Anopheles mosquitoes are key malaria vectors, their high diversity influences transmission competence. Accurate species identification is crucial for understanding malaria epidemiology and implementing effective vector control strategies. The COX1 gene is a widely used DNA barcoding marker for Anopheles due to its high mutation rate and species-specific variations. This study evaluates the consistency of morphological and molecular identification using COX1, analyzes phylogenetic relationships, and explores the implications of these findings for malaria vector control strategies. Anopheles mosquitoes were collected from Bangsring, Banyuwangi, and Hargowilis, Kulonprogo, Indonesia, two geographically distinct sites with a history of malaria outbreaks. Mosquitoes were collected using human landing catches. Identification was performed morphologically and confirmed by molecular analysis based on COX1 sequences. Phylogenetic tree and genetic distances were analyzed in MEGA11 using the Neighbor-Joining method with the Kimura-2 Parameter model. Morphological and COX1-based identification were mostly consistent; however, specimens identified as Anopheles (An.) aconitus and An. minimus from Hargowilis were molecularly confirmed as An. flavirostris. Phylogenetic analysis revealed eight monophyletic clades with strong bootstrap support (≥99% for six), confirming species groupings. Genetic distance analysis showed An. minimus from Hargowilis clustering more closely with An. flavirostris than with An. minimus from other Asian regions. The dominance of An. sundaicus (68%) in Bangsring and An. flavirostris (13%) in Hargowilis highlights the need for targeted vector control strategies. Misidentification of cryptic Anopheles species may lead to ineffective vector control in specific epidemiological settings. Integrating molecular tools into malaria surveillance can support more accurate species identification and contribute to informed disease prevention strategies.

Reliable taxonomic classification of metagenomic sequences remains constrained by high mutation rates, fragmented assemblies, and large heterogeneous reference databases. HYMET (Hybrid Metagenomic Tool) was developed to overcome these challenges through a two-stage hybrid design combining adaptive Mash-based screening with Minimap2 alignment and a coverage-weighted Lowest Common Ancestor (LCA) classifier. Its sample-adaptive thresholds and on-the-fly reference database construction enable efficient, domain-agnostic classification while maintaining accuracy across divergent genomes. Across seven CAMI assembly datasets in contig mode, HYMET achieved a mean F1 of 83.89%, with genus-level F1 of 76.75% and species-level F1 of 60.18%, while averaging 115.93s runtime and a mean peak memory of 6.24GB. Performance remained stable under mutation rates up to 30% for most domains (F1 ≥ 0.8), with viral sequences showing the expected decline (F1 ≈ 0.5 at 30%). Read and contig inputs produced nearly identical results when sharing reference caches, and real-world datasets confirmed robustness with the human gut metagenome reproduced typical anaerobic profiles, while in the ZymoBIOMICS mock community HYMET recovered all bacterial members; a further ground-truth evaluation on the ZymoBIOMICS Gut Microbiome Standard (D6331) yielded near-perfect genus-level concordance (Pearson r = 0.998, Bray-Curtis =0.04) across bacteria, fungi, and archaea. HYMET achieves a practical balance of accuracy, efficiency, and scalability for metagenomic classification. Its adaptive candidate selection, alignment-anchored taxonomy, and reproducible reference caching collectively enhance performance across domains. HYMET source code is fully available at https://github.com/ieeta-pt/HYMET.

Frequent HIV-1 recombination among MSM in Beijing revealed by subtyping and near full-length genome analyses.

DNA mutation rates in evolution, longevity, and disease: An evolutionary and biological trade-off

Benzo[a]pyrene promotes gastric cancer progression via activation of the Correa cascade through modulation of the STAT3-TP53-MMP9 molecular axis.

Exploring the efficiency of different sets of microhaplotypes for first to third degree kinships.

Identification and vaccine efficacy evaluation of a canine coronavirus isolated in central China.

Clinicopathologic characteristics, genomic signatures, and outcomes of patients undergoing resection for early- versus late-onset colorectal liver metastasis.

