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Bassani-Sternberg, M.

Publications and source records attributed to Bassani-Sternberg, M..

At least 19 recordsLinked to original sources

Identification of a large class of cancer-germline microproteins as a source of immunotherapeutic targets

Classical cancer germline-antigens (CGAs) are proteins that are expressed in the male germinal line but not in somatic tissues, and that can also become expressed in tumors. However, the vast majority of testis-specific transcripts are long non-coding RNAs (lncRNAs) rather than protein-coding genes. Since recent studies have shown that many lncRNAs contain non-canonical open reading frames (ncORFs) that are translated into small proteins, or microproteins, there could be a large class of non-canonical cancer-germline antigens (ncCGAs) that remains to be discovered. Here, we integrate ribosome profiling from human testis and cancer cell lines with paired tumor/normal transcriptomes from 917 patients across eight common cancer types to define a comprehensive catalog of ncCGAs. This set comprises 235 ncCGAs encoded by lncRNAs or mRNA untranslated regions (5UTRs and 3UTRs), compared to 192 canonical CGAs (cCGAs) with similar expression patterns. We show that ncCGAs are evolutionary young, consistent with recent de novo emergence in the rapidly evolving male germline. Moreover, a large fraction is expressed across multiple patients and cancer types, indicating recurrent reactivation mechanisms in tumors. We further find that ncCGAs are frequently located in cancer-amplified regions or associated with MYC or E2F-regulated pathways, which may explain their expression in cancer. Finally, we provide strong evidence that a subset of ncCGAs give rise to potentially immunogenic HLA class I bound peptides. Together, our results describe a previously unexplored class of tumor-restricted antigens with potential applications in cancer immunotherapy.

cancer biology↗

Tissue specificity and chromosomal alterations shape divergent immune programs in HRD tumors

Homologous recombination deficiency (HRD) activates pro-inflammatory cGAS/STING signaling, positioning it as a biomarker for combining immune checkpoint blockade (ICB) and PARP inhibition (PARPi). However, the consequences of HRD on the immune landscape across cancers remain unclear. Here, we applied a pan-cancer HRD classifier to >10,000 tumors from The Cancer Genome Atlas and uncovered striking heterogeneity in immune activity. Compared to HR-proficient tumors, HRD tumors showed elevated inflammation in breast, ovarian, and endometrial cancers. These tumors exhibited robust activation of innate and adaptive immune pathways (IFN, NF-{kappa}B) and transcriptional hallmarks of senescence, angiogenesis, and adenosine signaling. In contrast, lung, head and neck, and melanoma HRD tumors displayed suppressed inflammation and evidence of immune escape through large-scale loss-of-heterozygosity (LOH) at IFNA/B, STING, and other loci. These tumors also frequently presented HLA LOH and oncogene amplifications, suggesting selection under immune pressure and replication stress. Together, our study resolves HRD tumors into two immune archetypes, immune-inflamed and immune-evasive, linked to chromosomal instability and lineage, informing biomarker-driven evaluation of immune checkpoint blockade/PARPi combinatorial therapies.

genomics↗

Detection of human unannotated microproteins by mass spectrometry-based proteomics: a community assessment

Thousands of short open reading frames (sORFs) are translated outside of annotated coding sequences. Recent studies have pioneered searching for sORF-encoded microproteins in mass spectrometry (MS)- based proteomics and peptidomics datasets. Here, we assessed literature-reported MS-based identifications of unannotated human proteins. We find that studies vary by three orders of magnitude in the number of unannotated proteins they report. Of nearly 10,000 reported sORF-encoded peptides, 96% were unique to a single study, and 12% mapped to annotated proteins or proteoforms. Manual curation of a benchmark dataset of 406 manually evaluated spectra from 204 sORF-encoded proteins revealed large variation in peptide-spectrum match (PSM) quality between studies, with immunopeptidomics studies generally reporting higher quality PSMs than conventional enzymatic digests of whole cell lysates. We estimate that 65% of predicted sORF-encoded protein detections in immunopeptidomics studies were supported by high-quality PSMs versus 7.8% in non-immunopeptidomics datasets. Our work stresses the need for standardized protocols and analysis workflows to guide future advancements in microprotein detection by MS towards uncovering how many human microproteins exist.

