Biology subjects

David, J. K.

Publications and source records attributed to David, J. K..

5 recordsLinked to original sources

bioRxiv2025

Splicing neoepitope prediction is sensitive to methodological differences

MotivationCancer-specific neoepitopes may arise from abnormal splicing in the transcriptomic landscape (alternative splicing neoepitopes, ASNs), leading to divergent proteins with high potential immunogenicity. Predicting candidate ASNs requires a series of algorithmic and parameter choices, but no previous study has investigated the consistency and interpretability of these choices. ResultsWe apply two ASN prediction methods with 35 matched parameter sets to generate candidate ASNs for five breast and ovarian cancer samples from The Cancer Genome Atlas (TCGA). We find that: 1) junction 9-mer peptides generated by two similarly designed pipelines differed by, on average, 68.9% and 76.6% in the BRCA and OV cohorts, respectively, and putatively cancer-specific junction 9-mers from the two pipelines diverged further, by an average of 81.5 % in OV and 84.6 % in BRCA; 2) the most lenient filters in the BRCA cohort show the highest divergence, at 97 %; 3) the rate of mass spectrometry validation of ASNs protein presence in cells is dominated by the size of the input space; and 4) putatively cancer-specific ASNs found by the intersection of both pipelines can be validated when accounting for false discovery with an average of 1.74 and 284.4 candidates in the BRCA and OV cohorts, respectively. Taken together, these results highlight that ASN identification is fragile and difficult to reproduce across analysis platforms, with limited cross-pipeline overlap and strong dependence on parameter choices. Availability and ImplementationPython research code and scripts are available for download at https://github.com/ratschlab/projects2020_ohsu. Contactthompsre@ohsu.edu, raetsch@inf.ethz.ch

bioinformatics↗

bioRxiv2023

A pan-MHC reference graph with 246 fully contiguous phased sequences

The major histocompatibility complex (MHC) is a region of the human genome that is key to immune system function but sometimes refractory to genomic analyses due to extreme polymorphism and structural variation. We performed targeted long-read sequencing and de novo assembly of MHC to create 246 highly accurate, fully contiguous, and phased full-length sequences, mostly from data provided by the Human Pangenome Reference Consortium (HPRC). We identified alleles at high resolution across 39 loci including the class I and II HLA (human leukocyte antigen) genes, discovering 1,246 putative novel allele sequences. We identified copy number variation in the C4A and C4B genes and found significant linkage disequilibrium between C4A[~]C4B haplotypes and 14 MHC loci. We build our sequences into a novel "pan-MHC" reference graph, and we demonstrate that this improves the accuracy of short-read variant calling. Our haplotypes and graph contain significantly more population diversity than preexisting MHC sequences, thus improving the prospects for global health equity in this clinically important genomic region.

genomics↗

bioRxiv2022

Retained introns in long RNA-seq reads are not reliably detected in sample-matched short reads

There is growing interest in retained introns in a variety of disease contexts including cancer and aging. Many software tools have been developed to detect retained introns from short RNA-seq reads, but reliable detection is complicated by overlapping genes and transcripts as well as the presence of unprocessed or partially processed RNAs. We compared introns detected by 5 tools using short RNA-seq reads with introns observed in long RNA-seq reads from the same biological specimens and found: (1) significant disagreement among tools (Fleiss{kappa} = 0.231) such that 52.4% of all detected intron retentions were not called by more than one tool; (2) that no tool achieved greater than 20% precision or 35% recall under generous conditions; and (3) that retained intron detectability was adversely affected by greater intron length and overlap with annotated exons.

genomics↗

bioRxiv2019

Putatively cancer-specific alternative splicing is shared across patients and present in developmental and other non-cancer cells

We compared cancer and non-cancer RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) Project, and the Sequence Read Archive (SRA). We found that: 1) averaging across cancer types, 80.6% of exon-exon junctions thought to be cancer-specific based on comparison with tissue-matched samples are in fact present in other adult non-cancer tissues throughout the body; 2) 30.8% of junctions not present in any GTEx or TCGA normal tissues are shared by multiple samples within at least one cancer type cohort, and 87.4% of these distinguish between different cancer types; and 3) many of these junctions not found in GTEx or TCGA normal tissues (15.4% on average) are also found in embryological and other developmentally associated cells. This study probes the distribution of putatively cancer-specific junctions across a broad set of publicly available non-cancer human RNA-seq datasets. Overall, we identify a subset of shared cancer-specific junctions that could represent novel sources of cancer neoantigens. We further describe a framework for characterizing possible origins of these junctions, including potential developmental and embryological sources, as well as cell type-specific markers particularly related to cell types of cancer origin. These findings refine the meaning of RNA splicing event novelty, particularly with respect to the human neoepitope repertoire. Ultimately, cancer-specific exon-exon junctions may affect the anti-cancer immune response and may have a substantial causal relationship with the biology of disease.

cancer biology↗

bioRxiv2019

Burden of tumor mutations, neoepitopes, and other variants are cautionary predictors of cancer immunotherapy response and overall survival

BackgroundTumor mutational burden (TMB, the quantity of aberrant nucleotide sequences a given tumor may harbor) has been associated with response to immune checkpoint inhibitor therapy and is gaining broad acceptance as a result. However, TMB harbors intrinsic variability across cancer types, and its assessment and interpretation are poorly standardized. MethodsUsing a standardized approach, we quantify the robustness of TMB as a metric and its potential as a predictor of immunotherapy response and survival among a diverse cohort of cancer patients. We also explore the additive predictive potential of RNA-derived variants and neoepitope burden, incorporating several novel metrics of immunogenic potential. ResultsWe find that TMB is a partial predictor of immunotherapy response in melanoma and non-small cell lung cancer, but not renal cell carcinoma. We find that TMB is predictive of overall survival in melanoma patients receiving immunotherapy, but not in an immunotherapy-naive population. We also find that it is an unstable metric with potentially problematic repercussions for clinical cohort classification. We finally note minimal additional predictive benefit to assessing neoepitope burden or its bulk derivatives, including RNA-derived sources of neoepitopes. ConclusionsWe find sufficient cause to suggest that the predictive clinical value of TMB should not be overstated or oversimplified. While it is readily quantified, TMB is at best a limited surrogate biomarker of immunotherapy response. The data do not support isolated use of TMB in renal cell carcinoma.

cancer biology↗