Real-world evidence regarding the use of dacomitinib as a first-line therapy for advanced non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations remains limited. This multicenter, retrospective cohort study aimed to evaluate the clinical outcomes of dacomitinib as a first-line treatment in patients with untreated advanced EGFR-mutant NSCLC without brain metastases. This retrospective analysis included 161 patients with stage IIIB/IV EGFR-mutant NSCLC without brain metastasis at baseline who received first-line dacomitinib between October 2020 and August 2023 at four Taiwanese cancer centers. The primary outcomes included the objective response rate (ORR), progression-free survival (PFS), overall survival (OS), predictive risk factors for PFS, and adverse events (AEs). The ORR was 64.0%, and the disease control rate (DCR) reached 91.3%. The median PFS was 20.93 months (95% CI: 17.55-24.32), and the median OS was 41.27 months (95% CI: 31.71-50.82). Multivariate analysis revealed that an Eastern Cooperative Oncology Group (ECOG) performance status (PS) ≥ 2, bone metastasis, and liver metastasis were independent predictors of shorter PFS. Among patients who experienced disease progression and underwent rebiopsy, the secondary T790M mutation rate was 50.6%. Most treatment-related AEs were grade 1-2 and manageable. Dacomitinib demonstrated favorable efficacy and tolerability as a first-line therapy in advanced NSCLC patients with common EGFR mutations (exon 19 deletion or L858R). A baseline ECOG PS ≥ 2 and the presence of bone or liver metastases were significantly associated with worse PFS, suggesting a need for additional therapeutic strategies in these subgroups.

Lineage tracing techniques have been developed rapidly in the past decades by employing new genetic engineering tools. However, due to their invasive nature, these are difficult to apply to humans. Although endogenous DNA mutations can be used for in vivo lineage tracing in humans, their extremely low mutation rate presents substantial technical challenges. Epimutations on DNA methylation happen at a rate of about 0.001 per CpG site per division. Such rich and stable information enables high-resolution, noninvasive lineage tracing in humans, as recently achieved with both MethylTree and EPI-Clone. MethylTree is a computational innovation that accurately predicts cell lineages from single-cell DNA methylation data, be it genome-wide or targeted. EPI-Clone is a targeted approach that requires careful CpG panel selection for specific tissues, which has been validated in blood. In this review, we present an overview of related historical studies, discuss the development of both MethylTree and EPI-Clone, and compare these two approaches. Although EPI-Clone is more scalable and cheaper, MethylTree has a higher resolution and works directly across different tissues. We demonstrate here that MethylTree also works well with EPI-Clone data, thus providing a unified solution for epimutation-based lineage tracing. Finally, we highlight the advantages of epimutation-based lineage tracing, discuss future directions for tool development, and touch on considerations in biological applications. Epimutation-based lineage tracing opens up an exciting avenue for noninvasive lineage tracing in humans across many biological processes.

Cyanobacteria represent an ancient group of photosynthetic microorganisms that offer unparalleled insights into evolutionarily conserved stress adaptation mechanisms essential for plant resilience. To investigate how photosynthetic organisms mitigate chemical stressors, we employed Synechocystis sp. PCC 6803-a keystone model for photosynthetic research due to its plant-like electron transport chain and stress-responsive plasticity. By implementing a genomic hypermutation strategy, we synergistically knocked out DNA replication fidelity genes and overexpressed error-prone replication elements, generating hypermutable strains HM24 and HM33 with relative mutation rates of 97 and 116-fold, respectively. Following triclosan (TCS) stress screening, the CRISPR-Cpf1 strategy was used to complement mutations and yielded transformants R-HM24 and R-HM33 that exhibited 96h EC50 values of 4.963 mg/L and 5.238 mg/L-322- and 340-fold increases over wild-type levels. The strains demonstrated enhanced TCS and multidrug antibiotic tolerance. Whole-genome resequencing identified consistent missense mutation in fabI across resistant strains. Mechanistic analyses revealed that the hypermutated Synechocystis strains acquired resistance primarily by mutating the essential fabI protein to decrease its affinity for TCS. This study establishes the application of hypermutation-driven evolution for rapid dissection of pollutant resistance in photosynthetic microbes, thereby advocating for stricter regulation of antimicrobial pollutants in aquatic environments.

