Evolutionary divergence of HLA class I genotype impacts efficacy of cancer immunotherapy

HLA-DP diversity is associated with improved response to SARS-Cov-2 vaccine in hematopoietic stem cell transplant recipients

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients show lower humoral vaccine responsiveness than immunocompetent individuals. HLA diversity, measured by the HLA evolutionary divergence (HED) metrics, reflects the diversity of the antigenic repertoire presented to T cells, and has been shown to predict response to cancer immunotherapy. We retrospectively investigated the association of HED with humoral response to SARS-CoV-2 vaccine in allo-HSCT recipients. HED was calculated as pairwise genetic distance between alleles at HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1 loci in recipients and their donors. Low anti-spike IgG levels (<30 BAU/mL) were associated with short time from allo-SCT and low donor DPB1-HED, mostly related to donor DPB1 homozygosity. The diversity of donor HLA-DP molecules, assessed by heterozygosity or sequence divergence, may thus impact the efficacy of donor-derived CD4 T cells to sustain vaccine-mediated antibody response in allo-HSCT recipients.

Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.

Determinants of tumor immune evasion: the role of T cell exposed motif frequency and mutant amino acid exposure

Few neoepitopes detected in tumor biopsies are immunogenic. Tumor-specific T cell responses require both the presentation of an epitope that differs from wildtype and the presence of T cells with neoepitope-cognate receptors. We show that mutations detected in tumor biopsies result in an increased frequency of rare amino acid combinations compared to the human proteome and gastrointestinal microorganisms. Mutations in a large data set of oncogene and tumor suppressor gene products were compared to wildtype, and to the count of corresponding amino acid motifs in the human proteome and gastrointestinal microbiome. Mutant amino acids in T cell exposed positions of potential neoepitopes consistently generated amino acid motifs that are less common in both proteome reference datasets. Approximately 10% of the mutant amino acid motifs are absent from the human proteome. Motif frequency does not change when mutants were positioned in the MHC anchor positions hidden from T cell receptors. Analysis of neoepitopes in GBM and LUSC cases showed less common T cell exposed motifs, and HLA binding preferentially placing mutant amino acids in an anchor position for both MHC I and MHC II. Cross-presentation of mutant exposed neoepitopes by MHC I and MHC II was particularly uncommon. Review of a tumor mutation dataset known to generate T cell responses showed immunogenic epitopes were those with mutant amino acids exposed to the T cell receptor and with exposed pentamer motifs present in the human and microbiome reference databases. The study illustrates a previously unrecognized mechanism of tumor immune evasion, as rare T cell exposed motifs produced by mutation are less likely to have cognate T cells in the T cell repertoire. The complex interactions of HLA genotype, binding positions, and mutation specific changes in T cell exposed motif underscore the necessity of evaluating potential neoepitopes in each individual patient.

Association of HLA diversity with the risk of 25 cancers in the UK Biobank

BACKGROUND

The human leukocyte antigen (HLA) is a highly polymorphic region, and HLA diversity may play a role in presenting tumour-associated peptides and inducing immune responses. However, the effect of HLA diversity on cancers has not been fully assessed. We aimed to explore the role of HLA diversity on cancer development.

METHODS

A pan-cancer analysis was performed to evaluate the effect of HLA diversity, measured by HLA heterozygosity and HLA evolutionary divergence (HED), on the susceptibility of 25 cancers in the UK Biobank.

FINDINGS

We observed that the diversity of HLA class II locus was associated with a lower risk of lung cancer (OR_hetero = 0.94, 95% CI = 0.90-0.97, P = 1.29 × 10^-4) and head and neck cancer (OR_hetero = 0.91, 95% CI = 0.86-0.96, P = 1.56 × 10^-3). Besides, a lower risk of non-Hodgkin lymphoma was associated with an increased diversity of HLA class I (OR_hetero = 0.92, 95% CI = 0.87-0.98, P = 8.38 × 10^-3) and class II locus (OR_hetero = 0.89, 95% CI = 0.86-0.92, P = 1.65 × 10^-10). A lower risk of Hodgkin lymphoma was associated with the HLA class I diversity (OR_hetero = 0.85, 95% CI = 0.75-0.96, P = 0.011). The protective effect of HLA diversity was mainly observed in pathological subtypes with higher tumour mutation burden, such as lung squamous cell carcinoma (P = 9.39 × 10^-3) and diffuse large B cell lymphoma (P_{class I} = 4.12 × 10^-4; P_{class Ⅱ} = 4.71 × 10^-5), as well as the smoking subgroups of lung cancer (P = 7.45 × 10^-5) and head and neck cancer (P = 4.55 × 10^-3).

INTERPRETATION

We provided a systematic insight into the effect of HLA diversity on cancers, which might help to understand the etiological role of HLA on cancer development.

FUNDING

This study was supported by grants from the National Natural Science Foundation of China (82273705, 82003520); the Basic and Applied Basic Research Foundation of Guangdong Province, China (2021B1515420007); the Science and Technology Planning Project of Guangzhou, China (201804020094); Sino-Sweden Joint Research Programme (81861138006); the National Natural Science Foundation of China (81973131, 81903395, 81803319, 81802708).

Cancer Immunology: Immune Escape of Tumors-Expression and Regulation of HLA Class I Molecules and Its Role in Immunotherapies

The addition of "avoiding immune destruction" to the hallmarks of cancer demonstrated the importance of cancer immunology and in particular the role of immune surveillance and escape from malignancies. However, the underlying mechanisms contributing to immune impairment and immune responses are diverse. Loss or reduced expression of the HLA class I molecules are major characteristics of human cancers resulting in an impaired recognition of tumor cells by CD8 + cytotoxic T lymphocytes. This is of clinical relevance and associated with worse patients outcome and limited efficacy of T-cell-based immunotherapies. Here, we summarize the role of HLA class I antigens in cancers by focusing on the underlying molecular mechanisms responsible for HLA class I defects, which are caused by either structural alterations or deregulation at the transcriptional, posttranscriptional, and posttranslational levels. In addition, the influence of HLA class I abnormalities to adaptive and acquired immunotherapy resistances will be described. The in-depth knowledge of the different strategies of malignancies leading to HLA class I defects can be applied to design more effective cancer immunotherapies.

Leukemia relapse via genetic immune escape after allogeneic hematopoietic cell transplantation

Graft-versus-leukemia (GvL) reactions are responsible for the effectiveness of allogeneic hematopoietic cell transplantation as a treatment modality for myeloid neoplasia, whereby donor T- effector cells recognize leukemia neoantigens. However, a substantial fraction of patients experience relapses because of the failure of the immunological responses to control leukemic outgrowth. Here, through a broad immunogenetic study, we demonstrate that germline and somatic reduction of human leucocyte antigen (HLA) heterogeneity enhances the risk of leukemic recurrence. We show that preexistent germline-encoded low evolutionary divergence of class II HLA genotypes constitutes an independent factor associated with disease relapse and that acquisition of clonal somatic defects in HLA alleles may lead to escape from GvL control. Both class I and II HLA genes are targeted by somatic mutations as clonal selection factors potentially impairing cellular immune reactions and response to immunomodulatory strategies. These findings define key molecular modes of post-transplant leukemia escape contributing to relapse.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.

