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Results for “driver mutations”

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At least 19 recordsLinked to original sources

PubMed2025

ProgModule: A novel computational framework to identify mutation driver modules for predicting cancer prognosis and immunotherapy response.

BACKGROUND: Cancer originates from dysregulated cell proliferation driven by driver gene mutations. Despite numerous algorithms developed to identify genomic mutational signatures, they often suffer from high computational complexity and limited clinical applicability. METHODS: Here, we presented ProgModule, an advanced computational framework designed to identify mutation driver modules for cancer prognosis and immunotherapy response prediction. In ProgModule, we introduced the Prognosis-Related Mutually Exclusive Mutation (PRMEM) score, which optimizes the balance between exclusive mutation coverage and the incorporation of mutation combination mechanisms critical for cancer prognosis. RESULTS: Applying to BLCA and HNSC cohorts, ProgModule successfully identified driver modules that stratify patients into distinct prognostic subgroups, and the combination of these modules could serve as an effective prognostic biomarker. Extending our method to diverse cancers, ProgModule presented robust prognostic performance and stability across model parameters, including stopping criteria and network topology. Moreover, our analysis suggested that driver modules can predict immunotherapeutic benefit more effectively than existing signatures. Further analyses based on published CRISPR data indicated that genes within these modules may serve as potential therapeutic targets. CONCLUSIONS: Altogether, ProgModule emerges as a powerful tool for identifying mutation driver modules as prognostic and immunotherapy response biomarkers, and genes within these modules may be used as potential therapeutic targets for cancer, offering new insights into precision oncology.

Humans↗

PubMed2025

Nonhypermutator Cancers Access Driver Mutations Through Reversals in Germline Mutational Bias.

Cancer is an evolutionary disease driven by mutations in asexually reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Nonhypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and nonhypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and nonhypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

Neoplasms↗

PubMed2024

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias.

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Non-hypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and non-hypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and non-hypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

Journal Article↗

PubMed2026

YAP1 induces hepatocellular carcinoma via DNA demethylation rather than by canonical driver gene mutations.

Large-scale genome sequencing analyses have identified driver gene mutations (DGMs) in most cancers as well as their associated tumorigenic mechanisms. However, a small fraction of cancers are not positive for these canonical DGMs, leaving the mechanisms underpinning their formation a mystery. We hypothesized that canonical DGM-negative cancers might be driven by activation of the transcriptional coactivator YAP1 that led to the induction of epigenetic changes. To test this theory, we established a mouse mosaic model of hepatocellular carcinoma (HCC) in which we induced YAP1-TEAD activation in a few hepatocytes. Whole-exome sequencing did not identify canonical DGMs in HCCs, but bisulfite sequencing revealed widespread DNA demethylation leading to the transcriptional activation of multiple oncogenes. Knockdown of the DNA demethylation-promoting gene, Tet1, attenuated HCC formation in these mice. Single-cell spatial transcriptomics identified a Tet1-high subpopulation of HCC cells that interacted with other hepatic cell types. Our mechanistic mouse data align with the observation that YAP1-TEAD-TET1-associated signatures were also elevated in hepatocytes from patients with Fontan-associated liver disease (FALD), a condition associated with the development of HCCs with lower frequencies of canonical DGMs. Our study suggests that the YAP1-TEAD-TET1 axis promotes canonical DGM-negative HCC development, and provides new insights into the molecular processes involved.

Animals↗

PubMed2026

DBP-CanPred: a machine learning model for predicting cancer-causing mutations in DNA-binding proteins.

INTRODUCTION: The fundamental cellular processes, including transcriptional regulation, chromatin organization, and genome maintenance, are regulated by DNA-binding proteins (DBPs). Mutations in DBPs can alter protein-DNA interactions, leading to tumor development. However, identifying such driver mutations remains a major challenge due to limitations of experimental approaches. METHODS: We have trained a machine learning model, DBP-CanPred, to identify driver mutations in DBPs. We used the sequence-derived evolutionary features, as well as structure-based features such as mutation-perturbed structural descriptors. RESULTS: We evaluated DBP-CanPred using a curated test set, achieving an AU-ROC of 0.86 and a balanced accuracy of 0.79. Further analysis based on substitution-type showed consistent performance across different categories, especially higher performance on charged residues. In addition, we applied the model on an independent dataset and identified potential driver mutations with high confidence scores. DISCUSSION: The study contributes to understanding mutation patterns in DNA-binding proteins and supports variant interpretation in cancer research.

