This consensus by the CSCO Pancreatic Cancer Expert Committee establishes evidence-based guidelines for molecular testing in pancreatic ductal adenocarcinoma. It details recommendations for biomarkers (e.g., KRAS, BRCA, MSI), liquid biopsy, and precision imaging to direct targeted therapies and immunotherapy, aiming to standardize diagnosis and optimize individualized patient care. Pancreatic ductal adenocarcinoma (PDAC) is the most common pathological type of primary pancreatic malignancy, accounting for ~95% of cases and generally referred to as pancreatic cancer [1]. Its prognosis is extremely poor and its incidence continues to rise [2]. According to the most recent global cancer statistics, the incidence of pancreatic cancer ranks 12th among all cancers, and its mortality ranks 6th, making it one of the deadliest malignancies worldwide [3]. Approximately 57% of patients have metastatic disease at diagnosis and require systemic therapy, for which chemotherapy remains the standard first-line option [1]. However, the overall response rate to currently available systemic regimens is low, and the 5-year survival rate for patients with metastatic disease remains below 5% [3]. Although most pancreatic cancers harbor canonical driver mutations, they exhibit marked heterogeneity at the molecular level. Whole-genome sequencing (WGS) and integrative genomic analyses have identified molecular subtypes of PDAC with potential clinical relevance [4-9]. With the increasing implementation of precision oncology, the Chinese Society of Clinical Oncology (CSCO) Guidelines for the Diagnosis and Treatment of Pancreatic Cancer give a level 1 recommendation to perform genetic and other molecular testing on tissue or cytologic specimens as part of the pathological diagnostic work-up, in order to guide individualized treatment, including targeted therapy and immunotherapy [10]. To further promote the use of genetic and molecular testing in the precision treatment of pancreatic cancer, the CSCO Pancreatic Cancer Expert Committee convened a multidisciplinary panel to develop the present Chinese Expert Consensus on Precision Testing and Molecular Diagnosis of Pancreatic Cancer (2025), aiming to provide clinicians with an authoritative reference for precision diagnostics and treatment decision-making.
Reflex testing (RT) - pathologist-initiated molecular testing performed at non-small cell lung cancer (NSCLC) diagnosis - enables rapid identification of actionable genomic alterations for targeted therapy (TT) selection. Despite national and international guideline recommendations, approximately 15% of patients with advanced NSCLC in Germany remain untested for driver mutations. The portion of untested patients in early stages is likely to be even higher. This study simulated the clinical and economic impact of introducing RT for untested NSCLC patients under different implementation scenarios, using a decision-tree model from the German statutory health insurance (SHI) perspective. A decision-tree model simulated four RT cases (C): (C1) no molecular testing, (C2) testing per German S3 guideline recommendations, (C3) testing according to current TT approvals, and (C4) comprehensive panel testing (standard in Austria). PD-L1 expression was tested in all cases. The untested NSCLC population was projected for 2025 based on SHI demographics. Model inputs comprised RT sensitivity, mutation and stage distribution, drug acquisition costs (Lauer-Taxe, April 2025), and median overall/progression-free survival (mOS/mPFS) per therapeutic strategy. A scenario analysis was conducted assuming NGS test costs of €3,000 per panel to assess their potential influence on cost-effectiveness versus no testing. All RT cases (C2-C4) substantially increased actionable mutation detection, enabling earlier TT initiation and lower mean treatment costs versus no molecular testing. C2-C4 were clinically dominant, driven by increased mOS by 5.48-5.47 months and mPFS by 4.89-5.42 months. Model yielded annual cost savings versus no testing of €740 (C2) and €535 (C3/C4) per patient (annual cost savings of €1,175 - €1,621 per life-year gained). When €3,000 next-generation sequencing (NGS) panel costs were included, annual costs per patient increased modestly (C2: €2,260; C3/C4: €2,465 versus no testing), at annual incremental costs of €4,946 - €5,409 per life-year gained. Reflex testing across implementation cases, by enabling earlier identification of actionable biomarkers and receipt of matched targeted therapy, improves clinical outcomes and is cost-effective for untested NSCLC patients from the German SHI perspective. Structured initiatives, such as national Network for Genomic Medicine (nNGM), could further expand equitable access to precision oncology in Germany.
