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PubMed2026

Topologically distinct intratumoral heterogeneity scores for predicting high-risk pathological grades in invasive lung adenocarcinoma: A multicenter study across four institutions.

High-risk subtypes of invasive lung adenocarcinoma (IAC), particularly micropapillary- or solid-predominant patterns, are closely associated with poor prognosis. This multicenter retrospective study developed and validated a predictive model for the preoperative identification of these high-risk subtypes using topologically distinct intratumoral heterogeneity (ITH) scores derived from CT images. The study included 1,051 patients with IAC. Two complementary ITH scores were developed: a two-dimensional ITH score, which integrated local radiomics features with global pixel distribution patterns on the largest cross-sectional CT slice, and a three-dimensional ITH score, which extended this quantification across the entire tumor volume. Clinicoradiological features and ITH scores were incorporated as model inputs to construct six base machine learning classifiers and a final stacking ensemble classifier. Model interpretability and robustness were evaluated using SHapley Additive exPlanations (SHAP)-based ablation analyses. An independent dataset from The Cancer Imaging Archive (TCIA) was used for external validation to investigate associations between ITH scores and pathological characteristics, genomic features, recurrence-free survival, and overall survival. The stacking ensemble classifier achieved the best predictive performance, with an area under the receiver operating characteristic curve of 0.875, outperforming models based solely on radiomics features (0.834) or clinicoradiological features (0.792). SHAP analysis identified the 3D ITH score as the most influential contributor to model output, and TCIA validation showed that higher 3D ITH scores were associated with more aggressive tumor biology and poorer survival outcomes. The topologically distinct 3D ITH score may provide a clinically meaningful imaging biomarker for preoperative risk stratification in IAC.

Journal Article↗
PubMed2026

CD4+CD8+ double-positive T cells are associated with severity of tuberculosis.

BACKGROUND: Tuberculosis (TB) remains a global public health burden, and how immune cell subsets regulate host anti-TB immunity and disease progression remains incompletely understood. While previous studies have focused on single-positive (SP) T cells (CD4+ or CD8+) in TB pathogenesis, the association between CD4+CD8+ double-positive (DP) T cells and TB susceptibility, severity, and treatment outcomes have not been fully elucidated. This study aimed to investigate the relationship between DP T cells and other immune cell subsets with TB, and to explore the potential diagnostic and prognostic value of DP T cells in active TB. METHODS: A Genome-Wide Association Study (GWAS) was conducted to analyze 731 immune cell traits and a dataset encompassing 895 patients with TB. Subsequently, a cohort including 647 patients with active TB and 632 healthy controls was used to verify the findings of Mendelian randomization (MR). The correlation between the percentage of DP T cells in lymphocytes and TB severity, treatment efficacy, and Mycobacterium tuberculosis (Mtb)-specific IFN-&#x3b3; production was evaluated. Finally, a random forest model incorporating the percentage of DP T cells in leukocytes and other peripheral blood parameters was constructed to distinguish severe from mild active TB. RESULTS: MR analysis suggested potential causal links between the percentage of DP T cells among peripheral leukocytes and TB status. Clinical sample validation showed that the percentage of peripheral DP T cell among leukocytes was significantly lower in patients with active TB than in healthy controls (P < 0.001), and was inversely correlated with disease severity. Additionally, the percentage of DP T cells in leukocytes was positively correlated with Mtb-specific antigen-stimulated IFN-&#x3b3; production. Flow cytometric analysis demonstrated that DP T cells had a significantly higher frequency of IFN-&#x3b3;-expressing cells compared to CD8+ SP T cells (P < 0.001). The constructed random forest model effectively distinguished severe from mild TB, with good diagnostic performance (AUC&#xa0;=&#xa0;0.985). CONCLUSIONS: Our findings indicate that DP T cells are closely associated with TB severity, and are positively associated with Mtb-specific IFN-&#x3b3; response. The percentage of peripheral DP T cells in leukocytes could serve as a potential non-invasive biomarker for TB severity stratification.