DNA-binding proteins↗

PubMed2026

Origin and evolution of colorectal mixed neuroendocrine-non-neuroendocrine neoplasms (MiNEN).

Colorectal neuroendocrine carcinoma (NEC) is a rare and aggressive cancer and in a subset of patients associated with an adenocarcinoma (AC) component. When both components exceed 30% of the tumour, it is classified as mixed neuroendocrine-non-neuroendocrine neoplasm (MiNEN), although there is an ongoing debate about whether any presence of two distinct components should be sufficient for a MiNEN diagnosis. This study aimed to investigate the origin and subsequent genetic changes of these two components. Ten colorectal cases suitable for sampling of an AC and a poorly differentiated NEC component were identified from the NORDIC NEC 2 study and sequenced across a 360-cancer gene panel. Mock phylogenetic trees were constructed from the molecular profiles of each sample within a patient. All ten cases revealed a common trunk of shared somatic mutations, including well-known colorectal cancer driver mutations such as BRAF, KRAS, APC, and TP53. In all cases, a single branching point separated the AC and NEC components. Private AC and NEC mutations generally had low variant allele frequencies, indicating that most AC and NEC cells were genetically similar. NEC, when compared with AC samples, demonstrated a higher frequency of private mutations (P = 0.009), indicating a higher mutation rate and greater ploidy (P = 0.012), suggesting an association between genomic duplication and AC-to-NEC transition. Shared mutations indicate a common clonal origin, underscoring the role of established colorectal driver mutations in the early development of these tumours, while the mechanisms underlying NEC differentiation remain poorly understood and may involve non-genetic factors.

Humans↗

PubMed2018

Signaling Pathways Regulating Redox Balance in Cancer Metabolism.

The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells' demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions.

OXPHOS↗

PubMed2025

Genomic profiling of aggressive pathologic features in lung adenocarcinoma.

INTRODUCTION: Pathologic features involving LVI (lympho-vascular invasion), PNI (perineural invasion), STAS (spread through air spaces), and Grade 3 pattern (from the International Association for the Study of Lung Cancer grading system) are related to having an aggressive phenotype and linked to poor prognosis. However, few studies have conducted in-depth analyses of these features simultaneously with genomic profiling. METHODS: A total of 1559 sequencing of adenocarcinoma samples were included in the common driver mutations analysis, 1306 samples were brought into genomic mapping analysis. OncoSG's East Asian ancestry dataset was implemented for Tumor-Node-Metastasis-Biomarker (TNMB) classification and prognostic assessment. RESULTS: EGFR was more significantly prevalent in LVI negativity (P = 0.021), STAS negativity (P = 0.002), and moderate grade (P < 0.001). ALK was significantly interrelated with LVI (P = 0.028), STAS (P < 0.001), and poor grade (P < 0.001); ROS1 and STAS positivity (P = 0.031), poor grade (P = 0.016) were significantly related. KRAS (P = 0.003) and BRAF-V600E (P = 0.002) were only significantly intertwined with poor grade. Apart from common driver mutations, TP53, CHEK2, KEAP1, PTEN, RB1, NF1 were significantly enriched in LVI samples (P < 0.05). TP53, PTEN, CTNNB1, HGF, NF1 were more prominent in STAS (P < 0.01). TP53, LRP1B, NF1 were significantly more prevalent in Grade 3 pattern (P < 0.001). The mixture of STK11, PTEN, and TOP2A generated by exclusive mutations may be a potential predictor of TNMB categorization towards survival. The HR of stage II compared I of TNMB was 2.28 (95 % CI 1.36-3.86, P < 0.001), while stage III compared II was 1.95 (95 % CI 1.04-3.21, P = 0.031). CONCLUSIONS: This analysis demonstrated the correlation of pathologic features with common driver mutations, key mutations and canonical oncogenic signaling pathways. The data highlighted the similarities and differences among these features horizontally, and provide new insights in TNMB classification and prognostic assessment.

Humans↗

PubMed2025

Recurrent FGFR2 and PIK3CA Mutations in Sialoblastoma.