genomics↗

Double-stranded RNA responses, neoantigen presentation and suppression of hepatocellular carcinoma through NMD inhibition via endonuclease SMG6

Nonsense-mediated mRNA decay (NMD) eliminates aberrant transcripts to maintain transcriptome integrity, yet its broader physiological roles remain incompletely defined. Here, using a liver-specific, inducible mouse model, we selectively inactivate the endonuclease SMG6 - the terminal effector of NMD - in a genetic model of hepatocellular carcinoma (HCC). SMG6 loss completely prevents tumour development and triggers robust innate and adaptive immune responses. Mechanistically, SMG6 inactivation causes the cytoplasmic accumulation of endogenous double-stranded RNAs (dsRNAs), leading to type I interferon induction via the dsRNA sensor MDA5 and revealing an unexpected physiological role for NMD in maintaining dsRNA homeostasis. In parallel, stabilisation and translation of normally degraded transcripts generate non-canonical MHC-I-presented peptides that elicit potent CD8+ T-cell responses. These findings identify SMG6-dependent NMD as a central gatekeeper that restrains dsRNA-driven antiviral signalling and suppresses immunogenic transcript expression. Our work establishes selective SMG6 inhibition as a promising strategy to enhance tumour immunogenicity and suggests that targeting terminal NMD activity could represent a conceptually distinct avenue for cancer immunotherapy.

cancer biology↗

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

molecular biology↗

Myeloid cell networks determine reinstatement of original immune environments in recurrent ovarian cancer

Immunotherapy has produced disappointing results in recurrent ovarian cancer (OC). However, the prognostic value of tumour-infiltrating lymphocytes (TILs) is largely based on the analysis of treatment-naive tumours. To understand the immunobiology of recurrent cancers, and their evolution, we profiled 170 patient-matched primary-recurrent OC samples from 69 patients of two independent cohorts. By capturing heterogeneous TIL distributions, we identified four immune phenotypes associated with differential prognosis, TILs states and TILs:myeloid networks, which dictate malignant evolution after chemotherapy and recurrence. Notably, recurrent tumours recapitulate the immunogenic patterns of original cancers. Mirroring inflamed human OC, preclinical recurrent Brca1mut tumours maintained activated TILs:dendritic cells (DCs) niches and immunostimulatory tumour-associated macrophages (TAMs). Conversely, recurrent Brca1wt tumours displayed loss of TILs:DCs niches and accumulated immunosuppressive myeloid networks featuring Trem2/ApoEhigh TAMs and Nduf4l2high/Galectin3high malignant states. Our study highlights that persistent immunogenicity in recurrent OC is governed by the crosstalk between dissimilar myeloid cells and TILs, which is BRCA-dependent.

immunology↗

TCR-engineered T-cells directed against Ropporin-1 constitute a safe and effective treatment for triple-negative breast cancer in near-clinical models

Triple-negative breast cancer (TNBC) shows an urgent need for new therapies. We discovered Ropporin-1 (ROPN1) as a target to treat TNBC with T-cells. ROPN1 showed high and homogenous expression in 90% of primary and metastatic TNBC but not in healthy tissues. HLA-A2-binding peptides were detected via immunopeptidomics and predictions and used to retrieve T-cell receptors (TCRs) from naive repertoires. Following gene introduction into T-cells and stringent selection, we retrieved a highly specific TCR directed against the epitope FLYTYIAKV that did not recognize non-cognate epitopes from alternative source proteins. Notably, this TCR mediated killing of three-dimensional tumoroids in vitro and tumor cells in vivo and outperformed standard-of-care drugs. Finally, the T-cell product expressing this TCR and manufactured using a clinical protocol fulfilled standard safety and efficacy assays. Collectively, we have identified and preclinically validated ROPN1 as a target and anti-ROPN1 TCR T-cells as a treatment for the vast majority of TNBC patients.

