bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.02.17.706175

Genomic and Evolutionary Determinants of Two-hit Frequencies in Tumor Suppressor Genes

Abstract

While biallelic or "two-hit" inactivation is a central organizing principle for tumor suppressor genes (TSGs), large-scale cancer genomic data reveal substantial heterogeneity in the frequency of such events across genes. This variability reflects diverse selective constraints on allelic disruption, whose biological determinants remain incompletely characterized. Here, we present a comprehensive, allele-specific analysis of TSG two-hit alterations across [~]9,000 tumors from The Cancer Genome Atlas, focusing on loss of heterozygosity (LOH) arising from the co-occurrence of point mutation and deletion. We show that two-hit frequencies vary widely across TSGs and scale with the functional impact and selection strength of point mutations. Integrating mutation position with zygosity reveals distinct patterns consistent with dominant versus recessive modes of action, enabling a zygosity-informed framework for variant interpretation. We further demonstrate that chromosomal context strongly shapes two-hit frequencies, reflecting aneuploidy biases across chromosome arms and selective trade-offs imposed by neighboring loci, including the co-deletion of synergistic TSGs. Extending the LOH analysis beyond diploid tumors, we find that equivalent "all-hit" frequencies are largely preserved in polyploid cancers following whole-genome doubling, consistent with early acquisition of LOH during clonal evolution. Collectively, our results uncover multiple determinants of adherence to the two-hit model, providing new insight into long-standing heterogeneity in TSG behavior and its potential clinical relevance.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mukherjee, N., Sabarinathan, R.. 2026-02-18. Genomic and Evolutionary Determinants of Two-hit Frequencies in Tumor Suppressor Genes. https://doi.org/10.64898/2026.02.17.706175

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Structural variation in repeat elements is widespread in normal human tissues and in tumorigenesis

Somatic mosaicism contributes to genomic variation, yet postzygotic structural variants remain under-characterized. We performed long- and short-read WGS from multiple individuals (n=47 normal tissues; n=168 samples) and identified mosaic structural variants in all individuals and germ layers, impacting a median 285.2 kb/genome. Nearly half of breakpoints were independently validated, with tissue distributions reflecting both early and late developmental origins. Most mosaic variants were repeat-mediated and 8.3% overlapped functional elements, an enrichment compared to germline variants. To extend these analyses in samples where long-read sequencing is infeasible, we measured repeat alterations from short-read sequencing, recapitulating mosaic tissue-specific differences. We characterized tumor- and tissue- specific variation in repeats across 15 cancer types and found tumor-related repeat variation to be similar in scale to that of normal mosaic variation. Tracking repeat changes in cell-free DNA provided a noninvasive approach for tumor monitoring. Our analyses revealed widespread repeat-driven structural variation in health and disease.

genomics↗

RNA isoform-resolved multiplexed sequencing with bioorthogonal barcoding

RNA isoform dysregulation drives disease pathogenesis and is the target of FDA-approved splice-switching therapeutics. However, multiplexed sequencing methods discard splice junction information because only 3' termini are barcoded and counted. Here, we repurpose acylation and click chemistries to conjugate bioorthogonal barcodes (bobcodes) directly onto multiple internal positions along cellular RNAs. Bobcoded RNAs from multiple samples are pooled for multiplexed cDNA synthesis, during which reverse transcriptase switches from each RNA template onto its tethered bobcode with greater than 99% accuracy in species mixing experiments. Bobcode attachment intervals set cDNA insert sizes without a library fragmentation step, and priming with poly(dT) or random hexamers selects between 3'-end counting and full-length isoform capture. A bioorthogonal barcode-sequencing (BOB-seq v0.1) drug screen identifies transcriptome-wide on- and off-target RNA splicing effects and outperforms existing multiplexing RNA sequencing methods in workflow simplicity, sample-to-sample variability, and barcoding accuracy. Bobcodes add isoform resolution to scalable multiplexed RNA sequencing.

genomics↗

Structural polymorphism and population-variable coding capacity of HERV-K(HML-2) in human pangenomes

Approximately 8% of the human genome is derived from ancient retroviral infections. The most recently integrated of these endogenous retroviruses is the HERV-K(HML-2) clade, whose expression has been associated with cancer, amyotrophic lateral sclerosis, and embryogenesis. Studies of HERV expression, particularly HML-2, have relied predominantly on short-read sequencing. However, the high similarity among HML-2 proviruses prevents many short reads from being assigned uniquely to individual loci. We therefore compared haplotype-resolved long-read genome assemblies from 292 donors to resolve variation in proviral structure and coding capacity. Several loci previously thought to be fixed were structurally polymorphic. Tandem arrays occurred at 13 loci and contained up to six proviral copies in a single array. At 8q11.23, we identified a previously undescribed full-length provirus in one haplotype. All 583 other haplotypes carried a solo-LTR. We found that standard reference genomes failed to represent the coding capacity retained in many individuals, whose proviruses contained intact open reading frames despite disruptive mutations in the reference sequences. Short-read genotypes left 32.5% of the tested donor-variant pairs unresolved at sites associated with viral reading frames. These findings show why HML-2 expression must be interpreted in the context of the structural and coding alleles each individual carries.

genomics↗