PURPOSE: Sialoblastoma is an extremely rare low-grade malignant salivary gland neoplasm that presents at birth or early infancy and has heterogeneous clinical behavior. Due to its rarity, the molecular landscape remains incompletely characterized. We aimed to expand the current understanding of the genetic alterations in sialoblastoma through comprehensive molecular analysis. METHODS: Five sialoblastoma cases were retrieved from four institutional archives. Clinical and pathologic review was performed, and targeted next-generation sequencing was conducted using clinically validated panels. Copy number analysis was performed on four cases. RESULTS: The cohort included five patients with tumors located in parotid gland (n = 2), minor salivary glands (n = 2), and submandibular gland (n = 1). Four patients were diagnosed before 6 months of age. Histologically, all tumors showed solid organoid nests with primitive basaloid cells, dense fibrous stroma, and mitotic activity ranging from 8 to 25 per 10 high-power fields. Recurrent FGFR2 p.C382R variants were identified in 80% (4/5) of cases. Additional alterations were seen in FGFR2 p.C382R mutated tumors, including PIK3CA hotspot mutations in two cases (p.R88Q, p.R38H) and a truncating FGFR2 variant (p.L776Rfs) in one. The single tumor that lacked FGFR2 mutations harbored a CTNNB1 p.I35T variant and showed more favorable histologic features. Copy number analysis revealed recurrent whole-chromosome gains of chromosomes 8, 10, and 11. CONCLUSION: A distinct subset of sialoblastoma has FGFR2 p.C382R hotspot mutation as the predominant driver mutation. Tumors with this mutation tend to have solid growth pattern, aggressive histologic features, and clinical behavior. The identification of concurrent genomic alterations expands the molecular landscape of this rare tumor. The detection of alternative drivers, such as CTNNB1 hotspot mutations typical of basal cell adenoma, also suggests that a subset of sialoblastoma may represent other salivary gland tumors presenting in infancy.

Humans↗

PubMed2026

The Landscape of Genomic and Socioeconomic Variables in Patients with Colorectal Cancer Based on Genetic Ancestry.

BACKGROUND: Despite differences in tumor alterations across genetic ancestries, investigations of the colorectal cancer molecular landscape have used self-reported ethnicity instead of genetic ancestry. METHODS: We used tumor and matched normal whole-exome sequencing data from 16,388 patients with stage I to IV colorectal cancer to investigate colorectal cancer's germline and somatic molecular landscape and the potential influence of socioeconomic factors (Distressed Communities Index, DCI) across diverse genetic ancestries. Genetic ancestry determined via supervised local ancestry inference included African (AFR, N = 1,697), Native American (AMR, N = 1,291), East Asian (EAS, N = 2,247), European (EUR, N = 9,726), Levantine Middle Eastern (LME, N = 1,192), and South Asian (SAS, N = 184). RESULTS: Microsatellite instability (MSI) was the most common form of hypermutation (80.8%), higher in the EUR genetic ancestry than in the AFR, AMR, and EAS genetic ancestry. Among germline findings, positive results were most common in high-penetrance genes associated with Lynch syndrome. Enrichment patterns included MLH1 (SAS) and PMS2 (AFR). There were significant differences in the frequency of driver mutations in APC, BRAF, KRAS, TP53, and PIK3CA between the EUR and other ancestry groups in both MSI and microsatellite stable tumors. Mutational signatures suggested enrichment of reactive oxygen species and POLE in AFR, colibactin in EAS, and aflatoxin and NTHL1 in SAS. DCI scores differed by ancestry (higher distress in AFR/AMR than in EUR), but driver mutation frequencies did not vary across DCI quintiles. CONCLUSIONS: Genetic ancestry shapes hereditary risk, tumor biology, and environmental exposures. IMPACT: These findings suggest that incorporating ancestry into screening, trials, and precision oncology may improve equity, though outcome-linked prospective studies and implementation research are warranted.

Aged↗

PubMed2025

Unusual relapse dynamics in EGFR-mutated lung adenocarcinoma uncovered by genomic profiling: Insights from a case report.

Synchronous or metachronous multiple NSCLCs challenge clinical practice, particularly in distinguishing multiple separate primary lung cancers (SPLC) from intrapulmonary metastasis (IPM) for accurate staging and management. Here, we present a unique case of three resected lung adenocarcinomas (LUAD) from a single patient collected at different time points, all harboring the same EGFR p.L858R somatic driver mutation but exhibiting distinct clonal trajectories. Whole exome sequencing (WES) analysis revealed that the first tumor was an independent primary tumor, while the latter two tumors were clonally related. Our findings highlight the complexity of tumor progression and provide insights into clonal heterogeneity. This report underscores the importance of genomic profiling for discriminating SPLC from IPM and emphasizes that the detection of a single shared driver mutation is not sufficient to prove metastasis.

Humans↗

PubMed2024

Molecular Analysis of Persistent and Recurrent Barrett's Esophagus in the Setting of Endoscopic Therapy.