immunology↗

Tumor-reactive clonotype dynamics underlying clinical response to TIL therapy in melanoma

The profiles, specificity and dynamics of tumor-specific clonotypes that are associated with clinical response to adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TILs) remain unclear. Using single-cell RNA/TCR-sequencing, we tracked TIL clonotypes from baseline tumors to ACT products and post-ACT blood and tumor samples in melanoma patients treated with TIL-ACT. Patients with clinical responses had baseline tumors enriched in tumor-reactive TILs, which were more effectively mobilized upon in vitro expansion, yielding products with higher numbers of tumor-specific CD8+ cells, which also preferentially infiltrated tumors post-ACT. Conversely, lack of clinical responses was associated with tumors devoid of tumor-reactive resident clonotypes, and with cell products mostly composed of blood-borne clonotypes mainly persisting in blood but not in tumors post-ACT. Upon expansion, tumor-specific TILs lost the specific signatures of states originally exhibited in tumors, including exhaustion, and in responders acquired an intermediate exhausted effector state after tumor engraftment, revealing important functional cell reinvigoration.

cancer biology↗

What can Ribo-seq and proteomics tell us about the non-canonical proteome?

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from [~]19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding". In briefThe human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting. HighlightsO_LICombined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products. C_LIO_LIRibo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results. C_LIO_LINon-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations. C_LIO_LIA framework for standardized non-canonical ORF evidence will advance the research field. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/541049v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@4878d0org.highwire.dtl.DTLVardef@1f3c9e4org.highwire.dtl.DTLVardef@4ba1f7org.highwire.dtl.DTLVardef@17695a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

KRAB zinc finger proteins ZNF587/ZNF417 protect lymphoma cells from replicative stress-induced inflammation

Heterochromatin loss and genetic instability enhance cancer progression by favoring clonal diversity, yet uncontrolled replicative stress can lead to mitotic catastrophe and inflammatory responses promoting immune rejection. KRAB-containing zinc finger proteins (KZFPs) are epigenetic modulators, which for many control heterochromatin at transposable element (TE)-embedded regulatory sequences. We identified a cluster of 18 KZFPs associated with poor prognosis in diffuse large B cell lymphoma (DLBCL). We found their upregulation to correlate with increased copy number alterations and suppression of immune responses in tumor samples. Upon depleting two that target evolutionarily recent TEs, the primate-specific ZNF587 and ZNF417 paralogs, the proliferation of DLBCL cell lines was drastically impaired and replicative stress abruptly induced with marked alterations of the chromatin landscape and multiplication of DNA replication origins. Furthermore, ZNF587/417 knockdown upregulated interferon/inflammatory-related genes through activation of the cGAS-STING DNA sensing pathway, augmented the susceptibility of tumor cells to macrophage-mediated phagocytosis, and modified their immunogenicity through an increased surface expression of HLA-I and reshuffling of their immunopeptidome. ZNF587 and ZNF417 are thus pro-oncogenic factors allowing for higher degrees of genetic instability through attenuation of replicative stress and secondary inflammation, an influence that likely facilitates the clonal expansion, diversification, and immune evasion of cancer cells.

cancer biology↗

Tumor Microenvironment Cellular Crosstalk Predicts Response to Adoptive TIL Therapy in Melanoma