The present study comprehensively dissects the molecular landscape of elderly mantle cell lymphoma (MCL) patients enrolled in the phase II V-RBAC trial of the Fondazione Italiana Linfomi. Of the 140 patients enrolled in the trial, 132 had available gDNA extracted from lymph node biopsies or bone marrow aspirates and were included in the analysis. A CAPP-Seq assay targeting 146 genes relevant to MCL pathogenesis was employed to identify gene mutations and copy number variations. ATM was the most frequently mutated gene, detected in 55 patients (41.7%), followed by TP53 and KMT2D in 31 patients (23.5%). ATM deletion was observed in 32 patients (24%), while CDKN2A loss in 29 (22%). Beyond TP53 mutations, three other molecular lesions, including CDKN2A loss, CD36 mutations and single-hit ATM abnormalities (either mutation or deletion) were independently associated with progression-free survival after adjustment for high-risk trial-defining features, namely Ki-67 >30% and blastoid variant. Notably, patients harboring single-hit ATM alterations without any additional risk factors achieved durable long-term remission, while CD36 mutations were associated with adverse survival. Both findings represent previously unrecognized aberrations that in this cohort independently and inversely associated with survival. The four variables were integrated into a 4-factor molecular prognostic model internally validated using a bootstrapping approach, which identified four distinct patient subgroups with significantly different outcomes. These findings support the importance of i) molecular profiling in MCL, ii) risk-adapted trials like V-RBAC, and iii) the integration of other biological markers with TP53 mutations for a more precise risk assessment in MCL. (NCT03567876).
Hematological malignancies are highly heterogeneous diseases characterized by dysregulated signaling pathways and limited durable therapeutic responses. Calcium homeostasis has emerged as a critical regulator of cancer cell fate, yet the role of the sodium/calcium exchanger 1 (NCX1/SLC8A1) in leukemogenesis remains poorly defined. In this study, we comprehensively investigated the biological significance and therapeutic potential of NCX1 across major hematological malignancies by integrating transcriptomic analyses, protein-protein interaction networks, experimental validation, and in silico drug repurposing strategies. NCX1 was highly expressed in HL-60, K-562, and Jurkat cells compared to HaCaT controls. Network analyses revealed that NCX1 interacts with key regulators of calcium signaling, immune response, and signal transduction. In AML and CML patient datasets, a strong positive correlation was observed between NCX1 expression and immune-related pathways, while a negative correlation was observed with translation-related processes. Molecular docking analyses demonstrated that several clinically approved compounds, particularly imatinib and nilotinib, interact with NCX1. Molecular dynamics simulation was performed to evaluate the binding stability and safety of imatinib. Remarkably, the comprehensive analysis showed that imatinib exhibited a stable molecular dynamics profile. All these findings have demonstrated NCX1 as a biologically informative marker of myeloid differentiation and a promising therapeutic weak point within calcium signaling networks in hematological malignancies, providing a rationale for future functional and single-cell validation studies.
Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide, driven by complex genetic, epigenetic, and environmental factors. Despite advances in conventional treatments such as surgery, chemotherapy, and radiotherapy, therapeutic resistance and disease recurrence continue to limit long-term outcomes. This review provides a comprehensive overview of emerging and targeted therapeutic strategies in CRC, with emphasis on their molecular basis and clinical relevance. The key pathways involved in CRC pathogenesis, including the adenoma-carcinoma sequence, microsatellite instability, and CpG island methylator phenotype, are discussed to highlight their roles in disease progression and therapeutic targeting. Recent advances in targeted therapies, particularly those directed against vascular endothelial growth factor and epidermal growth factor receptor, along with the expanding role of immunotherapy, are critically examined. In addition, novel approaches such as gene- and RNA-based therapies, microbiome modulation, nanotechnology-driven drug delivery systems, and precision medicine strategies based on multi-omic profiling are explored. Despite these developments, the challenges including tumor heterogeneity, therapeutic resistance, and limitations in drug delivery and biomarker identification remain significant. Future perspectives emphasize the integration of molecular profiling and innovative therapeutic platforms to enable more personalized and effective treatment strategies. Collectively, these advances highlight a shift toward precision oncology for improved management of colorectal cancer.
