Abstract Background Immune checkpoint inhibitors improve outcomes in clear cell renal cell carcinoma (ccRCC), yet most patients do not achieve durable responses due in part to insufficient tumor antigenicity. While neoantigen vaccines have shown promising early-phase results in ccRCC, their patient-specific design limits broad applicability and poses additional challenges in low mutational burden tumors, where targetable epitopes are scarce. Human endogenous retroviruses (hERVs), which comprise ∼8% of the human genome, can become aberrantly expressed in cancer and represent a source of shared, tumor-specific antigens; however, the extent to which they expand the limited antigenic landscape of not only ccRCC, but non-ccRCC subtypes, remains largely unexplored. We hypothesized that a subset of these aberrantly expressed hERVs provide a new public source of immunogenic peptides that can be prioritized as candidates for mRNA vaccine development. Methods We performed a pan-cancer (TCGA) analysis of 3,173 putative hERV loci from the Vargiu et al (Retrovirology, 2016) reference to identify hERVs upregulated across all cancer types, with a focus on kidney cancer subtypes. Candidates were prioritized using a scoring framework that enriched for hERVs with high tumor expression and minimal expression in normal tissues. From prioritized loci, six-frame translation was used to generate candidate open reading frames (ORFs), which were filtered and integrated with polysome sequencing data from RCC cell lines to identify translation-supported regions. Candidate peptides were evaluated for HLA binding using complimentary antigen prediction pipelines (e.g., HLAthena, netMHCpan) for various HLA alleles. To assess immunogenicity, we developed a multi-epitope hERV-targeting mRNA vaccine and evaluated antigen-specific immune responses in HLA-A11 transgenic mouse models. Results TCGA analysis combined with our scoring framework identified ≥25 unique hERV vaccine candidates per RCC subtype, with substantial overlap between ccRCC and papillary RCC (pRCC) and a distinct profile in chromophobe RCC (chRCC). Within ccRCC-prioritized hERV candidates, ORFs were generated via six-frame translation, filtered for canonical structure, and integrated with polysome sequencing data from three ccRCC cell lines to identify regions with strong translational support. This reduced 294,927 candidate ORFs to 805 high-confidence ORFs from 18 unique hERV loci, including recently described HIF-2α–regulated hERVs 4818 and 5875. HLA binding prediction identified numerous high-affinity candidate peptides across all HLA alleles (e.g., HLA-A*02, HLA-A*11), with some loci yielding >80 predicted binders for HLA-A*11 alone. Reanalysis of published immunopeptidomics datasets identified multiple peptides mapping to prioritized hERV loci, supporting endogenous processing and presentation. A pilot study using a multi-epitope mRNA vaccine encoding previously described hERV-derived peptides in a prophylactic setting elicited robust tetramer-positive, antigen-specific T cell responses in HLA-A11 transgenic mice. Compared with a peptide-based counterpart, mRNA vaccination generated superior responses, with approximately threefold and twofold higher frequencies of tetramer-positive CD8+ T cells in the spleen and vaccine-draining lymph nodes, respectively. Conclusions We present an integrative framework to identify translated hERV-derived antigens across RCC, expanding on prior work in ccRCC by identifying both known and novel immunogenic candidate peptides with evidence of translation and strong predicted HLA binding. mRNA vaccination using previously described hERV-derived peptides elicited robust antigen-specific CD8+ T cell responses, outperforming peptide vaccination. Our findings also provide initial insight into the hERV landscape in pRCC and chRCC, supporting further investigation. Future work will evaluate newly predicted peptides in multi-epitope mRNA vaccines and test their anti-tumor efficacy in vivo. DOD CDMRP Funding yes
F. Scallo, A. Dighe, Josephine Burdekin et al.· The Oncologist· 0 citations
Abstract Background The current standard of care for advanced RCC is ICI-based combination therapies. However, most patients with advanced RCC develop disease progression despite ICI treatment, suggesting a lack of durable immune response. Although a lack of T cell infiltration or the presence of non-tumor-reactive “bystander” T cells are hypothesized mechanisms of ICI resistance across tumor types, therapeutic resistance in RCC may still occur in the presence of abundant infiltration of tumor-specific CD8+ T cells. We therefore investigated whether CD8+ T cell phenotype in the RCC tumor microenvironment (TME) impacts ICI response or resistance. Methods 70 tumor samples from 63 RCC patients were collected before (n = 48) or after (n = 22) therapies (VEGFi, n = 9; ICI monotherapy, n = 20; ICI combination, n = 26; others, n = 15). 11 samples were collected from patients without tumors. RCC variants included 59 clear cell and 11 non-clear cell samples. 18 were labeled as clinical benefit and 11 as no-clinical benefit. Single-cell RNA sequencing (10x Genomics) was performed on these samples to generate a transcriptome of the RCC TME. Graph-based clustering identified cell type populations, which were annotated with known lineage genes. Non-negative matrix factorization (NMF) identified gene programs within exhausted CD8+ T cells (Tex). Differential gene expression analysis determined the most differentially expressed genes between resident memory Tex and other cell populations. Results Within CD8+ T cells, Tex cells were identified through expression of TOX, PDCD1 (PD-1), and HAVCR2 (TIM-3). NMF generated 4 gene programs within Tex cells, expressing markers for immediate early genes (JUNB, FOS), exhaustion/activation (GZMK, CD74, LAG3), tissue residency (GZMH, ITGAE, IL7R), and stress response (HSPA1A, HSPA6). The tissue residency program was associated with resistance to ICI therapy (p = 0.05); this association was only found in samples with abundant tumor-specific CD8+ T cells. Differential expression between resident memory Tex (Tex-RM) and other cell types generated a signature of 10 markers that were most highly expressed in Tex-RM. Response and survival data of external bulk RNA-seq cohorts were analyzed. A signature score subtracting for Tex-RM signature was calculated (normalized to overall abundance of Tex cells by signature analysis), which was significantly higher in patients with progressive disease than those with complete/partial response (p = 0.0046), specifically for patients receiving ICI-based therapies. Additionally, survival analysis revealed that ICI-based patients with a higher (top 25%) signature score had significantly worse progression free survival (PFS; p = 0.0048) as well as overall survival (p = 0.0069) with ICI. For ICI-treated patients, the Tex-RM signature score was associated with worse PFS, with a hazard ratio of 2.1 (90% CI [1.3, 3.25]). There was no significant impact on patients receiving TKI monotherapy. Conclusions Through scRNA-seq analysis, we identify a tissue residency gene program in Tex cells associated with non-response to immunotherapy. A signature derived from this program was additionally shown to predict significantly worse response and outcomes for patients receiving ICI-based therapies within a group of bulk RNA-seq clinical trial cohorts. This study provides a framework for using scRNA-seq to identify mechanisms of ICI resistance in RCC and nominates resident memory exhausted CD8+ T cells as a targetable subset of cells to improve CD8+ T cell-mediated anti-tumor immunity. DOD CDMRP Funding yes
Rishabh Rout, S. Kashima, M. Hugaboom et al.· The Oncologist· 0 citations
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