Adoptive cell therapy (ACT) using ex vivo expanded tumor-infiltrating T lymphocytes (TILs) can mediate responses in metastatic melanoma, but long-term efficacy remains limited to a fraction of patients. Here we interrogated tumor-microenvironment (TME) cellular states and interactions of longitudinal samples from 13 metastatic melanoma patients treated with TIL-ACT in our clinical study (NCT03475134). We performed single-cell RNA-seq and spatial proteomic analyses in pre- and post-ACT tumor tissues and showed that responders exhibited higher tumor cell-intrinsic immunogenicity. Also, endogenous CD8+ TILs and myeloid cells of responders were characterized by increased cytotoxicity, exhaustion and costimulation and type-I IFN signaling, respectively. Cell-cell interaction prediction analyses corroborated by spatial neighborhood analyses revealed that responders have rich baseline intratumoral and stromal tumor-reactive T-cell networks with activated myeloid populations. Successful TIL-ACT therapy further reprogrammed the myeloid compartment and increased TIL-myeloid networks. Our systematic target discovery study reveals CD8+ T-cell network-based biomarkers that could improve patient selection and guide the design of ACT clinical trials. One-Sentence SummaryResponse to adoptive TIL therapy in melanoma is determined by CD8+ TIL-myeloid cell networks

immunology↗

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes

CD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on MHC-II molecules. The high polymorphism of MHC-II genes represents an important hurdle towards accurate prediction and identification of CD4+ T-cell epitopes in different individuals and different species. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across human, mouse, cattle and chicken. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse binding mode in MHC-II ligands. We then developed a machine learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T-cell epitopes, and enabled us to discover and characterize several viral and bacterial epitopes following the aforementioned reverse binding mode.

immunology↗

Multifactorial remodeling of the cancer immunopeptidome by interferon gamma

IFN{gamma} alters the immunopeptidome presented on HLA class I (HLA-I), and its activity on cancer cells is known to be important for effective immunotherapy responses. We performed proteomic analyses of untreated and IFN{gamma}-treated colorectal cancer patient-derived organoids (PDOs) and combined this with transcriptomic and HLA-I immunopeptidomics data to dissect mechanisms that lead to remodeling of the immunopeptidome through IFN{gamma}. IFN{gamma}-induced changes in the abundance of source proteins, switching from the constitutive- to the immunoproteasome, and differential upregulation of different HLA alleles explained some, but not all, observed peptide abundance changes. By selecting for peptides which increased or decreased the most in abundance, but originated from proteins with limited abundance changes, we discovered that the amino acid composition of presented peptides also influences whether a peptide is up- or downregulated on HLA-I through IFN{gamma}. The presence of proline within the peptide core was most strongly associated with peptide downregulation. This was validated in an independent dataset. Proline substitution in relevant core positions did not influence the predicted HLA-I binding affinity or stability, indicating that proline effects on peptide processing may be most relevant. Understanding the multiple factors that influence the abundance of peptides presented on HLA-I in the absence or presence of IFN{gamma} is important to identify the best targets for antigen-specific cancer immunotherapies such as vaccines or T-cell receptor engineered therapeutics.

cancer biology↗

Deciphering the landscape of phosphorylated HLA-II ligands

CD4+ T-cell activation in infectious diseases and cancer is governed by the recognition of peptides presented on class II human leukocyte antigen (HLA-II) molecules. Therefore, HLA-II ligands represent promising targets for vaccine design and personalized cancer immunotherapy. Much work has been done to identify and predict unmodified peptides presented on HLA-II molecules. However, little is known about the presentation of phosphorylated HLA-II ligands. Here, we analyzed Mass Spectrometry HLA-II peptidomics data and identified 1,113 unique phosphorylated HLA-II ligands. This enabled us to precisely define phosphorylated binding motifs for more than 30 common HLA-II alleles and to explore various molecular properties of phosphorylated peptides. Our data were further used to develop the first predictor of phosphorylated peptide presentation on HLA-II molecules.

immunology↗

Bedside formulation of a personalized multi-neoantigen vaccine against mammary carcinoma