We report for the first time the molecular landscape and outcome associations from the prospective CLIMEDIN trial in Greece. Two hundred patients with newly diagnosed advanced NSCLC (March 2022-October 2023) were enrolled and randomized to standard-of-care education versus additional automated, adverse-event-targeted digital interventions. Within this study baseline testing (EGFR, ALK, PD-L1) was performed in all; 165 tumors underwent comprehensive NGS (Oncomine Comprehensive Assay v3). Primary endpoint was improvement in AEs/QoL; secondary endpoints included ORR, PFS and OS. Associations between genomic alterations and outcomes were explored. Median age was 68 years; 75% male; 52% current smokers; adenocarcinoma 68.5%. Most received chemo-immunotherapy (66%). At data cut-off (December 2025; reverse-Kaplan-Meier median follow-up 36.3 months), median PFS was 9.6 months and median OS was 15.2 months. Across 200 tumors, 495 pathogenic variants (PVs) were identified in 83 genes. Exploratory outcome analyses showed longer OS in EGFR-mutant disease (preserved under parsimonious multivariable adjustment) and a formal KRAS × smoking interaction for OS (interaction P = 0.011). In this cohort, the molecular profile mirrors other Caucasian series, with clinically relevant enrichment patterns for EGFR and KRAS. ECOG performance status and first line treatment were the dominant prognostic factors in this cohort. A novel KRAS and smoking interaction for overall survival warrants prospective validation.
Non-small-cell lung cancer (NSCLC) has seen a paradigm shift over the past quarter century driven by systematic molecular characterization, the advent of targeted therapies, the implementation of low-dose CT screening, and the integration of immunotherapy across the disease continuum. Genomic profiling has defined oncogene-addicted subsets for which targeted agents now improve survival in both metastatic and resectable disease, while immune checkpoint inhibitors have displaced chemotherapy as first-line treatment for many patients without actionable drivers and have been incorporated into perioperative and consolidation strategies. Concurrently, adjuvant and consolidation tyrosine kinase inhibition has extended precision oncology into early-stage EGFR- and ALK-driven NSCLC. Here, we review pivotal therapeutic advances across metastatic, locally advanced, and early-stage disease; identify the need for more discriminating markers to refine treatment intensity and sequencing; and outline emerging approaches, including rational upfront combinations and the use of circulating tumor DNA to enable real-time, adaptive modulation of therapy in NSCLC.
CtBP1-S/BARS (C-terminal binding protein 1-S/Brefeldin A ADP-Ribosylation Substrate) is a moonlighting protein with key roles in membrane trafficking and gene regulation. We show that CtBP1-S/BARS couples enzymatic lipid remodeling [lysophosphatidic acid (LPA)-to-phosphatidic acid (PA) conversion] with membrane deformation to drive fission and that this activity is directly controlled by metabolic ligands. CtBP1-S/BARS exists as a monomer or dimer. The monomeric, acyl-CoA-bound form drives membrane fission by coupling acyltransferase-dependent LPA-to-PA conversion with amphipathic helix insertion into PA-enriched membranes. Under metabolic stress, reduced nicotinamide adenine dinucleotide (NADH) binding triggers dimerization and structural rearrangements that disable fission, enabling the binding of transcription factors regulating apoptosis and energy metabolism. This NADH/acyl-CoA competition likely coordinates trafficking shutdown with gene expression programs through a single conformational change. In intact cells, increased NADH promotes nuclear accumulation of dimeric/tetrameric CtBP1-S/BARS, whereas elevated acyl-CoA favors the cytosolic, membrane-associated monomer, indicating that cofactor availability determines protein function under physiological and stress conditions. This work reveals the structural basis for integrating membrane transport with transcriptional control, demonstrating how evolution embeds distinct cellular functions into a unified molecular pathway.
