SEARCH · Search PubMed

Results for “STK11”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

13 recordsLinked to original sources

PubMed2026

STK11 Mutations and Deletions Define an Aggressive Molecular Subgroup of Cervical Adenocarcinoma.

Cervical adenocarcinoma accounts for 15%-20% of cervical cancers and is associated with poorer survival and reduced response to screening and immunotherapy compared with squamous cell carcinoma (SCC). The genomic drivers underlying this molecular subgroup remain incompletely characterized. Whole-exome sequencing was performed on 302 invasive cervical cancers from Guatemala and Venezuela. Structural variation analysis was conducted using SNP-array and whole-genome sequencing data. Findings were replicated in more than 4600 additional cervical cancer samples from TCGA, AACR Project GENIE, MSKCC, and Caris datasets. TP53 mutations were more frequent in adenocarcinoma than SCC, particularly in HPV-negative tumors. STK11 alterations, including mutations and focal deletions, were significantly enriched in HPV-positive adenocarcinomas compared with SCC and affected 23% of adenocarcinomas overall. Whole-genome analyses identified recurrent focal deletions, inversions, chromosomal rearrangements, and breakage-fusion-bridge events involving chromosome 19p and STK11 that were not detected by exome sequencing alone. STK11 alterations were associated with younger age at diagnosis, poorer overall survival, and inferior outcomes following immune checkpoint inhibitor (ICI) therapy. STK11 alterations significantly co-occurred with YAP1 amplification but were largely mutually exclusive with PIK3CA mutation. Cervical adenocarcinomas also demonstrated significantly lower CD274 (PD-L1) expression than SCC. STK11 alterations define a distinct molecular subgroup of cervical adenocarcinoma characterized by structural disruption of chromosome 19p, younger age at onset, and poorer clinical outcomes. These findings have implications for molecular classification and future targeted therapeutic approaches in cervical cancer.

Humans↗

PubMed2026

Genetic and biochemical screens identify MGAT1 as a druggable glycosyltransferase target in STK11-mutant lung cancer.

Checkpoint inhibitors are standard-of-care therapies for non-small cell lung cancer (NSCLC), but their efficacy is limited in tumors with STK11 mutations, highlighting the need for new therapeutic strategies. Here, we performed complementary in vivo and in vitro CRISPR-Cas9 functional genomic screens to identify genes whose loss restores sensitivity to anti-PD-1 therapy. We found that loss of MGAT1, a Golgi glycosyltransferase critical for the maturation of high-mannose N-glycans into hybrid and complex glycan structures, reversed resistance to anti-PD-1 treatment in syngeneic mouse tumor models harboring STK11 mutations. Parallel co-culture screens with antigen-matched CD8+ T cells further showed that disruption of N-glycosylation strongly sensitized tumor cells to T cell-mediated killing. Genetic rescue studies demonstrated that this immune-evasion phenotype depends on MGAT1 catalytic activity, supporting direct biochemical interrogation of the enzyme. Using purified human MGAT1 and a UDP-Glo™ glycosyltransferase assay, we established a tractable screening platform and performed a 500,000-compound biochemical high-throughput screen, identifying an initial hit (compound 1; IC50 = 197 μM). Subsequent medicinal chemistry optimization delivered progressively more potent analogs, including TNG-9333 (0.814 μM) and TNG-2673 (0.043 μM) and represented a >1000-fold improvement in biochemical potency from the starting hit. Crystal structures of human MGAT1 in apo, UDP-bound, UDP-GlcNAc-bound, and inhibitor-bound states, together with SPR and DSF analyses, revealed that this chemical series engages a previously unrecognized allosteric pocket and inhibits MGAT1 through a UDP-noncompetitive mechanism. Collectively, our work implicates N-glycosylation as a key mediator of immune evasion and establishes MGAT1 as a ligandable, structurally tractable target for small-molecule drug discovery.

CRISPR/Cas9 target discovery↗

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↗

PubMed2026

Quantifying uncertainty of predictions from cancer progression models.

