Biology subjects

Cannataro, V. L.

Publications and source records attributed to Cannataro, V. L..

9 recordsLinked to original sources

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↗

bioRxiv2023

Mutation of NOTCH1 is selected within normal esophageal tissues, yet leads to selective epistasis suppressive of further evolution into cancer

BackgroundSomatic mutations commonly accumulate in histologically normal tissues and contribute to cancer development. However, many mutations that are common in normal tissue are also found in cancers from the same organ, making their role in malignant progression unclear. To address this, we asked whether such mutations increase cell proliferation and survival to different degrees at different steps of esophageal tumor development, and whether they alter selection for other driver mutations. MethodsWe used a quantitative evolutionary framework to distinguish underlying mutation rate from selection across two steps of esophageal development: from organogenesis to clonal histologically normal esophageal epithelium, and from that tissue to esophageal squamous-cell carcinoma. Analyzing sequence data from 2171 samples, we estimated step-specific selection on recurrent somatic mutations, corresponding to increased cellular division and survival, and tested whether mutations in one gene earlier in the trajectory changed selection for mutations on another. We additionally examined somatic copy-number alterations and single-cell transcriptomic profiles to contextualize these evolutionary patterns within broader genomic and cellular changes during progression. ResultsNOTCH1 mutations were strongly selected during the clonal expansion of histologically normal esophageal epithelium, explaining their high prevalence in that tissue. However, for the first time, we show that there is little to no positive selection for NOTCH1, NOTCH2, and FAT1 mutations during progression from clonal histologically normal esophageal tissue to esophageal squamous-cell carcinoma in humans, leading to a conclusion that these alterations promote clonal expansion in normal tissue, but do not drive malignant progression from established normal clones. Moreover, we provide a somatic genetic basis for this step-specific effect: we demonstrate for the first time that mutations in NOTCH1 exhibit antagonistic epistasis with mutations of TP53 and RB1, reducing selection for these key tumor suppressor alterations during tumor development. Consistent with this model, copy-number alterations associated with later ESCC progression were more strongly selected in TP53-mutant samples, supporting the idea that TP53 disruption promotes a genomic context more permissive for malignant evolution. ConclusionsEarly somatic mutations can promote clonal expansion in normal tissue without promoting cancer, and in some cases may limit progression by reducing selection for later driver events. NOTCH1 and other genes can shape evolutionary trajectories in ways that ultimately constrain malignant progression. By separating mutation rate from selection, quantifying step-specific genetic interactions, and considering broader changes in genomic and cellular context, our study shows that the effects of recurrent mutations depend strongly on disease stage and mutational context--what promotes clonal expansion in normal tissue may later impede growth or survival in tumors. These insights underscore the need for precision strategies that account for the shifting fitness landscape across premalignant and malignant stages, informing early detection, prevention, and therapeutic prioritization.

cancer biology↗

bioRxiv2021

Cancer relevance of human genes

BackgroundIt is unclear how many of genes contribute to the biology of cancer. We hypothesize that genes that interact with core cancer gene (CCG) in a protein-protein interaction network (PPI) may have functional importance. MethodsWe categorized genes into 1- (n=6791), 2- (n=7724), 3- (n=1587), and >3-steps (n=362) removed from the nearest CCG in the STRING PPI and demonstrate that the cancer-biology related functional contribution of the genes in these different neighborhood categories decreases as their distance from the CCGs increases. ResultsGenes closer to cancer genes manifest greater connectedness in the network, show greater importance in maintaining cell viability in a broad range of cancer cells in vitro, are also under greater negative germline selection pressure in the healthy populations, and have higher somatic mutation frequency and cancer effect. ConclusionsApproximately 70% of human genes are 1 or 2 steps removed from cancer genes in protein network and show functional importance in cancer-biology. These results suggest that the universe of cancer-relevant genes extends to thousands of genes that can contribute functional effects when dysregulated.

genomics↗

bioRxiv2020

Attribution of Cancer Origins to Endogenous, Exogenous, and Actionable Mutational Processes

Mutational processes in tumors leave tell-tale genomic signatures composed of "passenger" mutations and mutations that have quantifiable effects on the proliferation and survival of cancer cell lineages. We identify the contributions of mutational processes to each oncogenic variant, quantifying responsibility for origination of changes at oncogenic variant sites contributing to tumorigenesis in 23 cancer types. We demonstrate that the variants driving melanomas and lung cancers are predominantly attributable to the actionable, preventable, exogenous mutational processes of ultraviolet light and tobacco exposure, whereas gliomas and prostate adenocarcinomas are largely attributable to endogenous processes associated with aging. Preventable mutations associated with pathogen exposure and APOBEC activity account for a large proportion of the cancer effect within head and neck, bladder, cervical, and breast cancers. These attributions complement epidemiological approaches--revealing the burden of cancer driven by single-nucleotide variants caused by either endogenous or exogenous, non-actionable or actionable processes, and crucially inform cancer prevention.