INTRODUCTION: Early neoplastic progression of Barrett's esophagus (BE) is often treated with endoscopic therapy. Although effective, some patients are refractory to therapy or recur after apparent eradication of the BE. The goal of this study was to determine whether genomic alterations within the treated BE may be associated with persistent or recurrent disease. METHODS: We performed DNA sequencing on pre-treatment esophageal samples from 45 patients who were successfully treated by endoscopic therapy and did not recur as well as pre-treatment and post-treatment samples from 40 patients who had persistent neoplasia and 21 patients who had recurrent neoplasia. The genomic alterations were compared between groups. RESULTS: The genomic landscape was similar between all groups. Patients with persistent disease were more likely to have pre-treatment alterations involving the receptor tyrosine kinase pathway ( P = 0.01), amplifications of oncogenes ( P = 0.01), and deletions of tumor suppressor genes ( P = 0.02). These associations were no longer significant after adjusting for patient age and BE length. More than half of patients with persistent (52.5%) or recurrent (57.2%) disease showed pre-treatment and post-treatment samples that shared at least 50% of their driver mutations. DISCUSSION: Pre-treatment samples were genomically similar between those who responded to endoscopic therapy and those who had persistent or recurrent disease, suggesting there is not a strong genomic component to treatment response. Although it was expected to find shared driver mutations in pre-treatment and post-treatment samples in patients with persistent disease, the finding that an equal number of patients with recurrent disease also showed this relation suggests that many recurrences represent undetected minimal residual disease.

Humans↗

PubMed2026

Intramuscular patient-derived xenografts achieve high engraftment rates in gastric cancer: implications for pharmacodynamic testing and genomic biomarker discovery.

BACKGROUND: Gastric cancer (GC) exhibits marked inter-patient heterogeneity, limiting empirical chemotherapy efficacy. Patient-derived xenograft (PDX) models preserve the molecular features of parental tumors and can serve as pharmacodynamic surrogates, but conventional subcutaneous PDX suffers from low engraftment rates. This study evaluated an optimized intramuscular PDX platform for individualized drug testing in GC and applied whole exome sequencing (WES) for biomarker identification (Clinical trial registry: ChiCTR-OOC-17012731). MATERIALS AND METHODS: Ninety-eight treatment-naive GC patients were enrolled between April 2018 and December 2020. Fresh tumor tissues were engrafted into NCG mice by intramuscular transplantation. Drug efficacy was evaluated using tumor cell necrosis rate and Ki-67 expression. WES was performed on 32 engrafted tumorgrafts to characterize driver mutations in fast- and slow-growing subgroups. RESULTS: An engraftment rate of 71.7% (43/60) was achieved, substantially exceeding rates reported in prior studies. Clinical characteristics were independent of engraftment success and outgrowth time (all p > 0.05). Fast- and slow-growing tumorgrafts diverged in frequently altered genes: KMT2C, APOB, CDK12 and MSH2 predominated in fast-growing grafts, whereas TP53, CHD3 and TET2 were enriched in slow-growing grafts. Slow-growing tumorgrafts correlated with longer progression-free survival (p = 0.02). PDX-guided treatment was associated with improved prognosis. CONCLUSIONS: Intramuscular transplantation into NCG mice yields high engraftment rates for GC PDX. PDX-guided chemotherapy selection is associated with favorable outcomes. Driver mutation divergence between fast- and slow-growing tumorgrafts provides candidate prognostic biomarkers.

Animals↗

PubMed2026

Genome-Wide Single-Nucleotide Polymorphism (SNP)-based Profiling of Loss of Heterozygosity Reveals Distinct Molecular Subgroup-Specific Patterns in Gastrointestinal Stromal Tumors (GIST).