Humans↗
PubMed2026

C-Reactive Protein-Based Composite Indices for Predicting Tumor Overgrowth Restenosis After Partially Covered Duodenal Stenting in Gastric Cancer: A Cohort Study.

BACKGROUND/OBJECTIVES: Partially covered duodenal stents rapidly relieve malignant gastric outlet obstruction, but tumor overgrowth restenosis limits durability. We compared six preprocedural inflammatory, nutritional, and immune indices for predicting this outcome in patients with gastric cancer. METHODS: We retrospectively analyzed 68 consecutive patients from a prospectively maintained cohort. The primary endpoint was endoscopically or radiologically confirmed tumor overgrowth restenosis. Discrimination was assessed using receiver operating characteristic curves (pairwise DeLong tests with Bonferroni correction) and time-dependent areas under the curve (AUCs) accounting for death as a competing risk. Multivariable cause-specific Cox models were restricted to preprocedural covariates; post-stenting chemotherapy or radiotherapy was examined in time-dependent sensitivity analyses. RESULTS: Technical and clinical success rates were 100% and 94.1%. Seventeen patients (25.0%) developed restenosis at a median of 66 days. The C-reactive protein-albumin-lymphocyte (CALLY) index showed the highest AUC (0.859), followed by the C-reactive protein-to-albumin ratio (CAR; 0.822) and neutrophil-to-lymphocyte ratio (0.774); these three indices did not differ significantly. At an exploratory, internally derived cutoff of &#x2264;0.110, CALLY had 76.5% sensitivity and 84.3% specificity and remained associated with restenosis after adjustment for stenosis site and stent length (adjusted hazard ratio, 12.30; 95% confidence interval, 3.89-38.83; C-index, 0.836), with consistent results in continuous, time-dependent, and tumor-covariate-adjusted analyses. The 180-day cumulative incidence was 52.4% with low CALLY versus 4.3% with high CALLY. CONCLUSIONS: C-reactive protein-based indices showed the highest numerical discrimination, although pairwise differences among CALLY, CAR, and NLR were not statistically significant. CALLY is a promising exploratory biomarker for restenosis risk stratification, but its cutoff should not guide clinical decisions until externally validated.

C-reactive protein↗
PubMed2006

Biomarkers in cardiovascular disease: integrating pathophysiology into clinical practice.

Biomarkers play an important role in the diagnosis, prognostic assessment, and management of patients with suspected acute coronary syndromes (ACS). Specific biomarkers identify different components of the pathophysiology of ACS: troponins are prototype markers of myocyte necrosis, natriuretic peptides reflect neurohormonal activation and hemodynamic stress, soluble CD40 ligand is an indicator of platelet activation, and C-reactive protein, myeloperoxidase, and monocyte chemoattractant protein-1 reflect various inflammatory processes. When combined, multiple biomarkers reflecting different pathophysiologic processes appear to enhance risk stratification, as compared with using individual markers alone. Advances in proteomic technology promise to identify additional novel biomarkers that facilitate diagnosis, risk stratification, and selection of therapies in ACS. In the future, it is hoped that multiple biomarker panels will form the basis of an individualized approach to the treatment of ACS, in which therapy is tailored to individual biomarker profiles.

Biomarkers↗
PubMed2004

Molecular biomarkers in drug development.

Arguably, the most immediately promising reverberation of the genomics era has been the application of biomarkers to drug development. The promise of applying biomarkers to early drug development is that they might aid in preclinical and early clinical decisions such as dose ranging, definition of treatment regimen, or even a preview of efficacy. Later in the clinic, biomarkers could be used to facilitate patient stratification, selection and the description of surrogate endpoints. Information derived from biomarkers should result in a better understanding of preclinical and clinical data, which ultimately benefits patients and drug developers. If the promise of biomarkers is realized, they will become a routine component of drug development and companions to newly discovered therapies.

Animals↗
PubMed2002

Multimarker approach to risk stratification in non-ST elevation acute coronary syndromes: simultaneous assessment of troponin I, C-reactive protein, and B-type natriuretic peptide.