MOTIVATION: Cancer progresses through the accumulation of genomic events. Cancer progression models such as Mutual Hazard Networks (MHNs) describe this dynamic, enabling prediction of temporal event positions and patient-specific risks of acquiring mutations. However, current MHN analyses rely on single most likely models and do not quantify the uncertainty inherent to parameter estimation. Assessing forecast stability is essential before using them to anticipate treatment-relevant mutations, adapt targeted therapies, or prioritize monitoring of patients at elevated progression risk. RESULTS: We address a key prerequisite for the responsible clinical use of cancer progression models by making MHN-derived predictions uncertainty-aware. We present a Bayesian framework for MHN that uses Markov Chain Monte Carlo to sample from the posterior distributions of model parameters and derived predictions. For practical use we implemented the Random-Walk Metropolis, Metropolis-Adjusted Langevin Algorithm (MALA), and simplified manifold MALA samplers as part of the existing mhn Python package. Only MALA and smMALA were successful in sampling from MHN posteriors, with MALA performing best. While most MHN parameters and predictions showed low posterior variance, a small subset displayed greater variability across the posterior distribution. This differentiation cannot be obtained from a single most likely model, emphasizing the need for uncertainty quantification, especially in clinical contexts. As an illustrative example, posterior sampling identified a subgroup of STK11$-$, KRAS$+$ lung adenocarcinoma patients with a high predicted short-term risk-with low variance across posterior samples-to develop an STK11 mutation. This subgroup exhibited poorer survival under immunotherapy, resembling patterns observed in STK11+ patients. AVAILABILITY AND IMPLEMENTATION: Our implementation is part of version 1.2.0 of the mhn package (https://github.com/spang-lab/LearnMHN). All analyses including the code to produce all figures in this article can be found under https://github.com/huy29433/MCMC-sampling-for-MHN (https://doi.org/10.5281/zenodo.21160219).

Humans↗

PubMed2026

Genome-wide CRISPR screens map synthetic lethal interactions across recurrent cancer driver alterations.

Synthetic lethality (SL) provides a treatment paradigm for targeting cancer with alterations in driver genes that are not conventionally druggable, including tumor suppressor genes. We execute a series of genome-wide CRISPR screens using functionally validated isogenic cell lines and conduct a large-scale SL analysis using data from the cancer dependency map (DepMap). We chart SL interactions across 15 driver alterations: FBXW7, CCNE1, CDK12, ARID1A, KMT2D, DNMT3A, TET2, KEAP1, STK11, IDH1, SF3B1, SRSF2, U2AF1, chromosome 18q loss, and chromosome 13q loss. We show validation of several SL interactions, including ARID1A and the hexosamine biosynthetic pathway aminotransferase GFPT1, STK11 with CAMK protein kinase MARK2, FBXW7 and the CDK1 regulatory kinase PKMYT1, and CCNE1 amplification and the anaphase-promoting complex or cyclosome (APC/C). In summary, this study offers a rich resource of genetic interactions across cancer drivers enabling the discovery of biological insights and drug targets for future therapeutic development.

CP: cancer↗

PubMed2025

Distinct Clinicogenomic Features and Immunotherapy Associations in Pulmonary Sarcomatoid Carcinoma: A Multicenter Retrospective Study.