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/440778v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@88f5d3org.highwire.dtl.DTLVardef@1c32c71org.highwire.dtl.DTLVardef@9abbedorg.highwire.dtl.DTLVardef@a7f41a_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Individualized neoantigen vaccination against mammary carcinoma C_FIG BackgroundHarnessing the immune system to purposely recognize and destroy tumours represents a significant breakthrough in clinical oncology. Nonsynonymous mutations (neoantigenic peptides) were identified as powerful cancer targets. This knowledge can be exploited for further improvements of active immunotherapies, including cancer vaccines as T cells specific for neoantigens are not attenuated by immune tolerance mechanism and do not harm healthy tissues. The current study aimed at developing an optimized multi-target vaccine using short or long neoantigenic peptides utilizing virus-like particles (VLPs) as an efficient vaccine platform. MethodsHere we identified mutations of murine mammary carcinoma cells by integrating mass spectrometry-based immunopeptidomics and whole exome sequencing. Neoantigenic peptides were synthesized and covalently linked to virus-like nanoparticles using a Cu-free click-chemistry method for easy preparation of vaccines against mouse mammary carcinoma. ResultsAs compared to short peptides, vaccination with long peptides was superior in the generation of neoantigen-specific CD4+ and CD8+ T cells which readily produced IFN-{gamma} and TNF-. The resulting anti-tumour effect was associated with favourable immune re-polarization in the tumour microenvironment through reduction of myeloid-derived suppressor cells. Vaccination with long neoantigenic peptides also decreased post-surgical tumour recurrence and metastases, and prolonged mouse survival, despite the tumours low mutational burden. ConclusionIntegrating mass spectrometry-based immunopeptidomics and whole exome-sequencing is an efficient technique for identifying neoantigenic peptides. A multi-target VLP-based vaccine shows a promising anti-tumour results in an aggressive murine mammary carcinoma cell line. Future clinical application using this strategy is readily feasible and practical, as click-chemistry coupling of personalized synthetic peptides to the nanoparticles can be done at the bedside directly before injection.

immunology↗

Mass spectrometry based immunopeptidomics leads to robust predictions of phosphorylated HLA class I ligands

The presentation of peptides on class I human leukocyte antigen (HLA-I) molecules plays a central role in immune recognition of infected or malignant cells. In cancer, non-self HLA-I ligands can arise from many different alterations, including non-synonymous mutations, gene fusion, cancer-specific alternative mRNA splicing or aberrant post-translational modifications. Identifying HLA-I ligands remains a challenging task that requires either heavy experimental work for in-vivo identification or optimized bioinformatics tools for accurate predictions. To date, no HLA-I ligand predictor includes post-translational modifications. To fill this gap, we curated phosphorylated HLA-I ligands from several immunopeptidomics studies (including six newly measured samples) covering 72 HLA-I alleles, and retrieved a total of 2,066 unique phosphorylated peptides. We then expanded our motif deconvolution tool to identify precise binding motifs of phosphorylated HLA-I ligands. Our results reveal a clear enrichment of phosphorylated peptides among HLA-C ligands and demonstrate a prevalent role of both HLA-I motifs and kinase motifs on the presentation of phosphorylated peptides. This data further enabled us to develop and validate the first predictor of interactions between HLA-I molecules and phosphorylated peptides.

immunology↗

Integrated Proteogenomic Deep Sequencing and Analytics Accurately Identify Non-Canonical Peptides in Tumor Immunopeptidomes

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides that derive from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass-spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides and of an immunogenic peptide from a downstream reading frame in the melanoma stem cell marker gene ABCB5. It holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.

cancer biology↗

Deep motif deconvolution of HLA-II peptidomes for robust class II epitope predictions

CD4 T cells are key for priming and regulating immune recognition of infected and cancer cells, but predictions of class II epitopes have limited accuracy. We combined unbiased Mass Spectrometry-based HLA-II peptidomics with a novel motif deconvolution algorithm to profile and analyze a total of 99265 unique HLA-II ligands. Our work demonstrates substantial improvement in the definition of HLA-II binding motifs and enhanced accuracy in class II epitope predictions.

immunology↗