PURPOSE: Gastrointestinal stromal tumors (GIST) are molecularly heterogeneous neoplasms defined by mutually exclusive driver alterations (KIT, PDGFRA, SDH, BRAF, RAS, and NF1). However, driver mutations alone do not fully explain their biological and clinical variability. Chromosomal imbalances and loss of heterozygosity (LOH) may represent an additional layer of tumor characterization. We developed a single-nucleotide polymorphism (SNP)-based next-generation sequencing panel enabling genome-wide LOH assessment from formalin-fixed paraffin-embedded tissue. MATERIALS AND METHODS: Forty-nine GIST cases molecularly classified using targeted next-generation sequencing (KIT n = 19, PDGFRA n = 9, SDH-deficient n = 8, NF1 n = 7, quadruple wild-type n = 6) were analyzed. LOH was inferred from variant allele frequency patterns across 1826 genome-wide SNPs. RESULTS: Chromosome 14 was the most commonly affected (63%), followed by chromosomes 22 (45%), 15 (41%), 21 (27%), and 13 (20%). Loss of chromosome arm 1p occurred in 43% of tumors. Distinct subgroup-specific patterns emerged: KIT-mutant GIST exhibited the highest degree of genomic instability, whereas both SDH-deficient tumors and PDGFRA-mutant GIST displayed minimal chromosomal instability. NF1-mutant tumors showed recurrent single-arm chromosome 17 LOH. Quadruple wild-type GISTs were heterogeneous, including 1 case with extensive chromosomal instability. CONCLUSIONS: Genome-wide SNP-based LOH profiling reveals distinct, subgroup-specific patterns of chromosomal imbalance in GIST and may serve as a feasible complementary approach to driver mutation analysis for refined molecular characterization and potential future clinical utility.

Humans↗

PubMed2025

Colchicine and Longitudinal Dynamics of Clonal Hematopoiesis: An Exploratory Substudy of the LoDoCo2 Trial.

BACKGROUND: Clonal hematopoiesis (CH) is an aging-related hematologic condition associated with increased risk for cardiovascular events. Larger CH clones associate more strongly with cardiovascular risk. Preclinical data indicate that inflammatory signaling drives expansion of CH clones and CH-associated cardiovascular disease. However, the effect of anti-inflammatory therapies on CH clonal dynamics in humans is unclear. OBJECTIVES: The goal of this study was to test the association of randomization to colchicine vs placebo with CH growth in participants with chronic coronary artery disease. It also assessed the association of colchicine use with change in inflammatory biomarkers over time according to CH status. METHODS: In this exploratory substudy of the LoDoCo2 (Low-Dose Colchicine 2) trial, high-coverage targeted sequencing was used to detect CH driver mutations and to quantify variant allele frequency at 4 timepoints: baseline, after a 30-day open-label colchicine run-in phase (0.5 mg daily), 1 year postrandomization to colchicine or placebo, and at end of study (median follow-up of 25.0 months). Clonal dynamics were assessed by using a generalized linear mixed model. High-sensitivity C-reactive protein and interleukin-6 were additionally measured at baseline, randomization, and 1 year postrandomization. RESULTS: In total, 854 participants contributed 2,047 observations across 4 timepoints, including before and after the prerandomization colchicine run-in period. Randomization to placebo was associated with a 14.9% annual increase in CH clone size (βtime = 0.14; 95% CI: 0.08 to 0.21) vs a nonsignificant 6.3% increase with colchicine (βtime on colchicine: 0.06; 95% CI: -0.01 to 0.14), although this difference between treatment arms was not statistically significant (Pinteraction = 0.13). Compared with placebo, colchicine was associated with attenuated clonal growth in TET2 CH (βtime on colchicine: 0.09 [95% CI: -0.04 to 0.22]; βtime placebo: 0.27 [95% CI: 0.16 to 0.37]; Pinteraction= 0.04). Among individuals with non-DNMT3A CH, interleukin-6 levels increased to a lesser extent in those receiving colchicine vs placebo over 1 year (30.0% vs 98.1% increase, respectively; Pinteraction = 0.01). CONCLUSIONS: In this exploratory analysis, treatment with low-dose colchicine was associated with attenuated clonal expansion in TET2 CH. These findings suggest the potential for colchicine to curb the proliferative advantage of key CH driver mutations and to mitigate their associated risk of cardiovascular disease. Further validation in prospective studies is warranted.

Humans↗

PubMed2026

Mechanism of age-related accumulation of mtDNA mutations in human blood.