Human leukocyte antigen evolutionary divergence influences outcomes of paediatric patients and young adults affected by malignant disorders given allogeneic haematopoietic stem cell transplantation from unrelated donors

High genetic heterogeneity in the human leukocyte antigen (HLA) increases the likelihood of efficient immune response to pathogens and tumours. As measure of HLA diversity, HLA evolutionary divergence (HED) has been shown to predict the response of tumours to immunotherapy and haematopoietic stem cell transplantation (HSCT) in adults. We retrospectively investigated the association of HED with outcomes of 153 paediatric/young adults patients, treated for malignant disorders with HSCT from 9-10/10 HLA-matched unrelated donors. HED was calculated as pairwise genetic distance between alleles in patient HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1, using the locus median to stratify patients with 'high' or 'low' HED. Patients with high HED-B and -DRB1 showed significantly improved disease-free survival (DFS), especially when combined (70.8% vs 53.7% p = 0.008). High HED-B + -DRB1 was also associated with improved overall survival (OS) (82.1 vs 66.4% p = 0.014), and concomitant reduction of non-relapse-mortality (5.1% vs 21.1% p = 0.006). The impact on OS and DFS of combined HED-B + -DRB1 was confirmed in multivariate analysis [hazard ratio (HR) 0.39, p = 0.009; and HR 0.45, p = 0.007 respectively]. Only high HED scores for HLA-DPB1 were associated, in univariate analysis, with reduced incidence of relapse (15.9% vs 31.1%, p = 0.03). These results support HED as prognostic marker in allogeneic HSCT and, if confirmed in larger cohorts, would allow its use to inform clinical risk and potentially influence clinical practice.

Effect of genetic polymorphisms on outcomes following nivolumab for advanced renal cell carcinoma in the SNiP-RCC trial

BACKGROUND

Anti-PD-1 antibodies are widely used for cancer treatment including advanced renal cell carcinoma (RCC). However, their therapeutic and adverse effects vary among patients. This study aimed to identify genetic markers that predict outcome after nivolumab anti-PD-1 antibody treatment for advanced RCC.

METHODS

This study was registered on the website of the University Hospital Medical Information Network (protocol ID, UMIN000037739). Patient enrollment was conducted at 23 institutions in Japan between August 19, 2019, and September 30, 2020. Patient follow-up ended on March 31, 2021. Patients were treated with nivolumab for advanced clear cell RCC. A genome-wide association study was performed in the development set, while genotyping of target regions in the validation set was undertaken. Single nucleotide polymorphisms (SNPs) in genes of interest CD274, PDCD1LG2 and PDCD1 were genotyped in the combined set. The primary endpoint was the association of SNPs with objective response following nivolumab treatment. As secondary endpoints, the associations of SNPs with radiographic progression-free survival (rPFS) and treatment-related grade  ≥ 3 adverse events (AEs) were evaluated.

RESULTS

A genome-wide association study followed by a validation study identified that SNPs in FARP1 (rs643896 and rs685736) were associated with objective response and rPFS but not AEs following nivolumab treatment. Furthermore, SNPs in PDCD1LG2 (rs822339 and rs1411262) were associated with objective response, rPFS, and AEs following nivolumab treatment. Genetic risk category determined according to the number of risk alleles in SNPs (rs643896 in FARP1 and rs4527932 in PDCD1LG2) excellently predicted objective response and rPFS in nivolumab treatment.

CONCLUSION

This study revealed that SNPs in FARP1 and PDCD1LG2 were correlated with outcome in nivolumab treatment. The use of these SNPs may be beneficial in selecting appropriate treatment for individual patients and may contribute to personalized medicine.

Clinical and technical insights of tumour mutational burden in non-small cell lung cancer

Despite the durable responses provided by the introduction of checkpoint inhibitors in advanced Non-Small Cell Lung Cancer (NSCLC) without actionable targets in a subset of patients, a large proportion of them will progress after immunotherapy. Programmed Death Ligand 1 (PD-L1) was the first biomarker approved for immunotherapy, although it has multiple limitations, thus the development of novel biomarkers is an urgent need. Tumour Mutational Burden (TMB) is an emerging biomarker defined as the total number of mutations per coding area of tumour genome. Targeted gene panels have emerged as a cost-effective approach to estimate TMB. However, there is still an unmet need to fully standardize sample requirements, panel size, and bioinformatic pipelines to ensure that TMB is calculated appropriately. In addition, researchers are also evaluating TMB calculation in liquid biopsy. In this work, we summarize the relevant advances and the clinical utility of TMB in NSCLC.

Construction and validation of a bladder cancer risk model based on autophagy-related genes

Autophagy has an important association with tumorigenesis, progression, and prognosis. However, the mechanism of autophagy-regulated genes on the risk prognosis of bladder cancer (BC) patients has not been fully elucidated yet. In this study, we created a prognostic model of BC risk based on autophagy-related genes, which further illustrates the value of genes associated with autophagy in the treatment of BC. We first downloaded human autophagy-associated genes and BC datasets from Human Autophagy Database and The Cancer Genome Atlas (TCGA) database, and finally obtained differential prognosis-associated genes for autophagy by univariate regression analysis and differential analysis of cancer versus normal tissues. Subsequently, we downloaded two datasets from Gene Expression Omnibus (GEO), GSE31684 and GSE15307, to expand the total number of samples. Based on these genes, we distinguished the molecular subtypes (C1, C2) and gene classes (A, B) of BC by consistent clustering analysis. Using the genes merged from TCGA and the two GEO datasets, we conducted least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to obtain risk genes and construct autophagy-related risk prediction models. The accuracy of this risk prediction model was assessed by receiver operating characteristic (ROC) and calibration curves, and then nomograms were constructed to predict the survival of bladder cancer patients at 1, 3, and 5 years, respectively. According to the median value of the risk score, we divided BC samples into the high- and low-risk groups. Kaplan-Meier (K-M) survival analysis was performed to compare survival differences between subgroups. Then, we used single sample gene set enrichment analysis (ssGSEA) for immune cell infiltration abundance, immune checkpoint genes, immunotherapy response, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and tumor mutation burden (TMB) analysis for different subgroups. We also applied quantitative real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) techniques to verify the expression of these six genes in the model. Finally, we chose the IMvigor210 dataset for external validation. Six risk genes associated with autophagy (SPOCD1, FKBP10, NAT8B, LDLR, STMN3, and ANXA2) were finally screened by LASSO regression algorithm and multivariate Cox regression analysis. ROC and calibration curves showed that the model established was accurate and reliable. Univariate and multivariate regression analyses were used to verify that the risk model was an independent predictor. K-M survival analysis indicated that patients in the high-risk group had significantly worse overall survival than those in the low-risk group. Analysis by algorithms such as correlation analysis, gene set variation analysis (GSVA), and ssGSEA showed that differences in immune microenvironment, enrichment of multiple biologically active pathways, TMB, immune checkpoint genes, and human leukocyte antigens (HLAs) were observed in the different risk groups. Then, we constructed nomograms that predicted the 1-, 3-, and 5-year survival rates of different BC patients. In addition, we screened nine sensitive chemotherapeutic drugs using the correlation between the obtained expression status of risk genes and drug sensitivity results. Finally, the external dataset IMvigor210 verified that the model is reliable and efficient. We established an autophagy-related risk prognostic model that is accurate and reliable, which lays the foundation for future personalized treatment of bladder cancer.

