Molecular assessment of intratumoral immune cell subsets and potential mechanisms of resistance to odronextamab, a CD20×CD3 bispecific antibody, in patients with relapsed/refractory B-cell non-Hodgkin lymphoma.

BACKGROUND: Patients with relapsed/refractory B-cell non-Hodgkin lymphoma (R/R B-NHL) have a significant need for effective treatment options. Odronextamab is an Fc-silenced, human, CD20×CD3 bispecific antibody that targets CD20-expressing cells via T-cell-mediated cytotoxicity independent of T-cell/major histocompatibility complex interaction. Phase I results in patients with R/R B-NHL demonstrated that odronextamab monotherapy could achieve deep and durable responses with a generally manageable safety profile (ELM-1; NCT02290951). As part of a biomarker analysis of the same study, we investigated potential biomarkers and mechanisms of resistance to odronextamab. METHODS: Patients with R/R B-NHL enrolled in ELM-1 received one time per week doses of intravenous odronextamab for 4×21 day cycles, then doses every 2 weeks thereafter. Patient tumor biopsies were obtained at baseline, on-treatment, and at progression. Immune cell markers were analyzed by immunohistochemistry, flow cytometry, single-cell RNA sequencing, and whole genome sequencing. RESULTS: Baseline tumor biopsies showed that almost all patients had high proportions of B cells that expressed the CD20 target antigen, whereas expression of other B-cell surface antigens (CD19, CD22, CD79b) was more variable. Responses to odronextamab in patients with diffuse large B-cell lymphoma were not related to the relative level of baseline CD20 expression, cell of origin, or high-risk molecular subtype. A potential link was observed between greater tumor programmed cell death-ligand 1 expression and increased likelihood of response to odronextamab. Similarly, a trend was observed between clinical response and increased levels of CD8 T cells and regulatory T cells at baseline. We also identified an on-treatment pharmacodynamic shift in intratumoral immune cell subsets. Finally, loss of CD20 expression through inactivating gene mutations was identified as a potential mechanism of resistance in patients who were treated with odronextamab until progression, as highlighted in two detailed patient cases reported here. CONCLUSIONS: This biomarker analysis expands on clinical findings of odronextamab in patients with R/R B-NHL, providing verification of the suitability of CD20 as a therapeutic target, as well as evidence for potential mechanisms of action and resistance.

Intratumoral dendritic cell-CD4+ T helper cell niches enable CD8+ T cell differentiation following PD-1 blockade in hepatocellular carcinoma.

Despite no apparent defects in T cell priming and recruitment to tumors, a large subset of T cell rich tumors fail to respond to immune checkpoint blockade (ICB). We leveraged a neoadjuvant anti-PD-1 trial in patients with hepatocellular carcinoma (HCC), as well as additional samples collected from patients treated off-label, to explore correlates of response to ICB within T cell-rich tumors. We show that ICB response correlated with the clonal expansion of intratumoral CXCL13+CH25H+IL-21+PD-1+CD4+ T helper cells ("CXCL13+ TH") and Granzyme K+ PD-1+ effector-like CD8+ T cells, whereas terminally exhausted CD39hiTOXhiPD-1hiCD8+ T cells dominated in nonresponders. CD4+ and CD8+ T cell clones that expanded post-treatment were found in pretreatment biopsies. Notably, PD-1+TCF-1+ (Progenitor-exhausted) CD8+ T cells shared clones mainly with effector-like cells in responders or terminally exhausted cells in nonresponders, suggesting that local CD8+ T cell differentiation occurs upon ICB. We found that these Progenitor CD8+ T cells interact with CXCL13+ TH within cellular triads around dendritic cells enriched in maturation and regulatory molecules, or "mregDC". These results suggest that discrete intratumoral niches that include mregDC and CXCL13+ TH control the differentiation of tumor-specific Progenitor exhasuted CD8+ T cells following ICB.

Non-cancer-related pathogenic germline variants and expression consequences in ten-thousand cancer genomes.