Immunotherapy offers promising prospects for esophageal squamous cell carcinoma (ESCC), a highly fatal malignant tumor. Given the association between manganese metabolism and tumor immunity, this study explored the prognostic value and role of manganese-metabolism-related genes (MMRGs) in the ESCC immune microenvironment to uncover their clinical potential. Transcriptomic and clinical data of ESCC were retrieved from TCGA and the GEO as training and validation cohorts, respectively. Patients were clustered and subtyped based on MMRGs, with survival compared. A prognostic risk model was constructed using differential analysis, PPI network, and Cox regression; its relationship with immune characteristics, immunotherapy response, and drug sensitivity was evaluated. SLC40A1 was knocked down in vitro, and its effects on cellular function and drug sensitivity were assessed via qRT-PCR, Western blot, colony formation, Transwell, and CCK-8 assays. ESCC patients were stratified into two MMRG-defined subtypes. Cluster 2 showed significantly worse overall survival (OS) than Cluster 1. An 8-gene prognostic model was established and patients were assigned to RiskScorehigh and RiskScorelow groups. The high-risk group, characterized by worse OS, displayed an immunosuppressive microenvironment with abundant M2 macrophages and high immune-checkpoint expression (PDCD1, CTLA4, TIGIT), along with a lower TIDE score, suggesting potentially greater benefit from immune-checkpoint blockade. The RiskScorehigh group was more sensitive to Gemcitabine and Oxaliplatin, whereas the RiskScorelow group responded better to BI-2536 and NU7441. Cellular functional assays confirmed high expression of SLC40A1 in ESCC cells. SLC40A1 knockdown significantly inhibited cell proliferation, migration, and invasion. Additionally, cells exhibited greater sensitivity to Gemcitabine than to BI-2536. MMRG-based subtyping and the reliable prognostic risk score model provide novel insights for predicting prognosis and developing personalized therapy in ESCC.
Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options. Comprehensive molecular profiling with next-generation sequencing (NGS) may enable personalized therapies, but its feasibility using EUS-guided fine-needle biopsy (EUS-guided FNB) and broad panels in routine practice remains unclear. This study aimed to assess the feasibility of NGS using residual diagnostic tissue from EUS-guided FNB in PDAC, without dedicated sampling. We performed a retrospective single-center study of patients with PDAC who underwent EUS-guided FNB, analyzing residual paraffin-embedded tissue blocks for NGS using a 63-gene panel. Samples required a minimum tumor cellularity of 20% and tumor area ≥10 mm2. Baseline, procedural, and genomic data were compared between NGS-feasible and NGS-unfeasible groups. The primary endpoint was technical success. Thirty-five patients were included. NGS was successful in 74.3% of cases (26/35) using residual diagnostic material without additional biopsy passes. No significant baseline or procedural differences were observed between groups, except for metastatic disease, which was more frequent in the NGS-unfeasible group (55.6% vs. 11.5%, P = 0.029). KRAS mutations were identified in 73.1% of sequenced cases, predominantly at codon 12. EUS-guided FNB samples can support NGS from residual diagnostic tissue with high feasibility, avoiding dedicated sampling. This pragmatic approach may streamline molecular profiling and expand access to precision oncology in PDAC.
Immune checkpoint inhibitors (ICIs) combined with vascular endothelial growth factor tyrosine kinase inhibitors (VEGF-TKIs) have transformed the treatment landscape of advanced clear cell renal cell carcinoma (ccRCC). Current guidelines favour ICI plus VEGF-TKI (IO+TKI) combinations for favourable-risk disease (International Metastatic RCC Database Consortium [IMDC] score 0) based on improved objective response rates and progression-free survival. However, no IO+TKI combination has demonstrated a statistically significant overall survival (OS) benefit in this subgroup. A pooled analysis of four pivotal phase III trials (n = 839 favourable-risk patients) revealed no OS advantage for IO+TKI versus sunitinib monotherapy (hazard ratio [HR] 1.24; 95% CI 0.86-1.78) despite higher toxicity rates (71-82% Grade ≥ 3 adverse events vs. 63-72% with sunitinib) and substantially greater cost. The IMDC favourable-risk category represents approximately 20% of metastatic ccRCC cases and is often characterised by indolent disease biology. Emerging molecular classifications reveal distinct transcriptomic subgroups, including an angiogenic subtype (ccA/CC-e.2/clusters 1-2) enriched in favourable-risk patients, characterised by high hypoxia-inducible factor (HIF) pathway gene expression, frequent PBRM1 mutations, robust VEGF-TKI responsiveness, and comparatively lower benefit from immunotherapy. Current clinical risk stratification fails to capture this molecular heterogeneity, limiting optimal treatment selection. VEGF-TKI monotherapy (median OS 47.6-79.4 months) and active surveillance remain valid, evidence-based alternatives in carefully selected favourable-risk patients, particularly those with asymptomatic, metachronous, or otherwise indolent disease. Uncritical universal use of IO+TKI in this population may therefore represent overtreatment. The development and validation of predictive biomarkers, refinement of molecular risk stratification, and exploration of novel agents with more favourable toxicity profiles (e.g., HIF-2α inhibitors) are urgently required to personalise therapy and identify candidates for rational treatment de-escalation.