HLA-A*01:01 allele diminishing in COVID-19 patients population associated with non-structural epitope abundance in CD8+ T-cell repertoire

In mid-2021, the SARS-CoV-2 Delta variant caused the third wave of the COVID-19 pandemic in several countries worldwide. The pivotal studies were aimed at studying changes in the efficiency of neutralizing antibodies to the spike protein. However, much less attention was paid to the T-cell response and the presentation of virus peptides by MHC-I molecules. In this study, we compared the features of the HLA-I genotype in symptomatic patients with COVID-19 in the first and third waves of the pandemic. As a result, we could identify the diminishing of carriers of the HLA-A*01:01 allele in the third wave and demonstrate the unique properties of this allele. Thus, HLA-A*01:01-binding immunoprevalent epitopes are mostly derived from ORF1ab. A set of epitopes from ORF1ab was tested, and their high immunogenicity was confirmed. Moreover, analysis of the results of single-cell phenotyping of T-cells in recovered patients showed that the predominant phenotype in HLA-A*01:01 carriers is central memory T-cells. The predominance of T-lymphocytes of this phenotype may contribute to forming long-term T-cell immunity in carriers of this allele. Our results can be the basis for highly effective vaccines based on ORF1ab peptides.

Impact of cytotoxic T lymphocytes immunotherapy on prognosis of colorectal cancer patients

Background

Expansion and activation of cytotoxic T lymphocytes (CTLs) in vitro represents a promising immunotherapeutic strategy, and CTLs can be primed by dendritic cells (DCs) loaded with tumor-associated antigens (TAAs) transformed by recombinant adeno-associated virus (rAAV). This study aimed to explore the impact of rAAV-DC-induced CTLs on prognosis of CRC and to explore factors associated with prognosis.

Methods

This prospective observational study included patients operated for CRC at Yan'an Hospital Affiliated to Kunming Medical University between 2016 and 2019. The primary outcome was progression-free survival (PFS), secondary outcomes were overall survival (OS) and adverse events. Totally 49 cases were included, with 29 and 20 administered rAAV-DC-induced CTL and chemotherapy, respectively.

Results

After 37-69 months of follow-up (median, 54 months), OS (P=0.0596) and PFS (P=0.0788) were comparable between two groups. Mild fever occurred in 2 (6.9%) patients administered CTL infusion. All the chemotherapy group experienced mild-to-moderate adverse effects, including vasculitis (n=20, 100%), vomiting (n=5, 25%), nausea (n=17, 85%) and fatigue (n=17, 85%).

Conclusions

Lymphatic metastasis (hazard ratio [HR]=4.498, 95% confidence interval [CI]: 1.290-15.676; P=0.018) and lower HLA-I expression (HR=0.294, 95%CI: 0.089-0.965; P=0.044) were associated with poor OS in the CTL group. CTLs induced by rAAV-DCs might achieve comparable effectiveness in CRC patients compare to chemotherapy, cases with high tumor-associated HLA-I expression and no lymphatic metastasis were more likely to benefit from CTLs.

The ectonucleotidase CD39 identifies tumor-reactive CD8+ T cells predictive of immune checkpoint blockade efficacy in human lung cancer

Improved identification of anti-tumor T cells is needed to advance cancer immunotherapies. CD39 expression is a promising surrogate of tumor-reactive CD8+ T cells. Here, we comprehensively profiled CD39 expression in human lung cancer. CD39 expression enriched for CD8+ T cells with features of exhaustion, tumor reactivity, and clonal expansion. Flow cytometry of 440 lung cancer biospecimens revealed weak association between CD39+ CD8+ T cells and tumoral features, such as programmed death-ligand 1 (PD-L1), tumor mutation burden, and driver mutations. Immune checkpoint blockade (ICB), but not cytotoxic chemotherapy, increased intratumoral CD39+ CD8+ T cells. Higher baseline frequency of CD39+ CD8+ T cells conferred improved clinical outcomes from ICB therapy. Furthermore, a gene signature of CD39+ CD8+ T cells predicted benefit from ICB, but not chemotherapy, in a phase III clinical trial of non-small cell lung cancer. These findings highlight CD39 as a proxy of tumor-reactive CD8+ T cells in human lung cancer.

Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies

The high primary resistance incidence and unavoidable secondary resistance are the major clinical obstacle to lasting long-term benefits in Non-small-cell lung cancer (NSCLC) patients treated with immunotherapy. The mechanisms of immunotherapy resistance in NSCLC are complex, mainly involving tumor cells and tumor microenvironment (TME) infiltrating immune cells, including TAMs, B cells, NK cells, and T cells. The selection of clinical strategies for NSCLC progression after immunotherapy resistance should depend on the progressive mode. The progression pattern of NSCLC patients after immunotherapy resistance can be divided into oligo-progression and systemic/multiple progression, which should be considered for further treatment selection. In the future, it needs to explore how to optimize the combined therapy and explore strategies to reprogram infiltrating immune cells under various genetic backgrounds of tumor cells and timely reshape TME during antitumor treatments.

Genetic differences between smokers and never-smokers with lung cancer

Smoking is a major risk factor for lung cancer, therefore lung cancer epidemiological trends reflect the past trends of cigarette smoking to a great extent. The geographic patterns in mortality closely follow those in incidence. Although lung cancer is strongly associated with cigarette smoking, only about 15% of smokers get lung cancer, and also some never-smokers develop this malignancy. Although less frequent, lung cancer in never smokers is the seventh leading cause of cancer deaths in both sexes worldwide. Lung cancer in smokers and never-smokers differs in many aspects: in histological types, environmental factors representing a risk, and in genes associated with this disease. In this review, we will focus on the genetic differences between lung cancer in smokers versus never-smokers: gene expression, germ-line polymorphisms, gene mutations, as well as ethnic and gender differences. Finally, treatment options for smokers and never-smokers will be briefly reviewed.

