Biology subjects

Fisk, N.

Publications and source records attributed to Fisk, N..

4 recordsLinked to original sources

bioRxiv2026

Stepwise Evolution and Epistatic Interaction of Driver Mutations from Endometrial Hyperplasia to Carcinoma

To characterize early oncogenesis, pathologically identified pre-cancerous tissue can be analyzed for the presence of cancer drivers. Here, we argue that in such studies, analyses of the driver status of variants, of the association between step-specific prevalence and progression through tumorigenesis, and of driver co-occurrence and mutual exclusivity should be accompanied by estimates of inherent mutation rate of variants and presented within an evolutionary framework of selective epistasis. To illustrate this point, we examine the transition of endometrial tissue from atypical hyperplasia to carcinoma. We apply a step-specific analysis, demonstrating that the strength of selection on somatic driver mutations promoting cell division and survival differs between hyperplasia to carcinoma. We demonstrate that mutations of PTEN, which are highly prevalent in carcinomas and have been argued to exert substantial driver effects, exhibit an even larger effect of increasing cellular division and survival within developing hyperplasias. A determination of cooccurrence or mutual exclusivity may be a product of genes sharing or differing in underlying sources of mutation, as opposed to a product of biological interaction and selection. By accounting for tumor-specific mutational processes that influence co-occurrence, we calculate epistatic selective intensities between pairs of drivers. Mutations of KRAS and FGFR2 are often mutually exclusive and were indeed found to exhibit significant antagonistic selective epistasis. However, mutations of PIK3CA and PIK3R1, which also have been identified as showing mutual exclusivity, do not demonstrate significant antagonistic selective epistasis. Thus, evidence of mutually exclusivity is insufficient to determine epistasis. Accordingly, the application of quantitative approaches that distinctly analyze mutation and selection on cancer variants has the potential to substantially illuminate the trajectory of tumorigenesis and cancer progression.

Cancer Biology↗

bioRxiv2026

Signal, noise, and bias in phylogenetic inference:potential and limits to the resolution of phylogenetic trees in the phylogenomic era

Phylogenomic datasets assembled to resolve the Tree of Life now routinely span thousands of loci comprising millions of characters. Yet the persistence of incongruent topologies across such datasets reveals a fundamental truth of phylogenetics: not all data are equally informative. Here we derive analytical approaches that predict the relative impacts of phylogenetic signal, stochastic noise, and systematic bias on phylogenetic inference. We show that these three components exhibit divergent scaling properties with character sampling: signal and bias accumulate linearly, while noise accumulates nonlinearly with a concave trajectory. For some phylogenetic problems, substantial amounts of phylogenetic noise may eventually be overwhelmed by signal. For other phylogenetic problems--especially those involving deep divergences, short internodes, or constrained character-state space--the slope of signal accumulation can be so shallow that even signal from genome-scale data may never practically exceed noise. Moreover, linear accumulation of phylogenetic bias can in principle continuously overwhelm accumulation of signal at a lower slope with additional characters, regardless of dataset size. Applying our theory to empirical datasets, we show that anchored hybrid enrichment and ultraconserved element loci, like any loci, can exhibit signal that is overwhelmed by noise, and that character acquisition biases in some loci can further confound inference. Given the pervasive nature of incongruence in the phylogenomic era, our work provides a theoretical foundation for understanding the limits of inference, improving experimental design, and guiding efficient and accurate resolution of the Tree of Life.

evolutionary biology↗

bioRxiv2025

TyCHE enables time-resolved lineage tracing of heterogeneously-evolving populations

Phylogenetic methods for cell lineage tracing have driven significant insights into organismal development, immune responses, and tumor evolution. While most methods estimate mutation trees, time-resolved lineage trees are more interpretable and could relate events like cellular migration and differentiation to perturbations like vaccines and drug treatments. However, somatic mutation rates vary dramatically by cell type, significantly biasing existing methods. We introduce TyCHE (Type-linked Clocks for Heterogeneous Evolution), a Bayesian phylogenetics package that infers time-resolved phylogenies of populations with distinct evolutionary rates. We demonstrate that TyCHE improves tree accuracy using a new simulation package SimBLE (Simulator of B cell Lineage Evolution). We use TyCHE to infer patterns of memory B cell differentiation during HIV infection, dynamics of recall germinal centers following influenza vaccination, evolution of a glioma tumor lineage, and progression of a bacterial lung infection. TyCHE and SimBLE are available as open-source software packages compatible with the BEAST2 and Immcantation ecosystems.

immunology↗

bioRxiv2025

Somatic evolution of prostate cancer: mutation, selection, and epistasis across disease stages

BackgroundSomatic mutations involved in prostate cancer tumorigenesis and disease progression have been identified, but their evolutionary dynamics--including differential selective pressures across oncogenesis and metastatic spread--remain poorly understood. No prior study has systematically quantified the adaptive landscape from prostate organogenesis through tumor initiation and progression to metastatic castrate-resistant prostate cancer (mCRPC), nor characterized the selective epistatic interactions that structure this evolutionary trajectory. Methods and FindingsTo address this gap, we analyzed 2,704 low- and high-risk primary tumors and metastatic castration-resistant prostate cancers to quantify the mutation rates, mutational processes, and scaled selection coefficients of somatic mutations across disease stages. Trinucleotide mutational patterns were stable, but both mutation load and mutation rates increased with progression. In parallel, selective pressures on specific somatic mutations changed substantially, revealing a dynamic adaptive landscape. Stage-specific selective effects were associated with significant synergistic and antagonistic selective epistasis among key driver genes. Early selection on SPOP mutations in the BRD3 binding domain were under strong positive selection, and they increased selection for subsequent RHOA mutations while decreasing selection for TP53 mutations. Antagonistic selective epistasis was evident between mutations of CUL3 and both SPOP and PIK3CA. Mutations in KMT2C increased the selection for mutations in TP53, consistent with their frequent co-occurrence. Synergistic epistatic interactions between mutations of PTEN and both PIK3CA and AR support a strong therapeutic rationale for combined inhibition of PI3K/AR pathway in PTEN-deficient prostate cancers. ConclusionsThese findings provide a comprehensive map of the evolving selective and epistatic forces that shape prostate cancer progression across clinical stages. By distinguishing shifts in selection from changes in mutation rate and revealing the extents of cooperative and conflicting relationships among driver mutations, our work identifies critical points of vulnerability and informs that design of therapeutic strategies that anticipate and intercept the somatic evolutionary trajectory of prostate cancer.

cancer biology↗