Immune checkpoint inhibitors (ICIs) are superior to chemotherapy in metastatic colorectal cancer (mCRC) with MSI-H/dMMR. However, whether oncogenic driver alterations contribute to clinically meaningful heterogeneity in outcomes within this immunotherapy-sensitive population remains unclear. We conducted a systematic review and meta-analysis to evaluate the association between RAS and BRAF mutational status and outcomes in ICI-treated MSI-H/dMMR mCRC. A systematic literature search identified studies reporting outcomes of ICI therapy according to RAS and/or BRAF status in MSI-H/dMMR mCRC. Study-level pooled analyses were conducted using random-effects models to estimate odds ratios (ORs) for objective response rate (ORR) and hazard ratios (HRs) for progression-free survival (PFS) and overall survival (OS). Nine studies were included, comprising a total of 13 treatment cohorts and 2564 patients were analysed. ORR did not significantly differ across molecular subgroups. Compared with wild-type tumours, RAS-mutated disease was associated with modestly longer PFS (HR 0.81, 95% CI 0.66-0.99), whereas BRAF-mutated tumours showed shorter PFS (HR 1.37, 95% CI 1.11-1.69). Overall survival was significantly worse in BRAF-mutated disease (HR 1.74, 95% CI 1.17-2.59), while no significant OS differences were observed for RAS-mutated tumours. Exploratory analyses suggested that dual checkpoint blockade may increase response rates particularly in BRAF-mutated and molecularly wild-type subgroups. Within MSI-H/dMMR mCRC treated with ICIs, molecular subgroups show distinct survival patterns despite similar response rates. BRAF-mutated tumours retain an adverse prognostic impact, whereas RAS-mutated disease may exhibit more durable disease control. These findings support biological stratification within MSI-H/dMMR mCRC and provide a rationale for prospective biomarker-stratified studies of tailored immunotherapy strategies.
Background: Guanylate kinase 1 (GUK1) is crucial for nucleotide metabolism, yet its impact on breast cancer (BC) progression remains poorly defined. The objective of the present study is to investigate GUK1 as a prognostic biomarker and therapeutic target. Methods: We employed a multi-omics approach integrating The Cancer Genome Atlas (TCGA) data, machine learning algorithm, High-Definition spatial transcriptomics (Visium HD), single-cell profiling, molecular docking and experimental validation including in vitro knockdown models and Surface Plasmon Resonance (SPR). Results: LASSO regression identified GUK1 as a key metabolic driver. High expression correlated significantly with poor survival and was most pronounced in Human Epidermal Growth Factor Receptor 2 (HER2)-positive and triple-negative subtypes. Spatial transcriptomics revealed GUK1 strongly colocalizes with expanding cancer cell nests, intensifying with disease stage. Single-cell analysis linked GUK1 overexpression to an immunosuppressive microenvironment enriched in exhausted T-cells. Clinically and molecularly, TP53 mutations are highly associated with HSF1 promoter hypomethylation and subsequent HSF1-mediated GUK1 upregulation. We experimentally confirmed this axis, showing that HSF1 or GUK1 knockdown significantly impaired cell migration and suppressed mTOR signaling. Furthermore, while high GUK1 levels predicted resistance to CDK4/6 inhibitors, they enhanced sensitivity to the PI3K/mTOR inhibitor Apitolisib. This therapeutic vulnerability was validated by SPR, which confirmed high-affinity binding between GUK1 and Apitolisib, and by cell viability assays where GUK1 depletion induced drug resistance. Conclusion: GUK1 serves as a robust prognostic biomarker regulated by the TP53-HSF1 axis. Its distinct spatial patterns, immune-suppressive associations, and experimentally validated role in modulating PI3K/mTOR inhibitor sensitivity position GUK1 as a promising target for precision oncology in invasive BC.