HLA variants have different preferences to present proteins with specific molecular functions which are complemented in frequent haplotypes

Human leukocyte antigen (HLA) genes are the most polymorphic loci in the human genome and code for proteins that play a key role in guiding adaptive immune responses by presenting foreign and self peptides (ligands) to T cells. Each person carries up to 6 HLA class I variants (maternal and paternal copies of HLA-A, HLA-B and HLA-C genes) and also multiple HLA class II variants, which cumulatively define the landscape of peptides presented to T cells. Each HLA variant has its own repertoire of presented peptides with a certain sequence motif which is mainly defined by peptide anchor residues (typically the second and the last positions for HLA class I ligands) forming key interactions with the peptide-binding groove of HLA. In this study, we aimed to characterize HLA binding preferences in terms of molecular functions of presented proteins. To focus on the ligand presentation bias introduced specifically by HLA-peptide interaction we performed large-scale in silico predictions of binding of all peptides from human proteome for a wide range of HLA variants and established which functions are characteristic for proteins that are more or less preferentially presented by different HLA variants using statistical calculations and gene ontology (GO) analysis. We demonstrated marked distinctions between HLA variants in molecular functions of preferentially presented proteins (e.g. some HLA variants preferentially present membrane and receptor proteins, while others - ribosomal and DNA-binding proteins) and reduced presentation of extracellular matrix and collagen proteins by the majority of HLA variants. To explain these observations we demonstrated that HLA preferentially presents proteins enriched in amino acids which are required as anchor residues for the particular HLA variant. Our observations can be extrapolated to explain the protective effect of certain HLA alleles in infectious diseases, and we hypothesize that they can also explain susceptibility to certain autoimmune diseases and cancers. We demonstrate that these differences lead to differential presentation of HIV, influenza virus, SARS-CoV-1 and SARS-CoV-2 proteins by various HLA alleles. Taking into consideration that HLA alleles are inherited in haplotypes, we hypothesized that haplotypes composed of a combination of HLA variants with different presentation preferences should be more advantageous as they allow presenting a larger repertoire of peptides and avoiding holes in immunopeptidome. Indeed, we demonstrated that HLA-A/HLA-B and HLA-A/HLA-C haplotypes which have a high frequency in the human population are comprised of HLA variants that are more distinct in terms of functions of preferentially presented proteins than the control pairs.

Spatiotemporal evolution of the clear cell renal cell carcinoma microenvironment links intra-tumoral heterogeneity to immune escape

BACKGROUND

Intratumoral heterogeneity (ITH) is a hallmark of clear cell renal cell carcinoma (ccRCC) that reflects the trajectory of evolution and influences clinical prognosis. Here, we seek to elucidate how ITH and tumor evolution during immune checkpoint inhibitor (ICI) treatment can lead to therapy resistance.

METHODS

Here, we completed a single-arm pilot study to examine the safety and feasibility of neoadjuvant nivolumab in patients with localized RCC. Primary endpoints were safety and feasibility of neoadjuvant nivolumab. Then, we spatiotemporally profiled the genomic and immunophenotypic characteristics of 29 ccRCC patients, including pre- and post-therapy samples from 17 ICI-treated patients. Deep multi-regional whole-exome and transcriptome sequencing were performed on 29 patients at different time points before and after ICI therapy. T cell repertoire was also monitored from tissue and peripheral blood collected from a subset of patients to study T cell clonal expansion during ICI therapy.

RESULTS

Angiogenesis, lymphocytic infiltration, and myeloid infiltration varied significantly across regions of the same patient, potentially confounding their utility as biomarkers of ICI response. Elevated ITH associated with a constellation of both genomic features (HLA LOH, CDKN2A/B loss) and microenvironmental features, including elevated myeloid expression, reduced peripheral T cell receptor (TCR) diversity, and putative neoantigen depletion. Hypothesizing that ITH may itself play a role in shaping ICI response, we derived a transcriptomic signature associated with neoantigen depletion that strongly associated with response to ICI and targeted therapy treatment in several independent clinical trial cohorts.

CONCLUSIONS

These results argue that genetic and immune heterogeneity jointly co-evolve and influence response to ICI in ccRCC. Our findings have implications for future biomarker development for ICI response across ccRCC and other solid tumors and highlight important features of tumor evolution under ICI treatment.

TRIAL REGISTRATION

The study was registered on ClinicalTrial.gov (NCT02595918) on November 4, 2015.

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.

Germline variants associated with toxicity to immune checkpoint blockade

Immune checkpoint inhibitors (ICIs) have yielded remarkable responses but often lead to immune-related adverse events (irAEs). Although germline causes for irAEs have been hypothesized, no individual variant associated with developing irAEs has been identified. We carried out a genome-wide association study of 1,751 patients on ICIs across 12 cancer types. We investigated two irAE phenotypes: (1) high-grade (3-5) and (2) all-grade events. We identified 3 genome-wide significant associations (P < 5 × 10-8) in the discovery cohort associated with all-grade irAEs: rs16906115 near IL7 (combined P = 3.6 × 10-11; hazard ratio (HR) = 2.1); rs75824728 near IL22RA1 (combined P = 3.5 × 10-8; HR = 1.8); and rs113861051 on 4p15 (combined P = 1.2 × 10-8, HR = 2.0); rs16906115 was replicated in 3 independent studies. The association near IL7 colocalized with the gain of a new cryptic exon for IL7, a critical regulator of lymphocyte homeostasis. Patients carrying the IL7 germline variant exhibited significantly increased lymphocyte stability after ICI initiation, which was itself predictive of downstream irAEs and improved survival.

Tumor Immunogenic Cell Death as a Mediator of Intratumor CD8 T-Cell Recruitment

The success of anticancer treatments relies on a long-term response which can be mediated by the immune system. Thus, the concept of immunogenic cell death (ICD) describes the capacity of dying cancer cells, under chemotherapy or physical stress, to express or release danger-associated molecular patterns (DAMPs). These DAMPs are essential to activate dendritic cells (DCs) and to stimulate an antigen presentation to CD8 cytotoxic cells. Then, activated CD8 T cells exert their antitumor effects through cytotoxic molecules, an effect which is transitory due to the establishment of a feedback loop leading to T-cell exhaustion. This phenomenon can be reversed using immune checkpoint blockers (ICBs), such as anti-PD-1, PD-L1 or CTLA-4 Abs. However, the blockade of these checkpoints is efficient only if the CD8 T cells are recruited within the tumor. The CD8 T-cell chemoattraction is mediated by chemokines. Hence, an important question is whether the ICD can not only influence the DC activation and resulting CD8 T-cell activation but can also favor the chemokine production at the tumor site, thus triggering their recruitment. This is the aim of this review, in which we will decipher the role of some chemokines (and their specific receptors), shown to be released during ICD, on the CD8 T-cell recruitment and antitumor response. We will also analyze the clinical applications of these chemokines as predictive or prognostic markers or as new targets which should be used to improve patients' response.