Accumulation of mutant mitochondrial DNA (mtDNA) heteroplasmy is among the strongest signatures of ageing1. Here we investigated the underlying mechanism by calling mtDNA sequence, mtDNA abundance and mtDNA heteroplasmic variants in human blood using whole-genome sequences from approximately 750,000 individuals. We observed that mtDNA single-nucleotide variants (mtSNVs) accumulate sharply at age 60 years, occur at low levels of heteroplasmy, exhibit little evidence of positive selection and are likely to be predominantly neutral. The mutational spectrum of mtSNVs does not reflect oxidative lesions, as is commonly invoked, but is more consistent with mtDNA replication errors. To understand why mtSNVs become detectable with age, we performed a genome-wide association study for heteroplasmic mtSNV burden, identifying germline variants near TERT, TCL1A and SMC4, all of which have been linked to clonal haematopoiesis (CH)2. Rare-variant analysis also showed that high mtSNV burden is associated with mutations in numerous CH driver genes. These genetic associations persisted even after exclusion of individuals with known CH driver mutations. Our results support a model in which 'cryptic' mtDNA mutations initially arise randomly as replication errors but are undetectable in bulk. They then become apparent only through age-related expansion of cellular clones in blood. We propose that the high copy number and mutation rate of mtDNA make it a sensitive blood-based marker of somatic mosaicism due to CH. Our work mechanistically unifies three prominent signatures of ageing: common germline variants in TERT, CH and observed accrual of mtDNA mutations.

Humans↗

PubMed2026

Competing subclones and fitness diversity shape tumor evolution across cancer types.

MOTIVATION: Intratumor heterogeneity arises from ongoing somatic evolution and complicates cancer diagnosis, prognosis, and treatment. Reconstructing evolutionary dynamics typically requires spatiotemporal samples, which are often unavailable in clinical settings. Computational approaches that can infer tumor evolutionary history from single-timepoint bulk sequencing data remain limited. RESULTS: We present estimating evolutionary events through single-timepoint sequencing (TEATIME), a novel computational framework that models tumors as mixtures of two competing cell populations: an ancestral clone with baseline fitness and a derived subclone with elevated fitness. Using cross-sectional bulk sequencing data, TEATIME estimates mutation rates, timing of subclone emergence, relative fitness, and number of generations of growth. To quantify intratumor fitness asymmetries, we introduce a novel metric-fitness diversity-which captures the imbalance between competing cell populations and serves as a measure of functional intratumor heterogeneity. Applying TEATIME to 33 tumor types from The Cancer Genome Atlas, we revealed divergent as well as convergent evolutionary patterns. Notably, we found that immune-hot microenvironments constraint subclonal expansion and limit fitness diversity. Moreover, we detected temporal dependencies in mutation acquisition, where early driver mutations in ancestral clones epistatically shape the fitness landscape, predisposing specific subclones to selective advantages. These findings underscore the importance of intratumor competition and tumor-microenvironment interactions in shaping evolutionary trajectories, driving intratumor heterogeneity. Lastly, we demonstrate that TEATIME-derived evolutionary parameters and fitness diversity offer novel prognostic insights across multiple cancer types. AVAILABILITY AND IMPLEMENTATION: R implementation of TEATIME is available on GitHub (https://github.com/liliulab/TEATIME) and Zenodo (https://zenodo.org/records/17422174).

Neoplasms↗

PubMed2026

The potential clinical benefit of routine comprehensive genomic profiling in non-small cell lung cancer for the detection of prognostic co-mutations - A multicenter next generation sequencing study.

INTRODUCTION: Non-driver mutations such as TP53, STK11 and KEAP1 are clinically relevant in determining immunotherapy efficacy in patients with non-small cell lung cancer (NSCLC). The aim of this study is to determine the prevalence and clinical relevance of variations in TP53, STK11 and KEAP1 in patients in the analysis of NSCLC, using targeted next-generation sequencing. METHODS: This real-life prospective multicenter cohort study from July 2022 until October 2023 utilized samples of patients in the analysis of NSCLC. The samples were subjected to a targeted DNA NGS panel and, if indicated, RNA sequencing. The outcome of the molecular diagnostics was retrieved, including driver alterations and more in-depth analysis of TP53, STK11 and KEAP1. RESULTS: In 134 of the 437 samples an actionable genomic alteration (AGA) was detected. Of the remaining samples, 213 carried a mutation in either TP53, STK11 and/or KEAP1, while 90 harbored either variants of unknown significance (VUS) (16) or no variant (74). In-depth analysis showed 77 alterations of STK11, with 56 pathogenic and 21 VUS. Most STK11 variants were identified in exon 1, which is hypothesized to be correlated to an oncogenic isoform. Moreover, variants in KEAP1 were mostly VUS, with 48 VUS and 24 mutations. Lastly, 264 TP53 alterations, of which 249 pathogenic and 15 VUS, occurred, with an even spread in the DNA-binding domain. CONCLUSION: This study demonstrated the broad spectrum of variants in STK11, KEAP1 and TP53 in routine panel-based DNA NGS, with 70.3% of the samples without AGA showing a potential clinically relevant mutation in TP53, STK11 and/or KEAP1.

Humans↗