Objectives: Oral squamous cell carcinoma (OSCC) is a common and deadly cancer affecting the oral cavity. This study aims to explore the regulatory role and molecular mechanism of miR-548ae-3p in OSCC proliferation, invasion, and lipid metabolism, as well as the therapeutic potential of isoliquiritigenin (ISL) targeting OSCC lipid metabolism. Methods: Expression levels of miR-548ae-3p were measured in OSCC cell lines and normal oral keratinocytes using real-time quantitative polymerase chain reaction. Functional assays, such as cell counting Kit-8 proliferation and Transwell invasion assays, evaluated the effects of miR-548ae-3p overexpression in CAL-27 and SCC-25 cells. Bioinformatic prediction and dual-luciferase reporter assays investigated interactions among miR-548ae-3p, hsa_circRNA_0001794 (circPOLB), and cellular myelocytomatosis oncogene (c-MYC). Lipid metabolism was assessed using lipid droplet staining, fatty acid oxidation assays, total fatty acids and palmitic acid quantification, and fatty acid-binding protein 5 (FABP5) expression analysis. The inhibitory effects of ISL on OSCC lipid metabolism and invasiveness were also examined. Results: MiR-548ae-3p was downregulated in OSCC cells compared to normal keratinocytes (n = 3, p < 0.001). miR-548ae-3p overexpression inhibited the proliferation and invasion of CAL-27 and SCC-25 cells (n = 3, p < 0.001). CircPOLB functions as a molecular sponge for miR-548ae-3p, which in turn targets c-MYC, a key oncogene. MiR-548ae-3p overexpression reduced lipid droplet accumulation, fatty acid oxidation, total fatty acid content, and intracellular palmitic acid levels, accompanied by downregulation of FABP5 (n = 3, p < 0.001). Furthermore, ISL treatment decreased FABP5 expression, fatty acid metabolism, and invasive capacity of OSCC cells (n = 3, p < 0.001), supporting its potential as a therapeutic agent. Conclusions: MiR-548ae-3p displays tumor-suppressive activity in OSCC, restraining proliferation, invasion, and fatty-acid metabolism through engagement of the circPOLB/c-MYC axis and is associated with reduced FABP5 expression. Targeting lipid metabolism using agents like ISL could be a promising approach for treating OSCC.
Peripheral T-cell lymphoma (PTCL) is a heterogeneous and highly aggressive subtype of non-Hodgkin lymphoma. Approximately 30% of patients develop relapsed or refractory PTCL (R/R PTCL) due to disease recurrence or failure to achieve complete remission after first-line therapy. Despite therapeutic advances, the molecular and cellular mechanisms underlying treatment resistance in R/R PTCL remain unclear. Single-cell RNA sequencing and single-cell T-cell receptor sequencing were performed on seven tumor samples from six patients with R/R PTCL. These approaches were used to systematically characterize the transcriptional profiles of malignant T-cell clones and reactive T lymphocytes, define the transcriptomic landscape of R/R PTCL, and identify potential epigenetic biomarkers associated with drug response. We observed significant upregulation of genes associated with cell proliferation, oncogenic signaling, and immune modulation in R/R PTCL. Within the tumor microenvironment, specific protumorigenic ligand-receptor interactions were identified, including CXCL13-CXCR5, CCL5-CCR5, and CD74-MIF interactions, which may facilitate immune evasion by malignant T cells. Longitudinal analysis of a patient who progressed following dual epigenetic therapy revealed marked downregulation of immune response-related genes, including HLA-DRA/DPA1/DRB5, CD74, C1QC, and LYZ, as well as functional reprogramming of tumor-associated macrophages. Enhanced LGALS9-HAVCR2 and CSF1-CSF1R interactions were also observed following combination treatment with chidamide and azacitidine. This study delineates the transcriptional heterogeneity of malignant T-cell clones in R/R PTCL and suggests that this heterogeneity may contribute to resistance to epigenetic therapies. These findings provide novel insights into the molecular mechanisms underlying treatment resistance and highlight potential avenues for therapeutic intervention in R/R PTCL.