Translating the evolving molecular landscape of tumors to biomarkers of response for cancer immunotherapy

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapeutics, triggering studies to understand the molecular and cellular wiring of response and resistance. Our increased understanding of the underlying biology of response to ICI has enabled the investigation of tumor-intrinsic and -extrinsic features that may predict therapeutic outcomes. In parallel, liquid biopsy measurements of circulating tumor DNA (ctDNA) can be used to assess real-time molecular responses and guide clinical decisions during ICI. The combination of these approaches provides a deeper understanding of cancer biology, immunoediting, and evolution during ICI and promise to extend the utility of immunotherapies for patients with cancer.

Solving the puzzle of what makes immunotherapies work

The rapid adoption of immune checkpoint blockade (ICB) therapies has led to a need to understand the mechanistic drivers of efficacy and the identification of novel biomarkers that enrich for patients who benefit from ICB therapy. Here, we provide a perspective on emerging biomarker candidates, their underlying biological mechanisms, and how they may fit into the current landscape of ICB biomarkers. We discuss new frameworks to identify and evaluate biomarker candidates and review the opportunities and challenges of utilizing biomarker-derived models to facilitate the development of new immunotherapies.

A single arm phase Ib/II trial of first-line pembrolizumab, trastuzumab and chemotherapy for advanced HER2-positive gastric cancer

In this multi-center phase II trial, we evaluated the efficacy and safety of a quadruplet regimen (pembrolizumab, trastuzumab, and doublet chemotherapy) as first-line therapy for unresectable or metastatic human epidermal growth factor receptor 2 (HER2)-positive advanced gastric cancer (AGC) (NCT02901301). The primary endpoints were recommended phase 2 dose (RP2D) for phase Ib and objective response rate (ORR) for phase II. The secondary endpoints included progression-free survival (PFS), overall survival (OS), duration of response, time to response and safety. Without dose-limiting or unexpected toxicities, the starting dose in the phase Ib trial was selected as RP2D. In 43 patients, the primary endpoint was achieved: the objective response rate was 76.7% (95% confidence interval [CI]: 61.4-88.2), with complete and partial responses in 14% and 62.8% of patients, respectively. The median progression-free survival, overall survival, and duration of response were 8.6 months, 19.3 months, and 10.8 months, respectively. No patients discontinued pembrolizumab because of immune-related adverse events. Programmed death ligand-1 status was not related to survival. Post hoc analyses of pretreatment tumor specimens via targeted sequencing indicated that ERBB2 amplification, RTK/RAS pathway alterations, and high neoantigen load corrected by HLA-B were positively related to survival. The current quadruplet regimen shows durable efficacy and safety for patients with HER2-positive AGC.

HLA-B evolutionary divergence is associated with outcomes after SARS-CoV-2 infection

We examined the correlation between class I HLA evolutionary divergence (HED), a surrogate for the capacity to present different peptides, and the outcomes of 234 adult inpatients with confirmed SARS-CoV-2 infection. Genomic DNA was extracted from peripheral blood and genotyped by next-generation sequencing (NGS). HED scores for HLA class I (HLA-A, -B, and -C) genotypes were calculated using Grantham’s distance. Higher HED scores for HLA-B, but not HLA-A or -C, are significantly associated with a decreased probability of poor outcomes including ICU admission, mechanical ventilation, and death (OR = 0.93; P = 0.04) in the univariate analysis. In the multivariate analysis, increased HLA-B HED score, younger age, and no comorbidity were independently associated with favorable outcomes (P = 0.02, P = 0.01, and P = 0.05, respectively). This finding is consistent with the notion that broader peptide repertoires presented by class I HLA may be beneficial in infection control.

Individual HLA heterogeneity and its implications for cellular immune evasion in cancer and beyond

Structural and functional variability of human leukocyte antigen (HLA) is the foundation for competent adaptive immune responses against pathogen and tumor antigens as it assures the breadth of the presented immune-peptidome, theoretically sustaining an efficient and diverse T cell response. This variability is presumably the result of the continuous selection by pathogens, which over the course of evolution shaped the adaptive immune system favoring the assortment of a hyper-polymorphic HLA system able to elaborate efficient immune responses. Any genetic alteration affecting this diversity may lead to pathological processes, perturbing antigen presentation capabilities, T-cell reactivity and, to some extent, natural killer cell functionality. A highly variable germline HLA genotype can convey immunogenetic protection against infections, be associated with tumor surveillance or influence response to anti-neoplastic treatments. In contrast, somatic aberrations of HLA loci, rearranging the original germline configuration, theoretically decreasing its variability, can facilitate mechanisms of immune escape that promote tumor growth and immune resistance. The purpose of the present review is to provide a unified and up-to-date overview of the pathophysiological consequences related to the perturbations of the genomic heterogeneity of HLA complexes and their impact on human diseases, with a special focus on cancer.

Benefit and toxicity of programmed death-1 blockade vary by ethnicity in patients with advanced melanoma: an international multicentre observational study

BACKGROUND

Programmed cell death receptor-1 (PD-1) monotherapy is a standard treatment for advanced cutaneous melanoma, but its efficacy and toxicity are defined in white populations and remain poorly characterized in other ethnic groups, such as East Asian, Hispanic and African.

OBJECTIVES

To determine the efficacy and toxicity of PD-1 monotherapy in different ethnic groups.

METHODS

Clinical data for patients with unresectable or advanced melanoma treated with anti-PD-1 monotherapy between 2009 and 2019 were collected retrospectively from five independent institutions in the USA, Australia and China. Tumour response, survival and immune-related adverse events (irAEs) were compared by ethnicity (white vs. East Asian/Hispanic/African) across different melanoma subtypes: nonacral cutaneous (NAC)/unknown primary (UP) and acral/mucosal/uveal.

RESULTS

In total, 1135 patients were included. White patients had significantly higher objective response rate (ORR) [54%, 95% confidence interval (CI) 50-57% vs. 20%, 95% CI 13-28%; adjusted P < 0·001] and longer progression-free survival (14·2 months, 95% CI 10·7-20·3 vs. 5·4 months, 95% CI 4·5-7·0; adjusted P < 0·001) than East Asian, Hispanic and African patients in the NAC and UP subtypes. White ethnicity remained independently associated with a higher ORR (odds ratio 4·10, 95% CI 2·48-6·81; adjusted P < 0·001) and longer PFS (hazard ratio 0·58, 95% CI 0·46-0·74; adjusted P < 0·001) in multivariate analyses after adjustment for age, sex, primary anatomical location, metastasis stage, baseline lactate dehydrogenase level, mutational status and prior systemic treatment. White and East Asian/Hispanic/African patients shared similar ORR and progression-free survival in acral/mucosal/uveal melanomas. Similar melanoma-subtype-specific ethnic discrepancies were observed in complete response rate and overall survival. White patients had higher rates of gastrointestinal irAEs but lower rates of endocrine, liver and other rare types of irAEs. These differences in irAEs by ethnicity were not attributable to varying melanoma subtypes.