Objective: To investigate the mutation status of breast cancer susceptibility genes (BRCA) in colorectal cancer and the relationship between BRCA and the clinical-pathological characteristics and prognosis of colorectal cancer. Methods: A total of 132 colorectal cancer tissue specimens surgically resected at Shanxi Cancer Hospital from 2018 to 2021 were collected. Second-generation sequencing was used to detect BRCA mutations. Immunohistochemical staining assessed the infiltration density of CD3+, CD4+, and CD8+ T cells, and CD20+ B cells. The association between BRCA mutations and clinical-pathological features, immune cell infiltration density, and prognosis of colorectal cancer was analyzed. Results: Among 132 colorectal cancer cases, the overall BRCA mutation rate was 9.09% (12/132), with BRCA1 mutation rate at 3.03% (4/132) and BRCA2 mutation rate at 6.06% (8/132). Compared with the BRCA wild-type group, the BRCA mutation group exhibited smaller tumors (P=0.036), less vascular or nerve invasion (P=0.041), and lower tumor budding grades (P=0.013). Tumor microenvironment analysis revealed that the infiltration densities of CD3+, CD4+, and CD8+ T cells in the BRCA mutation group were 1 729.66 (652.91, 3 065.98)/mm², 438.36 (97.37, 718.43)/mm², and 1 017.86 (506.19, 2 257.35)/mm², respectively, all higher than those in the BRCA wild-type group [555.72 (304.58, 933.26)/mm², 89.34 (58.15, 178.35)/mm², and 354.23 (157.78, 752.37)/mm², respectively, all P＜0.05]. Molecular feature analysis revealed five cases of TMB-H in the BRCA-mutant group and three cases in the BRCA-wild group, with a statistically significant difference between the two groups (P＜0.001). Survival analysis revealed no association between BRCA mutation status and overall survival in colorectal cancer patients (P＞0.05). Multivariate Cox regression analysis identified clinical stage as an independent predictor of overall survival, with patients at stages Ⅲ-Ⅳ exhibiting poorer prognosis (HR=5.359, 95% CI: 1.124-25.546). Conclusion: BRCA-mutated colorectal tumors exhibit lower invasiveness, higher TMB-H rates, and abundant immune cell infiltration in the tumor microenvironment, suggesting that patients with BRCA-mutated colorectal cancer are more likely to benefit from immunotherapy.

ABSTRACT A precise diagnosis and customized treatment become more difficult by the genomic heterogeneity of breast cancer (BRCA). In order to examine gene expression data from two separate Gene Expression Omnibus (GEO) microarray datasets, we used a integrative approach in this study that combined bioinformatics and machine learning. We were able to distinguish between universal and subtype-specific transcriptome patterns by identifying both common and subtype-specific differentially expressed genes (DEGs) using dual-level differential expression analysis. Functional enrichment analysis and the creation of protein-protein interaction networks identified important hub genes, including TPM3, MYLK, and COL17A1, which showed substantial dysregulation and were linked to high mutation rates and a bad prognosis. Survival analyses, which identified COL17A1 as a predictive predictor for the general population and MYLK for the Luminal B subtype, highlighted the clinical significance of these hub genes. We used both Random Forest and K-Nearest Neighbors classifiers to ensure robust biomarker identification. In the analysis, we prioritized 35 model-agnostic biomarkers that performed well in subtype categorization, such as PNMT and KRTAP10-8. This dual-model approach improved the reliability of biomarker identification while reducing model-specific biases. These results set the stage for early identification, more accurate subtype classification, and possible therapeutic targeting in breast cancer.

ABSTRACT It is well established that radiation effects on wild organisms from nuclear power plant accidents primarily depend on the dose received at the accident; however, impacts of prolonged low-dose exposure remain poorly understood. In this study, oxidative DNA damage in Pinus densiflora, assessed via 8-OHdG levels, was compared between inside (0.87–7.74 μSv/h) and outside (0.094–0.16 μSv/h) the difficult-to-return zone 10 years after the Fukushima accident. Leaf 8-OHdG levels varied among the sites but were unrelated to the absorbed dose. In buds, 8-OHdG levels were very low. An irradiation experiment on 2-year seedlings using Cs-137 at three dose rates (44.8, 461, 1738 mGy/h) also found no association between dose rate and 8-OHdG levels; only sampling points correlated with 8-OHdG levels. In contrast, both dose rate and 8-OHdG levels negatively affected seedling survival after the irradiation experiment. Even without irradiation, samples with >0.04% 8-OHdG did not survive. These results suggest 8-OHdG status indicates seedling health and that environmental stress induces oxidative stress via photosynthesis disruption. Additionally, microsatellite mutation rate in megagametophytes was assessed in 1136 seeds using nine markers, detecting only one mutation in contaminated areas, not statistically significant. This mutation rate was too low for sufficient statistical power. In this study, no evidence was found that low-dose chronic exposure affects oxidative DNA damage or mutation rate in P. densiflora. To understand the impact of low-dose chronic radiation exposure on wild plants, further studies incorporating environmental stress and using endpoints other than mutations, such as genome methylation levels and/or responses to oxidative stress, are necessary.