Triple-negative breast cancer (TNBC) with axillary lymph node metastasis (ALNM) represents a high-risk population with substantially worse prognosis compared to other breast cancer subtypes. Despite the critical clinical importance of accurate prognostic assessment in this population, no validated risk prediction model specifically tailored for TNBC patients with ALNM currently exists. Machine learning approaches offer the potential to integrate multiple clinical and pathological factors for improved risk stratification, yet their application in this specific context remains unexplored. This retrospective study analyzed 19,289 TNBC patients with ALNM from the Surveillance, Epidemiology, and End Results (SEER) database (2015-2020). Patients were randomly allocated to training (n=13,502, 70%) and validation (n=5,787, 30%) cohorts. Independent prognostic factors were identified through univariable and multivariable Cox regression analysis. Five machine learning-based survival models were developed and compared: Cox Proportional Hazards (CoxPH), Random Survival Forest (RSF), Extremely Randomized Survival Trees (ERST), Gradient Boosting Survival Analysis (GBSA), and Survival Tree (ST). Model performance was evaluated using concordance index (C-index), time-dependent area under the curve (AUC), Brier scores, calibration curves, and decision curve analysis. SHapley Additive exPlanations (SHAP) analysis was employed to enhance model interpretability and identify key prognostic drivers. Multivariable Cox regression identified 13 independent prognostic factors encompassing demographic characteristics (age, race, marital status, household income), tumor pathological features (histology type, T stage, N stage, M stage, tumor grade, tumor size), and treatment modalities (surgery, radiotherapy, chemotherapy). The four ensemble/regression models (ERST, RSF, GBSA, CoxPH) demonstrated comparable C-indices (0.7494, 0.7489, 0.7483, and 0.7455, respectively) and substantially outperformed ST (0.6959); ERST was selected for downstream SHAP interpretation given its marginally highest C-index. Time-dependent AUC values for 1-, 3-, and 5-year survival predictions were 0.889, 0.773, and 0.740, respectively, with corresponding Brier scores of 0.014, 0.067, and 0.151, indicating excellent discriminatory ability and calibration. Decision curve analysis confirmed favorable clinical utility across a wide range of threshold probabilities. SHAP analysis revealed tumor grade, N stage, and radiotherapy as the three most influential prognostic factors, with high tumor grade, advanced nodal stage, and absence of radiotherapy consistently associated with increased mortality risk. We developed and internally validated the first machine learning-based prognostic model specifically for TNBC patients with ALNM, integrating 13 clinicopathological variables. The ERST model demonstrated robust discriminatory performance, excellent calibration, and favorable clinical utility. SHAP-based interpretability analysis provided transparent insights into key prognostic drivers, facilitating individualized risk assessment and clinical translation. This tool addresses a critical gap in precision oncology for this high-risk population and has the potential to inform treatment decisions, optimize surveillance strategies, and improve prognostic counseling. Future prospective validation in independent cohorts and integration of molecular biomarkers represent important next steps toward clinical implementation.
Testing for predictive biomarkers in lung cancer has evolved to integrate immunohistochemistry, tissue-based next-generation sequencing (NGS), and liquid biopsy. Tissue-based NGS remains the foundation for comprehensive genomic profiling, enabling detection of actionable mutations and guiding personalized therapies. RNA-based assays complement DNA testing by improving fusion detection. Liquid biopsy using circulating tumor DNA (ctDNA) offers a minimally invasive alternative for genotyping, monitoring treatment response, and assessing minimal residual disease, though sensitivity challenges persist in early-stage disease. Immunohistochemistry for PD-L1 and emerging antibody-drug conjugate targets further expands therapeutic options. Workflow optimization, including molecular tumor boards, reflex testing, and rapid assays, is critical to reduce turnaround times. Lastly, advances in digital pathology and AI promise novel biomarker discovery and integration into clinical practice, ensuring accurate interpretation and personalized treatment strategies in the rapidly evolving field of lung cancer personalized oncology.