CONCLUSIONS

Ethnic discrepancy in clinical benefit is specific to melanoma subtype, and East Asian, Hispanic and African patients with NAC and UP melanomas have poorer clinical benefits than previously recognized. The ethnic discrepancy in toxicity observed across different melanoma subtypes warrants an ethnicity-based irAE surveillance strategy. More research is needed to elucidate the molecular and immunological determinants of these differences. What is already known about this topic? There is a great difference in response to immunotherapy between different subtypes of melanoma (cutaneous, mucosal, acral and uveal) in patients with advanced disease. What does this study add? Our data show for the first time that there are differences between different ethnic groups in terms of both response and toxicity to immunotherapy beyond the well-appreciated discrepancies due to melanoma subtype.

Pan-Cancer HLA Gene-Mediated Tumor Immunogenicity and Immune Evasion

Human leukocyte antigen (HLA) expression contributes to the activation of antitumor immunity through interactions with T-cell receptors. Pan-cancer HLA-mediated immunogenicity and immunoediting mechanisms have not been systematically studied previously. In a retrospective analysis of 33 tumor types from the Cancer Genome Atlas (TCGA), we characterized the differential expression of HLA class I and class II genes across various oncogenic pathways and immune subtypes. While HLA I genes were upregulated in all immunogenically hot tumors, HLA II genes were upregulated in an inflammatory immune subtype associated with best prognosis and were systematically downregulated in specific oncogenic pathways. A subset of immunogenically hot tumors which upregulated HLA class I but not class II genes exploited HLA-mediated escape strategies. Furthermore, with a machine learning model, we demonstrated that HLA gene expression data can be used to predict the immune subtypes of patients receiving immune checkpoint blockade and stratify patient survival. Interestingly, tumors with the highest immune infiltration did not have the best prognosis but showed significantly higher immune exhaustion.

IMPLICATIONS

Taken together, we highlight the prognostic potential of HLA genes in immunotherapies and suggest that higher tumor immunogenicity mediated by HLA expression may sometimes lead to tumor escape under strong selective pressure.

'Know thyself' - host factors influencing cancer response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have revolutionised oncology and are now standard-of-care for the treatment of a wide variety of solid neoplasms. However, tumour responses remain unpredictable, experienced by only a minority of ICI recipients across malignancy types. Therefore, there is an urgent need for better predictive biomarkers to identify a priori the patients most likely to benefit from these therapies. Despite considerable efforts, only three such biomarkers are FDA-approved for clinical use, and all rely on the availability of tumour tissue for immunohistochemical staining or genomic assays. There is emerging evidence that host factors - for example, genetic, metabolic, and immune factors, as well as the composition of one's gut microbiota - influence the response of a patient's cancer to ICIs. Tantalisingly, some of these factors are modifiable, paving the way for co-therapies that may enhance the therapeutic index of these treatments. Herein, we review key host factors that are of potential biomarker value for response to ICI therapy, with a particular focus on the proposed mechanisms for these influences. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Identification and Validation of Necroptosis-Related LncRNA Signature in Hepatocellular Carcinoma for Prognosis Estimation and Microenvironment Status

Background: Hepatocellular carcinoma (HCC) is among malignancies with the highest fatality toll globally and minimal therapeutic options. Necroptosis is a programmed form of necrosis or inflammatory cell death, which can affect prognosis and microenvironmental status of HCC. Therefore, we aimed to explore the prognostic value of necroptosis-related lncRNAs (NRLs) in HCC and the role of the tumor microenvironment (TME) in immunotherapy. Methods: The RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). NRLs were identified by Pearson correlation analysis. The signature was constructed using the LASSO-Cox regression analysis and evaluated using the receiver operating characteristic curve (ROC) and the area under the Kaplan-Meier curve. The nomogram was built based on clinical information and risk score. Gene set enrichment analysis (GSEA), immunoassay, half-maximum inhibitory concentration (IC₅₀) analysis of the risk group, and the HCC subtype identification based on NRLs were also carried out. Finally, we detected the expression of lncRNAs in HCC tissues and cell lines in vitro. Results: A total of 508 NRLs were screened out, and seven NRLs were constructed as a risk stratification system to classify patients into distinct low- and high-risk groups. Patients in the high-risk group had a significantly lower overall survival (OS) than those in the low-risk group. Using multivariate Cox regression analysis, we found that the risk score was an independent predictor of OS. Functional analysis showed that the immune status of different patients was different. The IC₅₀ analysis of chemotherapy demonstrated that patients in the high-risk group were more sensitive to commonly prescribed drugs. qRT-PCR showed that three high-risk lncRNAs were upregulated in drug-resistant cells, and the expression in HCC tissues was higher than that in adjacent tissues. Conclusion: The prediction signature developed in this study can be used to assess the prognosis and microenvironment of HCC patients, and serve as a new benchmark for HCC treatment selection.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle–based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle–related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint–associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle–based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

Next-generation sequencing: unraveling genetic mechanisms that shape cancer immunotherapy efficacy

Immunity is governed by fundamental genetic processes. These processes shape the nature of immune cells and set the rules that dictate the myriad complex cellular interactions that power immune systems. Everything from the generation of T cell receptors and antibodies, control of epitope presentation, and recognition of pathogens by the immunoediting of cancer cells is, in large part, made possible by core genetic mechanisms and the cellular machinery that they encode. In the last decade, next-generation sequencing has been used to dissect the complexities of cancer immunity with potent effect. Sequencing of exomes and genomes has begun to reveal how the immune system recognizes “foreign” entities and distinguishes self from non-self, especially in the setting of cancer. High-throughput analyses of transcriptomes have revealed deep insights into how the tumor microenvironment affects immunotherapy efficacy. In this Review, we discuss how high-throughput sequencing has added to our understanding of how immune systems interact with cancer cells and how cancer immunotherapies work.