BACKGROUND: In patients with acute coronary syndromes (ACS), troponin I (TnI), C-reactive protein (CRP), and B-type natriuretic peptide (BNP) each predict adverse cardiac events. Little is known, however, about the utility of these biomarkers in combination. METHODS AND RESULTS: Baseline measurements of TnI, CRP, and BNP were performed in 450 patients in OPUS-TIMI 16. Elevations in TnI, CRP, and BNP each were independent predictors of the composite of death, myocardial infarction (MI), or congestive heart failure (CHF). When patients were categorized on the basis of the number of elevated biomarkers at presentation, there was a near doubling of the mortality risk for each additional biomarker that was elevated (P=0.01). Similar relationships existed for the endpoints of MI, CHF, and the composite, both at 30 days and through 10 months. In a validation cohort of 1635 patients in TACTICS-TIMI 18, the number of elevated biomarkers remained a significant predictor of the composite endpoint after adjustment for known clinical predictors: patients with one, two, and three elevated biomarkers had a 2.1- (P=0.006), 3.1- (P<0.001), and 3.7- (P=0.001) fold increase in the risk of death, MI, or CHF by 6 months. CONCLUSIONS: Troponin, CRP, and BNP each provide unique prognostic information in patients with ACS. A simple multimarker strategy that categorizes patients based on the number of elevated biomarkers at presentation allows risk stratification over a broad range of short- and long-term major cardiac events.

Acute Disease↗
PubMed2002

[Chest pain units. Organization and protocol for the diagnosis of acute coronary syndromes].

The two main goals of chest pain units are the early, accurate diagnosis of acute coronary syndromes and the rapid, efficient recognition of low-risk patients who do not need hospital admission. Many clinical, practical, and economic reasons support the establishment of such units. Patients with chest pain account for a substantial proportion of emergency room turnover and their care is still far from optimal: 8% of patients sent home are later diagnosed of acute coronary syndrome and 60% of admissions for chest pain eventually prove to have been unnecessary.We present a systematic approach to create and manage a chest pain unit employing specialists headed by a cardiologist. The unit may be functional or located in a separate area of the emergency room. Initial triage is based on the clinical characteristics, the ECG and biomarkers of myocardial infarct. Risk stratification in the second phase selects patients to be admitted to the chest pain unit for 6-12 h. Finally, we propose treadmill testing before discharge to rule out the presence of acute myocardial ischemia or damage in patients with negative biomarkers and non-diagnostic serial ECGs.

Acute Disease↗
PubMed2006

Novel and potential future biomarkers for assessment of the severity and prognosis of chronic heart failure : a clinical review.

Over the last two decades, the pathophysiology and biomolecular basis of heart failure syndrome has reached sound and more comprehensive understanding. This knowledge has allowed expert researchers and clinicians to explore an entirely new spectrum of potential biochemical markers derived from different cellular and signaling pathways that lead to myocardial hypertrophy, chronic damage of the myocyte, apoptosis, and, ultimately, myocardial remodeling. Indeed, the link between myocardial remodeling and adverse outcomes, as well as the recognition of the myocardial interstitium as a multifunctional dynamic entity strongly influenced by systemic neurohormonal and inflammatory activation, has provided a solid ground for research of biomarkers that might correlate with severity and prognostication in chronic heart failure. This paper reviews and summarize recent literature on some of the most interesting circulating biomarkers with potential use for the stratification of patients with chronic heart failure.

Biomarkers↗
PubMed2006

Tissue plasminogen activator on admission is an important predictor of 30-day mortality in patients with acute myocardial infarction undergoing primary angioplasty.