Lung cancer in individuals who have never smoked (LCINS) represents a clinically and biologically distinct subset of non-small cell lung cancer, driven predominantly by oncogenic alterations rather than tobacco-related mutagenesis. This review aims to summarize current and emerging targeted and immune-based therapeutic strategies in LCINS individuals. These patients present a molecular profile that differs substantially from tobacco-associated disease and has direct consequences for treatment selection. Evidence published over the past five years has clarified how these molecular features shape treatment response and resistance in this setting. Particular attention is given to tumors with alterations in epidermal growth factor receptor, anaplastic lymphoma kinase, c-ros oncogene 1, rearranged during transfection, Mesenchymal-Epithelial Transition (MET) exon 14 skipping mutation, human epidermal growth factor receptor 2, valine-to-glutamic acid substitution at codon 600 of the BRAF gene (BRAF V600E), and neurotrophic tyrosine receptor kinase, which together comprise the dominant driver landscape in never-smoker lung cancer. Although third-generation tyrosine kinase inhibitors have markedly improved response rates in several of these subgroups, long-term disease control is frequently compromised by acquired resistance, and heterogeneous drug exposure, particularly in the central nervous system. By contrast, immune checkpoint inhibitors have yielded limited benefit, in keeping with the low mutational burden and generally low baseline immune activation observed in most LCINS tumors. As a result, alternative approaches such as antibody-drug conjugates, bispecific antibodies, and adoptive cellular therapies are being evaluated to address gaps left by existing treatments.
Oncogenic gene fusions define a clinically important subset of non-small cell lung carcinoma (NSCLC) for which targeted therapies have transformed outcomes. Over the past 15 years, successive generations of tyrosine kinase inhibitors (and more recently, monoclonal antibodies) have demonstrated substantial improvements in response rates, progression-free survival, and central nervous system control across multiple fusion-defined populations. This review consolidates current evidence for FDA-approved therapies targeting ALK, ROS1, RET, NTRK, and NRG1 fusions in lung cancer, highlighting mechanisms of action, pivotal clinical trials, resistance patterns, and toxicity profiles. We also discuss advances in molecular diagnostics (including the growing role of RNA-based sequencing) and emerging strategies in the adjuvant and perioperative settings. Finally, we outline ongoing clinical trials and future directions aimed at overcoming resistance and expanding precision oncology approaches for patients with rare fusion-driven lung cancers.
Thyroid Hormone Receptor Interactor 12 (TRIP12) is an E3 ubiquitin ligase capable of mediating ubiquitin-dependent proteolysis of specific protein substrates. This function regulates key biological processes, including cell cycle progression, cell differentiation, chromatin remodelling and DNA damage repair. Consequently, loss-of-function mutations in TRIP12 have been associated with a broad spectrum of human diseases, including cancer and neurological and neurodevelopmental disorders. Previous studies have demonstrated that pathological variants of TRIP12 cause Clark-Baraitser syndrome, characterized by craniofacial dysmorphism, motor delay and intellectual disability, with or without autism spectrum disorder. Despite the well-characterized clinical manifestations, the underlying molecular pathways affected by TRIP12 disruption and their implication in the pathophysiology of autism spectrum disorder and intellectual disability remain unclear. Using a knock-out zebrafish model, we have elucidated the essential role of trip12 in diverse metabolic and biological pathways, particularly those related to neural and neurodevelopmental processes, shedding light on potential mechanisms underlying the pathogenesis. Heterozygous and recessive homozygous zebrafish mutants exhibit clinical features analogous to those observed in human patients, including craniofacial anomalies and decreased locomotor activity. Furthermore, this study provides substantial evidence for the vital role of trip12 in the early stages of development, as homozygous individuals exhibited early mortality by Day 23 post-fertilization, while a substantial mortality rate of 90% was observed by Day 35 in 'heterozygous' mutants. The present study demonstrates the profound impact that trip12 mutations have on embryogenesis, and transcriptomic analysis offers an in-depth knowledge of the molecular basis of the disease. These findings offer valuable insights into potential therapeutic targets for improving outcomes in individuals with TRIP12-associated disorders.