INTRODUCTION: Pulmonary sarcomatoid carcinoma (PSC) is a rare NSCLC subtype with poor prognosis. Outcomes to immune checkpoint inhibitors (ICIs) and genomic features in PSC remain underexplored compared with other NSCLC subtypes. METHODS: Patients from three institutions and the National Cancer Database (NCDB) with metastatic NSCLC treated with ICI alone or with chemotherapy were identified. Clinicogenomics and treatment outcomes were compared across PSC, lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC). RESULTS: We analyzed 4841 patients including 165 PSC cases treated with ICI-based therapy from three institutions and 201 PSC from NCDB. In MDACC, 65 (4.3%) were PSC, 1138 (75.1%) LUAD, and 312 (20.6%) LUSC. Patients with PSC were older and more likely to present with metastatic disease. In both the MDACC and NCDB cohorts, ICIs resulted in better outcomes for patients with PSC compared with chemotherapy. In these patients, there was no difference in outcome between ICI-monotherapy and ICI-chemotherapy. Across the three institutional cohorts, 37% to 43% of patients with PSC who received ICIs were responders, compared with 26% to 29% in LUAD and 22% to 46% in LUSC (p < 0.05). Improved ICI outcomes in PSC appeared driven by high PD-L1 (≥50% in 73%-77% cases). Among patients with high PD-L1, response rates were similar across histologic subtypes. Conversely, TMB was similar in PSC compared with LUAD or LUSC and was not associated with ICI outcomes. Across cohorts, PSC tumors were enriched for TP53, NF1, NF2, and NRAS, with relative depletion of STK11 and KEAP1 compared with LUAD. Case observation revealed relatively better outcomes to ICI than targeted therapies in patients with PSC with MET exon 14 skipping or KRAS G12C. CONCLUSION: PSC exhibits improved outcomes to ICI relative to other therapies, potentially driven by high PD-L1 expression. Genomic analysis highlights a distinct genomic landscape of PSC when compared with LUAD.

Humans↗

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

Molecular analysis of lung adenocarcinomas from the SAFIR02-Lung cohort reveals new metastasis-associated copy-number alterations including frequent mutant-specific KRAS-allelic imbalance and identifies CDKN2A homozygous deletions as an independent biomarker of poor prognosis.

BACKGROUND: Identifying molecular alterations specific to advanced lung adenocarcinomas could provide insights into tumour progression and dissemination mechanisms. METHOD: We analysed tumour samples, either from locoregional lesions or distant metastases, from patients with advanced lung adenocarcinoma from the SAFIR02-Lung trial by targeted sequencing of 45 cancer genes and comparative genomic hybridisation array and compared them to early tumours samples from The Cancer Genome Atlas. RESULTS: Differences in copy-number alterations frequencies suggest the involvement in tumour progression of LAMB3, TNN/KIAA0040/TNR, KRAS, DAB2, MYC, EPHA3 and VIPR2, and in metastatic dissemination of AREG, ZNF503, PAX8, MMP13, JAM3, and MTURN. Conversely, no meaningful difference was found in pathogenic single-nucleotide variant frequencies, reinforcing the notion that they are early events in tumorigenesis. CDKN2A homozygous deletion was linked to poor clinical outcome in patients with early tumours (overall survival hazard ratio 2.17, 95% CI: 1.43-3.28, corrected p-value = 0.01). Furthermore, we found that KRAS mutant allele specific imbalance, i.e. focal amplification of the mutant allele, is more prevalent in locoregional or distant samples of metastatic patients than in early lesions (8.4%, 13% and 2.8% respectively). This observation was replicated in three public cohorts. Tumours with KRAS mutant allele specific imbalance show specific patterns of co-occurrence and mutual exclusion with alterations in key cancer genes like CDKN2A, TP53, STK11 and NKX2-1, often in a tumour type dependent manner. CONCLUSION: Advanced LUAD tumours exhibit higher copy-number alteration burden, with distinct alterations associated with tumour progression and metastasis. CDKN2A homozygous deletions predict poor prognosis in early disease, while KRAS mutant allele-specific imbalance is enriched in advanced tumours.

Humans↗

PubMed2026

Liquid biopsies reveal dual compartments of cancer risk from tumor and host-derived mutations.