Various poly(ADP-ribose) polymerases (PARPs) are known to be related to DNA repair, and PARP7 has been linked to estrogen signaling and immunity. Recently, PARP7 was shown to increase cancer cell proliferation, but reports are conflicting. Given that these studies are mostly based on in vitro experiments, this study investigated how PARP7 expression impacts breast cancer patients. Clinical and transcriptomic data of breast cancer patients were obtained from the METABRIC (n = 1904), TCGA (n = 1090), and SCAN-B (n = 3069) cohorts. The median value was used to divide the cohorts into high- and low-PARP7 groups. High PARP7 expression was significantly associated with better overall survival in two of the three cohorts (p < 0.05), and PARP7 was expressed predominantly by epithelial cells (p < 0.001). Estrogen receptor (ER)-positive breast cancer had a higher expression of PARP7 than other subtypes (p < 0.001). High PARP7 expression was associated with high estrogen and androgen response consistently in all cohorts. Tumors expressing higher PARP7 levels had significantly lower mutation rates, neoantigens, type 1 interferon (IFN-1), and immune cell infiltration in (p < 0.001). High PARP7 expression was associated with less enrichment of cell proliferation-related gene sets (E2F targets, G2M checkpoint, and MYC targets), in all cohorts. Higher PARP7 expression was associated with less cancer cell proliferation, lower tumor grade, and lower Ki67 (p < 0.001). High PARP7 expression is associated with estrogen and androgen response, but also with better overall survival and lower cell proliferation.

The wildlife–livestock interface (WLI) serves as a critical hotspot for zoonotic spillover of emerging viral pathogens, facilitating the transmission of viruses from wildlife reservoirs to livestock (as intermediate or bridge hosts) and subsequently to humans. This review synthesizes the multi-scale mechanisms underpinning viral spillover, including ecological drivers (such as habitat fragmentation, deforestation, intensive farming, wildlife trade, and climate change), genetic plasticity of RNA viruses (high mutation rates, quasi-species diversity, and recombination), cellular compatibility (receptor usage and tissue tropism), and viral evasion of innate immune responses (interferon antagonism via proteins like NS1, V, VP35). Special emphasis is placed on how livestock act as amplification or mixing vessels, enabling adaptation before human infection. Key case studies illustrate these processes: Henipaviruses (Nipah and Hendra viruses) demonstrate bat-to-pig/horse-to-human pathways or direct bat-to-human routes influenced by strain-specific pathogenesis and cultural practices; MERS-CoV highlights source-sink dynamics in dromedary camels with seasonal spillover linked to calving cycles. The document also explores the debated biodiversity-disease relationship (dilution vs. amplification effects), network ecology for identifying bridge hosts (rodents in human-dominated landscapes), and anthropogenic factors amplifying risk. Effective mitigation requires a One Health approach integrating surveillance in biodiversity hotspots, biosecurity at interfaces, predictive AI modeling, and global data sharing to anticipate and prevent future spillovers of viruses with pandemic potential.

Homing-based CRISPR-Cas9 gene drives (CCGDs) are powerful tools for genetic control of wild populations, with applications from disease eradication to species conservation. However, Cas9 alone and in a complex with guide RNA can cause double-stranded DNA breaks at off-target sites, which could increase the mutational load and lead to unintended loss-of-heterozygosity (LOH) events. These undesired effects raise potential concerns about the long-term evolutionary safety of CCGDs, but the magnitude of these effects is unknown. To measure how the presence of a CCGD or a Cas9 alone in the genome affects the rates of LOH events and de novo mutations, we carried out a mutation accumulation experiment in yeast Saccharomyces cerevisiae. We found no detectable effects on the genome-wide rates of mutations or LOH events. Our power calculations suggest that CCGD or Cas9 affect these rates by less than 30%, which is much less than natural variation for these traits in yeast. A more detailed examination shows that CCGD or Cas9 may alter the lengths and genomic distributions of LOH events, but the statistical support for these effects is weak. Thus, our results demonstrate that CCGDs impose at most a weak additional mutational burden in the yeast model. Although mutagenic effects of gene drives need to be further evaluated in other systems, our results add credence to the proposition that the evolutionary risks posed by well-designed gene drives may be acceptable.