cancer biology↗

bioRxiv2020

Identifying Modules of Cooperating Cancer Drivers

AbstractIdentifying cooperating modules of driver alterations can provide biological insights to cancer causation and would advance the development of effective personalized treatments. We present Cancer Rule-Set Optimization (CRSO) for inferring the combinations of alterations that cooperate to drive tumor formation in individual patients. Application to 19 TCGA cancer types found a mean of 11 core driver combinations per cancer, comprising 2-6 alterations per combination, and accounting for a mean of 70% of samples per cancer. CRSO departs from methods based on statistical cooccurrence, which we demonstrate is a suboptimal criterion for investigating driver cooperation. CRSO identified well-studied driver combinations that were not detected by other approaches and nominated novel combinations that correlate with clinical outcomes in multiple cancer types. Novel synergies were identified in NRAS-mutant melanomas that may be therapeutically relevant. Core driver combinations involving NFE2L2 mutations were identified in four cancer types, supporting the therapeutic potential of NRF2 pathway inhibition. CRSO is available at https://github.com/mikekleinsgit/CRSO/.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cancer biology↗

bioRxiv2019

Identifying Combinations of Cancer Drivers in Individual Patients.

Identifying the subset of genetic alterations present in individual tumors that are essential and collectively sufficient for cancer initiation and progression would advance the development of effective personalized treatments. We present CRSO for inferring the combinations of alterations, i.e., rules, that cooperate to drive tumor formation in individual patients. CRSO prioritizes rules by integrating patient-specific passenger probabilities for individual alterations along with information about the recurrence of particular combinations throughout the population. We present examples in glioma, liver cancer and melanoma of significant differences in patient outcomes based on rule assignments that are not identifiable by consideration of individual alterations.

bioinformatics↗

bioRxiv2017

Effect sizes of somatic mutations in cancer

A major goal of cancer biology is determination of the relative importance of the genomic alterations that confer selective advantage to cancer cells. Tumor sequence surveys have frequently ranked the importance of substitutions to cancer growth by P value or a false-discovery conversion thereof. However, P values are thresholds for belief, not metrics of effect. Their frequent misuse as metrics of effect has often been vociferously decried. Here, we estimate the effect sizes of all recurrent single nucleotide variants in 23 cancer types, quantifying relative importance within and between driver genes. Some of the variants with the highest effect size, such as EGFR L858R in lung adenocarcinoma and BRAF V600E in primary skin cutaneous melanoma, have yielded remarkable therapeutic responses. Quantification of cancer effect sizes has immediate importance to the prioritization of clinical decision-making by tumor boards, selection and design of clinical trials, pharmacological targeting, and basic research prioritization.

cancer biology↗

bioRxiv2017

Dark selection for JAK/STAT-inhibitor resistance in chronic myelomonocytic leukemia

Acquired therapy resistance to cancer treatment is a common and serious clinical problem. The classic U-shape model for the emergence of resistance supposes that: (1) treatment changes the selective pressure on the treatment-naive tumour; (2) this shifting pressure creates a proliferative or survival difference between sensitive cancer cells and either an existing or de novo mutant; (3) the resistant cells then out-compete the sensitive cells and - if further interventions (like drug holidays or new drugs or dosage changes) are not pursued - take over the tumour: returning it to a state dangerous to the patient. The emergence of ruxolitinib resistance in chronic myelomonocytic leukemia (CMML) seems to challenge the classic model: we see the global properties of resistance, but not the drastic change in clonal architecture expected with the selection bottleneck. To study this, we explore three population-level models as alternatives to the classic model of resistance. These three effective models are designed in such a way that they are distinguishable based on limited experimental data on the time-progression of resistance in CMML. We also propose a candidate reductive implementation of the proximal cause of resistance to ground these effective theories. With these reductive implementations in mind, we also explore the impact of oxygen diffusion and spatial structure more generally on the dynamics of CMML in the bone marrow concluding that, even small fluctuations in oxygen availability can seriously impact the efficacy of ruxolitinib. Finally, we look at the ability of spatially distributed cytokine signaling feedback loops to produce a relapse in symptoms similar to what we observe in the clinic.

cancer biology↗

bioRxiv2017

The likelihood of heterogeneity or additional mutation in KRAS or associated oncogenes to compromise targeting of oncogenic KRAS G12C

Activating mutations in RAS genes are associated with approximately 20% of all human cancers. New targeted therapies show preclinical promise in inhibiting the KRAS G12C variant, however, concerns exist regarding the effectiveness of such therapies in vivo given the possibilities of existing intratumor heterogeneity or de novo mutation leading to treatment resistance. We performed deep sequencing of 27 KRAS G12 positive lung tumors and found no evidence of other oncogenic mutations within KRAS or within commonly mutated downstream genes that could confer resistance at the time of treatment. Furthermore, we estimate the de novo mutation rate in KRAS position 12 and in genes downstream of KRAS. We find that mutations that confer resistance are about as likely to occur downstream of KRAS as within KRAS. Moreover, we present an approach for estimation of the selection intensity for these point mutations that explains their high prevalence in tumors. Our approach predicts that BRAF V600E would provide the highest fitness advantage for de novo resistant subclones. Overall, our findings suggest that resistance to targeted therapy of KRAS G12C positive tumors is unlikely to be present at the time of treatment and, among the de novo mutations likely to confer resistance, mutations in BRAF, a gene with targeted inhibitors presently available, result in subclones with the highest fitness advantage.\n\nOne Sentence SummaryMutations conferring resistance to KRAS G12C targeted therapy are unlikely to be present at the time of resection, and the likely mechanisms of evolved resistance are predicted be ones that are responsive to therapies that are in development or that are already available.

cancer biology↗