MOTIVATION: Circulating tumor DNA (ctDNA) and clonal hematopoiesis of indeterminate potential (CHIP) are two biologically distinct sources of somatic mutations detectable in blood. While ctDNA captures tumor-intrinsic alterations, CHIP arises from age-related hematopoietic clones and is often considered background noise. Here, we conduct a large-scale, tumor-type-resolved analysis of over 9000 patients with CHIP data and 1500 patients with ctDNA data across solid tumors profiled at Memorial Sloan Kettering Cancer Center. RESULTS: Our results reveal that CHIP and ctDNA mutations exhibit non-overlapping, clinically meaningful signals. CHIP mutations, particularly in DNA damage response and epigenetic regulators (e.g. PPM1D, CHEK2, ATM, TP53, ASXL1), are associated with worse overall survival, increased metastatic potential, and site-specific dissemination. ctDNA mutations in canonical oncogenic drivers (e.g. TP53, EGFR, KRAS, STK11) reflect tumor aggressiveness and correlate with poor prognosis and metastasis across multiple cancer types. Joint modeling in lung adenocarcinoma confirms the independent prognostic contributions of both compartments. Additionally, longitudinal clonal analysis links specific CHIP mutations to the emergence of hematologic malignancies under therapeutic pressure. These findings support a dual-compartment model of liquid biopsy, in which tumor- and host-derived mutations jointly inform on cancer risk, progression, and metastatic behavior. Integrating both compartments may enhance the clinical utility of blood-based biomarkers in oncology. AVAILABILITY: All genomic and clinical data used in this study are available through cBioPortal. Summarized outputs and processed results tables are provided in Supplementary Data.

Humans↗

PubMed2026

RAS signaling in lung adenocarcinoma is defined by lineage context and DUSP4 loss.

BACKGROUNDThe molecular landscape of lung adenocarcinoma (LUAD) is often illustrated as a driver-oncogene pie chart, but identical mutations exhibit heterogeneous signaling shaped by comutations, transcriptional programs, and lineage context. We propose a lineage-integrated signaling framework using an EGFR mutation signature (mSig).METHODSWe defined EGFR mSig using differentially expressed genes in EGFR-mutant (EGFR-mt) LUADs. Semisupervised clustering and machine learning models were used to test reproducibility in different combinations of datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and EGFR copy number alterations in EGFR mSig-defined subtypes of LUAD.RESULTSEGFR mSig showed robust classification performance (area under receiver operating characteristic curve = 0.83-0.95; mean negative predictive value = 96.3%). Validated gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. Most EGFR mSig+ tumors, including many without EGFR mutations, belonged to the bronchioid subtype. A subset of canonical RAS mutations were mSig+ and mirrored the EGFR mutation pattern. EGFR WT/mSig- tumors were enriched for nonbronchioid subtypes and had comutations in TP53 or RAS/RAF/RTKs. We highlight a parsimonious collection of coordinated mutations, including RAS, KEAP1, STK11, TP53, and CDKN2A, that taken together suggest coordination of tumor signaling previously suggested but now reproduced and expanded.CONCLUSIONA potentially novel EGFR mSig that captures the transcriptional footprint of EGFR activation revealed a subset of EGFR WT LUADs with mt-like features. mSig refines LUAD taxonomy beyond mutation-only pie-chart models by incorporating lineage and comutation context. Lineage-directed stratification with coalteration identifies clinically relevant groups across EGFR and RAS states and highlights treatment opportunities for patients currently considered oncogene-negative.FUNDINGNational Cancer Institute (NCI) U01CA272541, R01CA262296, U24CA264021, UG1CA233333, R01CA211939.

Humans↗

PubMed2026

Real-World Treatment Patterns and Clinical Outcomes After First-Line Therapy in Patients with KRAS G12C-Mutant Advanced Non-Small-Cell Lung Cancer in the United States.