Dissimilatory metal-reducing bacteria are found worldwide and encode diverse multiheme cytochromes with properties suitable for applications in bioremediation, bioenergy, and bioelectronics. We find that multiheme cytochromes involved in extracellular electron transfer show poor conservation, with significantly higher mutation rates than other elements of the proteome. This previously undescribed characteristic will limit the efficacy of standard methods of homolog annotation and database mining currently used to identify specific multiheme cytochromes. Our findings also suggest that a vast pool of undiscovered multiheme cytochromes are constantly being acquired and exchanged.

Abstract Background: As the MBC treatment landscape evolves, understanding ESR1m testing patterns for ER+, HER2- MBC is essential to identify patients for targeted therapies. Despite existing guidelines recommending testing of patients with MBC at progression for ESR1m, real-world data on testing and mutation rates are limited. Therefore, we described ESR1m testing and positivity (+) rates in patients with ER+, HER2- MBC to identify opportunities for improved ESR1m test utilization. Methods: This retrospective, observational study included patients aged ≥18 years at ER+, HER2- MBC diagnosis (Dx) who initiated 1st line (1L) therapy with aromatase inhibitors (AI) or selective estrogen receptor degraders (SERDs) ± CDK4/6 inhibitors (CDK4/6i) from 1/1/20-3/31/25. Flatiron Health Research Database (FHRD), a de-identified US-based electronic health record database, was used to estimate ESR1m+ rates in windows defined as: A) initial early breast cancer (EBC) Dx date or 90 days before de novo MBC Dx to last patient contact, B) MBC Dx date to 1L initiation date+28 days, C) during line of therapy (LoT;start to end date), and D) at LoT initiation (90 days before to 28 days after LoT initiation). Results: Of all 12148 patients, 48% (n=5874) had ≥1 ESR1m test and most tested patients (n=3650/5874; 62%) were tested only once (mean:1.6 test/patient). Among all patients, testing rates were similar at each LoT initiation (25-29%). In exploratory analyses of all patients, post-2023 testing rates were often higher than pre-2023, especially at 1L (34 vs 20%) and 2L initiation (36 vs 26%). When considering patients with data available on ESR1m testing by sample type (n=2028), ∼60% were in tissue only and ∼40% were in blood only. Among a subgroup of patients with de novo MBC who received 1L AI±CDK4/6i, testing rates at 2L and 3L initiation were 27-28%. For the subgroup of patients with EBC who relapsed and developed MBC while on adjuvant AI±CDK4/6i or ≤12 months after completion, the testing rate was the highest during 1L (38%). Among all patients, ESR1m+ was 15% during 1L and increased to 37% at 3L initiation. Among patients with de novo MBC (received 1L AI±CDK4/6i), ESR1m+ was highest at 3L initiation (40%). Among the relapsed patients, ESR1m+ was 23% at 1L initiation, 31% at 2L initiation, and 33% at 3L initiation. Conclusion: Among all patients with MBC, 52% were never tested and only 34-36% were tested at 1L and 2L initiation from 2023 onward. Importantly, lower rates of ESR1m+ were observed in the real-world compared to clinical trials. This may be due to suboptimal test timing, poor patient identification for testing, and frequent use of tissue-based testing, which is less sensitive than the recommended blood-based ctDNA used in clinical trials. These results highlight an unmet need for increased ESR1m testing using blood-based ctDNA to optimize patient identification for targeted therapies in ER+, HER2- MBC. Citation Format: C. Liao, N. Bansal, J. John, M. Bhave, F. Bidard, T. Marquart, A. Chawla, L. Williams. Real-world ESR1 mutation (ESR1m) testing and positivity rates in patients with ER+, HER2- metastatic breast cancer (MBC) [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-12-08.