BACKGROUND: DNA sequencing is increasingly incorporated into the routine care of cancer patients, many of whom also carry inherited, moderate/high-penetrance variants associated with other diseases. Yet, the prevalence and consequence of such variants remain unclear. METHODS: We analyzed the germline genomes of 10,389 adult cancer cases in the TCGA cohort, identifying pathogenic/likely pathogenic variants in autosomal-dominant genes, autosomal-recessive genes, and 59 medically actionable genes curated by the American College of Molecular Genetics (i.e., the ACMG 59 genes). We also analyzed variant- and gene-level expression consequences in carriers. RESULTS: The affected genes exhibited varying pan-ancestry and population-specific patterns, and overall, the European population showed the highest frequency of pathogenic/likely pathogenic variants. We further identified genes showing expression consequence supporting variant functionality, including altered gene expression, allelic specific expression, and mis-splicing determined by a massively parallel splicing assay. CONCLUSIONS: Our results demonstrate that expression-altering variants are found in a substantial fraction of cases and illustrate the yield of genomic risk assessments for a wide range of diseases across diverse populations.

Mutational bias and the protein code shape the evolution of splicing enhancers.

Exonic splicing enhancers (ESEs) are enriched in exons relative to introns and bind splicing activators. This study considers a fundamental question of co-evolution: How did ESE motifs become enriched in exons prior to the evolution of ESE recognition? We hypothesize that the high exon to intron motif ratios necessary for ESE function were created by mutational bias coupled with purifying selection on the protein code. These two forces retain certain coding motifs in exons while passively depleting them from introns. Through the use of simulations, genomic analyses, and high throughput splicing assays, we confirm the key predictions of this hypothesis, including an overlap between protein and splicing information in ESEs. We discuss the implications of mutational bias as an evolutionary driver in other cis-regulatory systems.

Future directions for high-throughput splicing assays in precision medicine.

Classification of variants of unknown significance is a challenging technical problem in clinical genetics. As up to one-third of disease-causing mutations are thought to affect pre-mRNA splicing, it is important to accurately classify splicing mutations in patient sequencing data. Several consortia and healthcare systems have conducted large-scale patient sequencing studies, which discover novel variants faster than they can be classified. Here, we compare the advantages and limitations of several high-throughput splicing assays aimed at mitigating this bottleneck, and describe a data set of ~5,000 variants that we analyzed using our Massively Parallel Splicing Assay (MaPSy). The Critical Assessment of Genome Interpretation group (CAGI) organized a challenge, in which participants submitted machine learning models to predict the splicing effects of variants in this data set. We discuss the winning submission of the challenge (MMSplice) which outperformed existing software. Finally, we highlight methods to overcome the limitations of MaPSy and similar assays, such as tissue-specific splicing, the effect of surrounding sequence context, classifying intronic variants, synthesizing large exons, and amplifying complex libraries of minigene species. Further development of these assays will greatly benefit the field of clinical genetics, which lack high-throughput methods for variant interpretation.

MMSplice: modular modeling improves the predictions of genetic variant effects on splicing.

Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI5 exon skipping prediction challenge. The MMSplice modules are neural networks scoring exon, intron, and splice sites, trained on distinct large-scale genomics datasets. These modules are combined to predict effects of variants on exon skipping, splice site choice, splicing efficiency, and pathogenicity, with matched or higher performance than state-of-the-art. Our models, available in the repository Kipoi, apply to variants including indels directly from VCF files.

Changes in the process of alternative RNA splicing results in soluble B and T lymphocyte attenuator with biological and clinical implications in critical illness.

BACKGROUND: Critically ill patients with sepsis and acute respiratory distress syndrome have severely altered physiology and immune system modifications. RNA splicing is a basic molecular mechanism influenced by physiologic alterations. Immune checkpoint inhibitors, such as B and T Lymphocyte Attenuator (BTLA) have previously been shown to influence outcomes in critical illness. We hypothesize altered physiology in critical illness results in alternative RNA splicing of the immune checkpoint protein, BTLA, resulting in a soluble form with biologic and clinical significance. METHODS: Samples were collected from critically ill humans and mice. Levels soluble BTLA (sBTLA) were measured. Ex vivo experiments assessing for cellular proliferation and cytokine production were done using splenocytes from critically ill mice cultured with sBTLA. Deep RNA sequencing was done to look for alternative splicing of BTLA. sBTLA levels were fitted to models to predict sepsis diagnosis. RESULTS: sBTLA is increased in the blood of critically ill humans and mice and can predict a sepsis diagnosis on hospital day 0 in humans. Alternative RNA splicing results in a premature stop codon that results in the soluble form. sBTLA has a clinically relevant impact as splenocytes from mice with critical illness cultured with soluble BTLA have increased cellular proliferation. CONCLUSION: sBTLA is produced as a result of alternative RNA splicing. This isoform of BTLA has biological significance through changes in cellular proliferation and can predict the diagnosis of sepsis.