BACKGROUND: Approximately 13% of NSCLC cases have KRAS G12C mutations. As therapeutic strategies targeting KRAS G12C-mutant NSCLC evolve, it is important to understand clinical presentation and current outcomes for these patients. METHODS: This retrospective study used data from two US nationwide databases, an electronic health records (EHR) database and a clinico-genomic database (CGDB) of EHR data linked to data from comprehensive genomic profiling tests. Eligible patients had advanced NSCLC, initiated first-line therapy from August 2018 to December 2022, and had KRAS test results. Clinicopathologic characteristics, treatments, real-world progression-free survival (rwPFS), and overall survival (OS) were analyzed. RESULTS: There were 1227 patients with KRAS G12C-mutant NSCLC in the EHR database and 447 in the CGDB. First-line regimen was platinum-based chemotherapy plus pembrolizumab for 46% and pembrolizumab monotherapy for 20%. Less than 40% of patients received second-line therapy. Median (95% CI) OS for KRAS G12C-mutant NSCLC patients in the EHR was 17.0 (15.2-18.9) months. Variables significantly associated with shorter OS included PD-L1 <1%, brain metastases, STK11 co-mutation, and poor performance status. Patients treated with platinum-based chemotherapy plus pembrolizumab had median rwPFS of 5.3 (4.5-7.3) months and OS of 12.8 (11.1-17.3) months in the CGDB; median OS was 15.6 (12.5-18.6) months in the EHR. Patients with PD-L1 ≥ 50% treated with pembrolizumab monotherapy had median rwPFS of 4.6 (3.0-15.6) months and OS of 20.4 (10.3-38.5) months in the CGDB; median OS was 22.1 (18.7-30.7) in the EHR. CONCLUSIONS: These data provide a real-world benchmark of outcomes for patients with KRAS G12C-mutant NSCLC receiving the current standard of care and indicate an unmet need for more effective first-line therapies.

KRAS G12C↗

PubMed2026

Genetic mutations in metastatic adenocarcinoma of unknown primary.

INTRODUCTION: Although several genomic alterations have been reported in adenocarcinoma of unknown primary (ACUP), molecularly targeted therapies are not yet clinically established, and comprehensive genomic profiling (CGP) is rarely used in daily practice. AIM: We aimed to clarify the molecular landscape and prognostic impact of key mutations in recurrent or metastatic ACUP. MATERIALS AND METHODS: Data from 480 consecutive ACUP patients registered in Japan's National Cancer Center (C-CAT) between June 2019 and August 2025 were analyzed. Somatic mutations were identified using the FoundationOne CDx platform. Overall survival (OS) was assessed by Kaplan-Meier analysis, log-rank tests, and multivariate Cox proportional hazards modeling. RESULTS: The most frequent alterations were TP53 (59.4%), KRAS (31.5%), CDKN2A (26.3%), KMT2D (22.3%), LTK (17.9%), NOTCH3 (16.9%), STK11 (16.3%), CDKN2B (15.8%), ERBB2 (15.4%), and GNAS (15.2%). Patients harbored an average of 17.3 9.9 mutations. Mutations in GNAS (p = 0.046) and PIK3CA (p = 0.025) were associated with better OS, whereas ARID1A (p = 0.049) and NOTCH1 (p = 0.038) predicted worse OS. In Cox analysis, hazard ratios (HR [95% CI]) were 0.57 (0.36-0.92, p = 0.020) for GNAS, 0.57 (0.33-0.96, p = 0.033) for PIK3CA, 1.98 (1.27-3.09, p = 0.0024) for ARID1A, and 1.84 (1.17-2.91, p = 0.0090) for NOTCH1. CONCLUSIONS: GNAS and PIK3CA mutations were linked to favorable outcomes, while ARID1A and NOTCH1 alterations indicated poor prognosis in ACUP. These results highlight the prognostic significance of specific genomic alterations and support integrating CGP into the clinical management of ACUP.

Humans↗

PubMed2024

Genome-wide CRISPR screens in spheroid culture reveal that the tumor suppressor LKB1 inhibits growth via the PIKFYVE lipid kinase.

The tumor suppressor LKB1 is a serine/threonine protein kinase that is frequently mutated in human lung adenocarcinoma (LUAD). LKB1 regulates a complex signaling network that is known to control cell polarity and metabolism; however, the pathways that mediate the tumor-suppressive activity of LKB1 are incompletely defined. To identify mechanisms of LKB1-mediated growth suppression, we developed a spheroid-based cell culture assay to study LKB1-dependent growth. We then performed genome-wide CRISPR screens in spheroidal culture and found that LKB1 suppresses growth, in part, by activating the PIKFYVE lipid kinase. Finally, we used chemical inhibitors and a pH-sensitive reporter to determine that LKB1 impairs growth by promoting the internalization of wild-type EGFR in a PIKFYVE-dependent manner.

Humans↗