Abstract Background: Endocrine resistance in ER+/HER2- metastatic breast cancer is frequently mediated by ESR1 mutations. These mutations typically arise after prolonged endocrine therapy (ET) exposure in the metastatic setting, particularly with aromatase inhibitors (AI). This study evaluates the real-world evidence incidence and prognostic impact of ESR1 mutations in Spanish patients (pts) with ER+/HER2- advanced breast cancer (ABC) progressing on 1st line CDK4/6 inhibitor (CDK 4/6i) + ET. Methods: The GEICAM/2014-03 RegistEM study (NCT02819882) is an ongoing non-interventional cohort that collects prospective data and biological samples from patients with ABC, across 38 sites in Spain. A subset of 125 pts with ER+/HER2- ABC and available plasma samples collected at progression after 1st line with CDK4/6i + ET (n=125) was analyzed using the Plasma-SeqSensei™ BC IVD kit (Sysmex Inostics) to identify and quantify ctDNA mutations in six BC-related genes, ESR1, AKT1, ERBB2, KRAS, PIK3CA and TP53. Median PFS and OS were estimated from the Kaplan-Meier survival curves. Hazard ratios with 95% confidence intervals were obtained from multivariable Cox regression and logistics regression models, adjusted by clinical confounders (age, first metastatic, visceral disease, prior sensitivity to ET). Results: ESR1 mutation rates after progression on 1st line CDK4/6i + ET were 41.6%. The incidence of mutations increased with longer duration of 1st line therapy and varied according to the ET partner. Among patients treated with fulvestrant (FULV), mutation frequencies were 15.8% for &amp;lt;12 months, 50.0% for 12-24 months, and 14.3% for &amp;gt;24 months. In contrast, with aromatase inhibitors (AI), frequencies were 22.2%, 61.1%, and 65.2%, respectively. Overall, The most common ESR1 mutations were D538G (28%), Y537S (17%), Y537N (16%), and E380Q (11%), all more common with AI than with FULV. Specifically, D538G was found in 35% of AI-treated patients vs. 11% with FULV; Y537S in 21% vs. 8%; Y537N in 21% vs. 3%; and E380Q in 12% vs. 8%. The detection of ESR1 mutations after CDK4/6i + ET was significantly associated with shorter mPFS, and showed a consistent trend toward worse OS, particularly with polyclonal ESR1 mutations (Table 1). Co-occurrence of ESR1 with PIK3CA/AKT1 or TP53 mutations was in 16.8% and 14.4%, respectively. The negative impact of ESR1 mutations on PFS and OS was independent of co-mutations in PIK3CA/AKT1 or TP53. Conclusions: ESR1 mutations are frequent after progression on CDK4/6i + ET, particularly following &amp;gt;1 year of AI, and are associated with poorer outcomes, especially when polyclonal. Their prognostic impact is independent of co-mutations in PIK3CA/AKT1 and TP53 and varies according to specific ESR1 variants. These findings support the use of ESR1 mutation profiling to guide treatment decisions post-CDK4/6i. Citation Format: Á. Guerrero-Zotano, S. Antolín, A. Tibau Martorell, J. Cruz-Jurado, R. Andrés, S. Saura, C. Rodríguez-Sánchez, E. Galve, C. Falo, M. Margelí-Vila, Á. Rodríguez-Lescure, A. Miguel, J. Chacón, E. Adrover-Cebrian, M. Corbellas -Aparicio, M. Marin-Alcalá, I. González-Maeso, S. Varela-Ferreiro, C. Arqueros, A. Antón-Torres, S. Servitja, D. Moreno-Muñoz, M. Merino, A. Ballesteros-García, M. Echarri-González, J. Alonso-Romero, R. Seijas Tamayo, V. Iranzo-Cruz, J. De la Haba-Rodríguez, J. Guerra, L. Palomar Abad, J. Illarramendi Mañas, A. Godoy Ortiz, A. García-Palomo, M. Ruíz-Borrego, R. Villanueva, S. Zazo, Y. Jerez-Gilarranz, C. Reboredo Rendo, N. Ancizar Lizarraga, I. Ceballos-Lenza, L. Murillo Jaso, L. Figuero, J. Herranz, N. Martín, D. Fernández-García, I. Álvarez López, S. López-Tarruella, F. Rojo Todo. Frequency and Prognostic Significance of ESR1 Mutations Post-CDK4/6 inhibitors in ER+/HER2− Metastatic Breast Cancer: Real-World Data from the GEICAM_RegistEM Study [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-12-17.