Hereditary cancer genes are highly susceptible to splicing mutations.

Substitutions that disrupt pre-mRNA splicing are a common cause of genetic disease. On average, 13.4% of all hereditary disease alleles are classified as splicing mutations mapping to the canonical 5' and 3' splice sites. However, splicing mutations present in exons and deeper intronic positions are vastly underreported. A recent re-analysis of coding mutations in exon 10 of the Lynch Syndrome gene, MLH1, revealed an extremely high rate (77%) of mutations that lead to defective splicing. This finding is confirmed by extending the sampling to five other exons in the MLH1 gene. Further analysis suggests a more general phenomenon of defective splicing driving Lynch Syndrome. Of the 36 mutations tested, 11 disrupted splicing. Furthermore, analyzing past reports suggest that MLH1 mutations in canonical splice sites also occupy a much higher fraction (36%) of total mutations than expected. When performing a comprehensive analysis of splicing mutations in human disease genes, we found that three main causal genes of Lynch Syndrome, MLH1, MSH2, and PMS2, belonged to a class of 86 disease genes which are enriched for splicing mutations. Other cancer genes were also enriched in the 86 susceptible genes. The enrichment of splicing mutations in hereditary cancers strongly argues for additional priority in interpreting clinical sequencing data in relation to cancer and splicing.

Widespread intra-dependencies in the removal of introns from human transcripts.

Research into the problem of splice site selection has followed a reductionist approach focused on how individual splice sites are recognized. Early applications of information theory uncovered an inconsistency. Human splice signals do not contain enough information to explain the observed fidelity of splicing. Here, we conclude that introns do not necessarily contain 'missing' information but rather may require definition from neighboring processing events. For example, there are known cases where an intronic mutation disrupts the splicing of not only the local intron but also adjacent introns. We present a genome-wide measurement of the order of splicing within human transcripts. The observed order of splicing cannot be explained by a simple kinetic model. Simulations reveal a bias toward a particular, transcript-specific order of intron removal in human genes. We validate an extreme class of intron that can only splice in a multi-intron context. Special categories of splicing such as exon circularization, first and last intron processing, alternative 5 and 3'ss usage and exon skipping are marked by distinct patterns of ordered intron removal. Excessive intronic length and silencer density tend to delay splicing. Shorter introns that contain enhancers splice early.

Defective splicing of the RB1 transcript is the dominant cause of retinoblastomas.

Defective splicing is a common cause of genetic diseases. On average, 13.4% of all hereditary disease alleles are classified as splicing mutations with most mapping to the critical GT or AG nucleotides within the 5' and 3' splice sites. However, splicing mutations are underreported and the fraction of splicing mutations that compose all disease alleles varies greatly across disease gene. For example, there is a great excess (46%; ~threefold) of hereditary disease alleles that map to splice sites in RB1 that cause retinoblastoma. Furthermore, mutations in the exons and deeper intronic position may also affect splicing. We recently developed a high-throughput method that assays reported disease mutations for their ability to disrupt pre-mRNA splicing. Surprisingly, 27% of RB1-coding mutations tested also disrupt splicing. High-throughput in vitro spliceosomal assembly assay reveals heterogeneity in which stage of spliceosomal assembly is affected by splicing mutations. 58% of exonic splicing mutations were primarily blocked at the A complex in transition to the B complex and 33% were blocked at the B complex. Several mutants appear to reduce more than one step in the assembly. As RB1 splicing mutants are enriched in retinoblastoma disease alleles, additional priority should be allocated to this class of allele while interpreting clinical sequencing experiments. Analysis of the spectrum of RB1 variants observed in 60,706 exomes identifies 197 variants that have enough potential to disrupt splicing to warrant further consideration.

The effects of structure on pre-mRNA processing and stability.