Coming of Age: Human Genomics and the Cancer-Immune Set Point

Cancer is largely a disease of the tumor cell genome. As a result, the majority of genetics research in oncology has concentrated on the role of tumor somatic mutations, as well as inherited risk variants, in disease susceptibility and response to targeted treatments. The advent and success of cancer immunotherapies, however, have opened new perspectives for the investigation of the role of inherited genetic variation in codetermining outcome and safety. It is increasingly likely that the entirety of germline genetic variation involved in regulating immune responses accounts for a significant fraction of the observed variability in responses to cancer immunotherapies. Although germline genetic data from patients treated with cancer immunotherapies are still scarce, this line of research benefits from a vast body of knowledge derived from studies into autoimmune and infectious disease phenotypes, thus not requiring a start from a blank slate. Here, we discuss how a thorough investigation of genomic variation relevant for individuals' variability in (auto)immune responses can contribute to the discovery of novel treatment approaches and drug targets, and yield predictive biomarkers to stratify cancer patient populations in precision and personalized medicine settings.

Cancer evolution: special focus on the immune aspect of cancer

Cancer is an evolutionary disease. Intra-tumor heterogeneity (ITH), which describes the diversity within individual tumors, sets the foundation for evolution. The fitness of tumor cells is determined by their microenvironment, which exerts intense selection pressure that generally favors cells with survival and proliferation advantages. It has been revealed that host immunity dramatically influences the evolutionary trajectory of cancer. As technologies advance, a refined map of the immune system's involvement in cancer evolution has gradually come to our knowledge. Here we specifically view cancer through the lens of evolutionary immunological biology. We will cover the neoplastic evolution under immunosurveillance, including how the host immunity shapes the tumor evolutionary trajectory and how progressive tumors modulate the host immunity to survive. A comprehensive understanding of the interplay between cancer evolution and cancer immunity provides clues to combating cancer strategically.

HLA Class I Downregulation in Progressing Metastases of Melanoma Patients Treated With Ipilimumab

Characterization of the molecular mechanisms underlying antitumor immune responses and immune escape mechanisms has resulted in the development of more effective immunotherapeutic strategies, including immune checkpoint inhibitor (ICI) therapy. ICIs can induce durable responses in patients with advanced cancer in a wide range of cancer types, however, the majority of the patients fail to respond to this therapy or develop resistance in the course of the treatment. Information about the molecular mechanisms underlying primary and acquired resistance is limited. Although HLA class I molecules are crucial in the recognition of tumor antigens by cytotoxic T lymphocytes, only a few studies have investigated the role of their expression level on malignant cells in ICI resistance. To address this topic, utilizing immunohistochemical staining with monoclonal antibodies (mAbs) we analyzed HLA class I expression level in pre-treatment and post-treatment tumor samples from melanoma patients treated with ipilimumab. Twenty-nine metastases removed from six patients were available for the study, including 18 pre-treatment and 11 post-treatment lesions. Compared to metastases excised before ipilimumab therapy, post-treatment lesions displayed a significantly lower HLA class I expression level on melanoma cells; HLA class I downregulation was most marked in progressing metastases from nonresponding patients. We also evaluated the level of infiltration by CD8⁺ T cells and NK cells but did not find consistent changes between pre- and post-treatment samples. Our results indicate the potential role of HLA class I downregulation as a mechanism of ICI resistance.

MAPK signaling regulates the efficacy of chemoimmunotherapy

Resistance to chemoimmunotherapy is a major issue for cancer care. We recently unravelled the role of mitogen-activated protein kinase (MAPK) to limit the antitumor efficacy of such combination. Inhibitor of MAPK pathway using mitogen-activated protein kinase (MEK) inhibitor in combination with chemotherapy triggers mitophagy of cancer cells, which induces the release of mitochondrial DNA that interact with Toll Like receptor 9 (TLR9) to promote the production of the chemokine CXCL10. CXCL10 could then turn cold tumor into hot tumor, thus leading to improve efficacy of chemoimmunotherapy.

The translational challenges of precision oncology

The translational challenges in the field of precision oncology are in part related to the biological complexity and diversity of this disease. Technological advances in genomics have facilitated large sequencing efforts and discoveries that have further supported this notion. In this review, we reflect on the impact of these discoveries on our understanding of several concepts: cancer initiation, cancer prevention, early detection, adjuvant therapy and minimal residual disease monitoring, cancer drug resistance, and cancer evolution in metastasis. We discuss key areas of focus for improving cancer outcomes, from biological insights to clinical application, and suggest where the development of these technologies will lead us. Finally, we discuss practical challenges to the wider adoption of molecular profiling in the clinic and the need for robust translational infrastructure.

Human Leukocyte Antigens in Pregnancy and Preeclampsia

Preeclampsia is a pregnancy-induced hypertensive disorder, the pathophysiology of which includes underlying maternal cardiovascular disease, deficient spiral artery remodeling during placenta development, and inflammatory immune responses at the maternal-fetal interface. Human leukocyte antigens (HLA) are major histocompatibility complex molecules essential for the recognition of foreign antigens that is central to immune defense against pathogens and critical determinants for the immune system discriminating between self and non-self tissues, such as in transplantation. Pregnancy represents a naturally existing “transplantation”, where the maternal immune system must be immunologically tolerant to the developing fetus which is 50% allogeneic. It is then unsurprising that HLA also influence normal pregnancy and pregnancy complications including preeclampsia. Here we review the role of classical and non-classical HLA molecules in influencing normal physiologic function during pregnancy and describe the association of HLA with pathophysiology in preeclampsia.

Predicting Durable Responses to Immune Checkpoint Inhibitors in Non-Small-Cell Lung Cancer Using a Multi-Feature Model

Due to the complex mechanisms affecting anti-tumor immune response, a single biomarker is insufficient to identify patients who will benefit from immune checkpoint inhibitors (ICIs) treatment. Therefore, a comprehensive predictive model is urgently required to predict the response to ICIs. A total of 162 non-small-cell lung cancer (NSCLC) patients undergoing ICIs treatment from three independent cohorts were enrolled and used as training and test cohorts (training cohort = 69, test cohort1 = 72, test cohort2 = 21). Eight genomic markers were extracted or calculated for each patient. Ten machine learning classifiers, such as the gaussian process classifier, random forest, and support vector machine (SVM), were evaluated. Three genomic biomarkers, namely tumor mutation burden, intratumoral heterogeneity, and loss of heterozygosity in human leukocyte antigen were screened out, and the SVM_poly method was adopted to construct a durable clinical benefit (DCB) prediction model. Compared with a single biomarker, the DCB multi-feature model exhibits better predictive value with the area under the curve values equal to 0.77 and 0.78 for test cohort1 and cohort2, respectively. The patients predicted to have DCB showed improved median progression-free survival (mPFS) and median overall survival (mOS) than those predicted to have non-durable clinical benefit.

