*03:01 allele had significantly lower disease control rates than patients without the allele (17.4% vs. 53.8%, p = 0.002); its presence was also an independent risk factor for progressive disease (hazard ratio 4.35, 95% confidence interval 1.03-18.46). Furthermore, patients with the HLA-DQB1*03:01 allele had significantly worse progression-free survival than patients without the allele (median progression-free survival 3.1 vs. 4.8 months, p = 0.035). There was no significant relationship between any HLA status and the incidence of severe adverse events. Several germline HLA genotypes, especially HLA-DQB1*03:01, may be associated with radiographic progression. However, their impact on treatment response is limited, and germline HLA genotypes was not independently associated with survival outcomes. Further prospective studies are needed to confirm the relationship between germline HLA genotypes and clinical outcomes in patients with chemoresistant advanced UC treated with pembrolizumab.

Co-Inhibitory Molecules – Their Role in Health and Autoimmunity; Highlighted by Immune Related Adverse Events

Immune checkpoint receptors are key players in regulating the immune response. They are responsible for both generating an immune response sufficient to kill invading pathogens, balancing the same response, and protecting against tissue destruction or the development of autoimmune events. The central role of the co-inhibitory receptors also referred to as inhibitory immune checkpoints, including PD-1 and CTLA-4 has become especially evident with the cancer treatments targeting these receptors. Blocking these pathways enhances the immune activity, resulting in both an increased chance of cancer clearance, at the same time induction of immune-related adverse events (irAE). Some of these irAE progress into actual autoimmune diseases with autoantibodies and symptoms, undistinguished from the naturally occurring diseases. This review will take advantage of the lessons learned from immune checkpoint blockade and relate this knowledge to our understanding of the same pathways in naturally occurring autoimmune diseases, mainly focusing on rheumatic diseases.

Genomic predictors of response to PD-1 inhibition in children with germline DNA replication repair deficiency

Cancers arising from germline DNA mismatch repair deficiency or polymerase proofreading deficiency (MMRD and PPD) in children harbour the highest mutational and microsatellite insertion–deletion (MS-indel) burden in humans. MMRD and PPD cancers are commonly lethal due to the inherent resistance to chemo-irradiation. Although immune checkpoint inhibitors (ICIs) have failed to benefit children in previous studies, we hypothesized that hypermutation caused by MMRD and PPD will improve outcomes following ICI treatment in these patients. Using an international consortium registry study, we report on the ICI treatment of 45 progressive or recurrent tumors from 38 patients. Durable objective responses were observed in most patients, culminating in a 3 year survival of 41.4%. High mutation burden predicted response for ultra-hypermutant cancers (>100 mutations per Mb) enriched for combined MMRD + PPD, while MS-indels predicted response in MMRD tumors with lower mutation burden (10–100 mutations per Mb). Furthermore, both mechanisms were associated with increased immune infiltration even in ‘immunologically cold’ tumors such as gliomas, contributing to the favorable response. Pseudo-progression (flare) was common and was associated with immune activation in the tumor microenvironment and systemically. Furthermore, patients with flare who continued ICI treatment achieved durable responses. This study demonstrates improved survival for patients with tumors not previously known to respond to ICI treatment, including central nervous system and synchronous cancers, and identifies the dual roles of mutation burden and MS-indels in predicting sustained response to immunotherapy.

Hypermutation and microsatellite burden determine responses and long-term survival following PD-1 blockade in children and young adults with refractory cancers resulting from germline DNA replication repair deficiency.

Pan-cancer analysis of longitudinal metastatic tumors reveals genomic alterations and immune landscape dynamics associated with pembrolizumab sensitivity

Serial circulating tumor DNA (ctDNA) monitoring is emerging as a non-invasive strategy to predict and monitor immune checkpoint blockade (ICB) therapeutic efficacy across cancer types. Yet, limited data exist to show the relationship between ctDNA dynamics and tumor genome and immune microenvironment in patients receiving ICB. Here, we present an in-depth analysis of clinical, whole-exome, transcriptome, and ctDNA profiles of 73 patients with advanced solid tumors, across 30 cancer types, from a phase II basket clinical trial of pembrolizumab (NCT02644369) and report changes in genomic and immune landscapes (primary outcomes). Patients stratified by ctDNA and tumor burden dynamics correspond with survival and clinical benefit. High mutation burden, high expression of immune signatures, and mutations in BRCA2 are associated with pembrolizumab molecular sensitivity, while abundant copy-number alterations and B2M loss-of-heterozygosity corresponded with resistance. Upon treatment, induction of genes expressed by T cell, B cell, and myeloid cell populations are consistent with sensitivity and resistance. We identified the upregulated expression of PLA2G2D, an immune-regulating phospholipase, as a potential biomarker of adaptive resistance to ICB. Together, these findings provide insights into the diversity of immunogenomic mechanisms that underpin pembrolizumab outcomes.