Pre-mRNA molecules can form a variety of structures, and both secondary and tertiary structures have important effects on processing, function and stability of these molecules. The prediction of RNA secondary structure is a challenging problem and various algorithms that use minimum free energy, maximum expected accuracy and comparative evolutionary based methods have been developed to predict secondary structures. However, these tools are not perfect, and this remains an active area of research. The secondary structure of pre-mRNA molecules can have an enhancing or inhibitory effect on pre-mRNA splicing. An example of enhancing structure can be found in a novel class of introns in zebrafish. About 10% of zebrafish genes contain a structured intron that forms a bridging hairpin that enforces correct splice site pairing. Negative examples of splicing include local structures around splice sites that decrease splicing efficiency and potentially cause mis-splicing leading to disease. Splicing mutations are a frequent cause of hereditary disease. The transcripts of disease genes are significantly more structured around the splice sites, and point mutations that increase the local structure often cause splicing disruptions. Post-splicing, RNA secondary structure can also affect the stability of the spliced intron and regulatory RNA interference pathway intermediates, such as pre-microRNAs. Additionally, RNA secondary structure has important roles in the innate immune defense against viruses. Finally, tertiary structure can also play a large role in pre-mRNA splicing. One example is the G-quadruplex structure, which, similar to secondary structure, can either enhance or inhibit splicing through mechanisms such as creating or obscuring RNA binding protein sites.

Pathogenic variants that alter protein code often disrupt splicing.

The lack of tools to identify causative variants from sequencing data greatly limits the promise of precision medicine. Previous studies suggest that one-third of disease-associated alleles alter splicing. We discovered that the alleles causing splicing defects cluster in disease-associated genes (for example, haploinsufficient genes). We analyzed 4,964 published disease-causing exonic mutations using a massively parallel splicing assay (MaPSy), which showed an 81% concordance rate with splicing in patient tissue. Approximately 10% of exonic mutations altered splicing, mostly by disrupting multiple stages of spliceosome assembly. We present a large-scale characterization of exonic splicing mutations using a new technology that facilitates variant classification and keeps pace with variant discovery.

The importance of p53 pathway genetics in inherited and somatic cancer genomes.

Decades of research have shown that mutations in the p53 stress response pathway affect the incidence of diverse cancers more than mutations in other pathways. However, most evidence is limited to somatic mutations and rare inherited mutations. Using newly abundant genomic data, we demonstrate that commonly inherited genetic variants in the p53 pathway also affect the incidence of a broad range of cancers more than variants in other pathways. The cancer-associated single nucleotide polymorphisms (SNPs) of the p53 pathway have strikingly similar genetic characteristics to well-studied p53 pathway cancer-causing somatic mutations. Our results enable insights into p53-mediated tumour suppression in humans and into p53 pathway-based cancer surveillance and treatment strategies.

RNA structure replaces the need for U2AF2 in splicing.

RNA secondary structure plays an integral role in catalytic, ribosomal, small nuclear, micro, and transfer RNAs. Discovering a prevalent role for secondary structure in pre-mRNAs has proven more elusive. By utilizing a variety of computational and biochemical approaches, we present evidence for a class of nuclear introns that relies upon secondary structure for correct splicing. These introns are defined by simple repeat expansions of complementary AC and GT dimers that co-occur at opposite boundaries of an intron to form a bridging structure that enforces correct splice site pairing. Remarkably, this class of introns does not require U2AF2, a core component of the spliceosome, for its processing. Phylogenetic analysis suggests that this mechanism was present in the ancestral vertebrate lineage prior to the divergence of tetrapods from teleosts. While largely lost from land dwelling vertebrates, this class of introns is found in 10% of all zebrafish genes.

RNA-Binding Proteins: Splicing Factors and Disease.

Pre-mRNA splicing is mediated by interactions of the Core Spliceosome and an array of accessory RNA binding proteins with cis-sequence elements. Splicing is a major regulatory component in higher eukaryotes. Disruptions in splicing are a major contributor to human disease. One in three hereditary disease alleles are believed to cause aberrant splicing. Hereditary disease alleles can alter splicing by disrupting a splicing element, creating a toxic RNA, or affecting splicing factors. One of the challenges of medical genetics is identifying causal variants from the thousands of possibilities discovered in a clinical sequencing experiment. Here we review the basic biochemistry of splicing, the mechanisms of splicing mutations, the methods for identifying splicing mutants, and the potential of therapeutic interventions.