A machine learning algorithm with subclonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity

Human leukocyte antigen loss of heterozygosity (HLA LOH) allows cancer cells to escape immune recognition by deleting HLA alleles, causing the suppressed presentation of tumor neoantigens. Despite its importance in immunotherapy response, few methods exist to detect HLA LOH, and their accuracy is not well understood. Here, we develop DASH (Deletion of Allele-Specific HLAs), a machine learning-based algorithm to detect HLA LOH from paired tumor-normal sequencing data. With cell line mixtures, we demonstrate increased sensitivity compared to previously published tools. Moreover, our patient-specific digital PCR validation approach provides a sensitive, robust orthogonal approach that could be used for clinical validation. Using DASH on 610 patients across 15 tumor types, we find that 18% of patients have HLA LOH. Moreover, we show inflated HLA LOH rates compared to genome-wide LOH and correlations between CD274 (encodes PD-L1) expression and microsatellite instability status, suggesting the HLA LOH is a key immune resistance strategy.

Human leukocyte antigen loss of heterozygosity (HLA LOH) is an important mechanism of immune escape in patients with cancer. Here the authors design and validate a machine learning algorithm with subclonal sensitivity for the identification of HLA LOH from paired tumor-normal sequencing data.

Central Role of the Antigen-Presentation and Interferon-γ Pathways in Resistance to Immune Checkpoint Blockade

Resistance to immunotherapy is due in some instances to the acquired stealth mechanisms of tumor cells that lose expression of MHC class I antigen–presenting molecules or downregulate their class I antigen–presentation pathways. Most dramatically, biallelic β2-microglobulin (B2M) loss leads to complete loss of MHC class I expression and to invisibility to CD8+ T cells. MHC class I expression and antigen presentation are potently upregulated by interferon-γ (IFNγ) in a manner that depends on IFNγ receptor (IFNGR) signaling via JAK1 and JAK2. Mutations in these molecules lead to IFNγ unresponsiveness and mediate loss of recognition and killing by cytotoxic T lymphocytes. Loss of MHC class I augments sensitivity of tumor cells to be killed by natural killer (NK) lymphocytes, and this mechanism could be exploited to revert resistance, for instance, with interleukin-2 (IL-2)-based agents. Moreover, in some experimental models,potent local type I interferon responses, such as those following intratumoral injection of Toll-like receptor 9 (TLR9) or TLR3 agonists, revert resistance due to mutations of JAKs.

Pre-treatment serum albumin and mutational burden as biomarkers of response to immune checkpoint blockade

The effects of cytokine and protein stabilizing carriers, such as serum albumin, on tumor response to immune checkpoint blockade (ICB) is not well understood. By examining 1714 patients across 16 cancer types, we found that high pretreatment serum albumin level predicts favorable tumor radiographic response following ICB treatment in a dose-dependent fashion. Serum albumin is a candidate biomarker that can be combined with tumor mutational burden (TMB) for additional predictive capacity, and the tumor response rate to ICB was ~49% in the albumin-high/TMB-high group.

The microbial metabolite trimethylamine N-oxide promotes antitumor immunity in triple-negative breast cancer

Immunotherapy has achieved limited success in patients with triple-negative breast cancer (TNBC), an aggressive disease with a poor prognosis. Commensal microbiota have been proven to colonize the mammary gland, but whether and how they modulate the tumor microenvironment remains elusive. We performed a multiomics analysis of a cohort of patients with TNBC (n = 360) and found genera under Clostridiales, and the related metabolite trimethylamine N-oxide (TMAO) was more abundant in tumors with an activated immune microenvironment. Patients with higher plasma TMAO achieved better responses to immunotherapy. Mechanistically, TMAO induced pyroptosis in tumor cells by activating the endoplasmic reticulum stress kinase PERK and thus enhanced CD8⁺ T cell-mediated antitumor immunity in TNBC in vivo. Collectively, our findings offer new insights into microbiota-metabolite-immune crosstalk and indicate that microbial metabolites, such as TMAO or its precursor choline, may represent a novel therapeutic strategy to promote the efficacy of immunotherapy in TNBC.

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose¹. Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions.

Computational mining of MHC class II epitopes for the development of universal immunogenic proteins

The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts.

Class I/Class II HLA Evolutionary Divergence Ratio Is an Independent Marker Associated With Disease-Free and Overall Survival After Allogeneic Hematopoietic Stem Cell Transplantation for Acute Myeloid Leukemia

Class I Human Leukocyte Antigen (HLA) evolutionary divergence (HED) is a metric which reflects immunopeptidome diversity and has been associated with immune checkpoint inhibitor responses in solid tumors. Its impact and interest in allogeneic hematopoietic stem cell transplantation (HCT) have not yet been thoroughly studied. This study analyzed the clinical and immune impact of class I and II HED in 492 acute myeloid leukemia (AML) recipients undergoing HCT. The overall cohort was divided into a training (n=338) and a testing (n=132) set. Univariate cox screening found a positive impact of a high class I HED and a negative impact of a high class II HED on both disease-free (DFS) and overall survival (OS). These results were combined in a unique marker, class I/class II HED ratio, and assessed in the testing cohort. The final multivariate cox model confirmed the positive impact of a high versus low class I/class II HED ratio on both DFS (Hazard Ratio (HR) 0.41 [95% CI 0.2-0.83]; p=0.01) and OS (HR 0.34 [0.19-0.59]; p<0.001), independently of HLA matching and other HCT parameters. No significant association was found between the ratio and graft-versus-host disease (GvHD) nor with neutrophil and platelet recovery. A high class I HED was associated with a tendency for an increase in NK, CD8 T-cell, and B cell recovery at 12 months. These results introduce HED as an original and independent prognosis marker reflecting immunopeptidome diversity and alloreactivity after HCT.

Association between Antibiotic Exposure and Systemic Immune Parameters in Cancer Patients Receiving Checkpoint Inhibitor Therapy

Antibiotic administration is associated with worse clinical outcomes and changes to the gut microbiome in cancer patients receiving immune checkpoint inhibitors (ICI). However, the effects of antibiotics on systemic immune function are unknown. We, therefore, evaluated antibiotic exposure, therapeutic responses, and multiplex panels of 40 serum cytokines and 124 antibodies at baseline and six weeks after ICI initiation, with p < 0.05 and false discovery rate (FDR) < 0.2 considered significant. A total of 251 patients were included, of whom the 135 (54%) who received antibiotics had lower response rates and shorter survival. Patients who received antibiotics prior to ICI initiation had modestly but significantly lower baseline levels of nucleolin, MDA5, c-reactive protein, and liver cytosol antigen type 1 (LC1) antibodies, as well as higher levels of heparin sulfate and Matrigel antibodies. After ICI initiation, antibiotic-treated patients had significantly lower levels of MDA5, CENP.B, and nucleolin antibodies. Although there were no clear differences in cytokines in the overall cohort, in the lung cancer subset (53% of the study population), we observed differences in IFN-γ, IL-8, and macrophage inflammatory proteins. In ICI-treated patients, antibiotic exposure is associated with changes in certain antibodies and cytokines. Understanding the relationship between these factors may improve the clinical management of patients receiving ICI.