Tissue plasminogen activator (tPA) is emerging as an important risk factor for coronary heart disease, but the association between tPA concentration and mortality in acute myocardial infarction (AMI) remains uncertain. We studied the relationship between tPA antigen level on admission and 30-day mortality in 226 consecutive patients with AMI undergoing primary angioplasty. Death within 30 days occurred in 13 patients (5.7%). The concentration of tPA was significantly higher among the 13 patients who died than among the 213 who survived (26.5+/-16.3 versus 12.5+/-8.5 ng/mL, p<0.001). Compared with those in the lowest quartile (<9 ng/mL), patients in the highest quartile (>16 ng/mL) had a relative risk of subsequent death of 13.1 (p=0.014). In a Cox regression model, a tPA concentration >19 ng/mL was independently associated with mortality (HR 12.1, 95% CI, 1.9-76.7, p=0.001). This cutoff value had a 76.9% sensitivity and an 85.9% specificity for predicting 30-day mortality. tPA concentration was also higher in patients with severe heart failure (20.9+/-14.2 ng/mL versus 11.7+/-7.5 ng/mL, p=0.001) or ventricular tachyarrhythmia (24.3+/-13.9 ng/mL versus 12.2+/-8.4 ng/mL, p=0.001). In conclusions, elevated tPA antigen at initial presentation in patients with AMI was associated with higher short-term risk of death, suggesting that tPA may be a useful prognostic biomarker for the early risk stratification of these patients.

Aged↗
PubMed2024

Top-Down Proteomics Identifies Plasma Proteoform Signatures of Liver Cirrhosis Progression.

Cirrhosis, advanced liver disease, affects 2 to 5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2&#xa0;years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery top-down proteomics to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring.

Humans↗
PubMed2005

Clinical trial designs for prospective validation of biomarkers.

Traditionally, anatomic staging systems have been used to determine predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in patients with cancer. With new targeted therapies, the role of biomarkers is increasingly promising, suggesting an integrated approach using the genetic make-up of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or in differential diagnosis (identifying individuals who are likely to respond to specific drugs). To be clinically useful, a marker must favorably affect clinical outcomes such as decreased toxicity, increased overall and/or disease-free survival, or improved quality of life. This paper focuses on possible clinical trial designs for assessing the utility of a predictive marker(s) for toxicity or clinical efficacy. We consider the scenario of single and multiple markers as well as present alternative solutions based on the prevalence of a marker. Our designs rest on the assumption that the methods for assessment of the biomarker are established and the initial results show promise with regard to the predictive ability of a marker. Additional research is clearly warranted to achieve the goal of 'predictive oncology'.

Biomarkers, Tumor↗
PubMed2026

A Foundation Model Based CT Biomarker for Non-Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non-Small Cell Lung Cancer.

Predicting pathological complete response (pCR) to neoadjuvant immunochemotherapy in non-small cell lung cancer (NSCLC) is clinically important yet remains challenging. Here, we introduce a foundation model-derived computed tomography (CT) imaging biomarker established from a multi-center cohort of 702 patients. Specifically, we developed and validated a non-invasive baseline CT-based model for risk stratification of pathological response. To address scanner and protocol heterogeneity, we first built a 3D Vision Mamba-based CT super-resolution model trained on 2494 cases for image standardization. We then fine-tuned a lung cancer-specific CT foundation model from a pretrained 3D model (VoCo) using 6643 chest CT scans. Finally, we constructed a multi-task Swin Transformer that jointly performs risk stratification and segments tumors to generate the imaging biomarker. Across five centers, the model achieved consistently strong generalization (AUC: 0.75-0.87) for pCR prediction. Genomic analysis revealed that the biomarker was independent of tumor mutational burden but significantly associated with TP53 mutations, suggesting an association with a radiogenomic phenotype related to this alteration. Together, these results demonstrate a generalizable and biologically meaningful foundation model-based biomarker for non-invasive risk stratification of pathological response in NSCLC.

Female↗
PubMed2004

Plasma levels of heat shock protein 70 in patients with prostate cancer: a potential biomarker for prostate cancer.

Heat shock protein 70 (Hsp70) is a stress-inducible protein that is also known for its inhibitory effects on apoptosis. Increased Hsp70 expression is reported in a variety of tumor tissues. Heat shock protein 70 is detectable in plasma and could potentially be used as a biomarker for diagnosis or disease stratification. The relationship between plasma levels of Hsp70 and prostate cancer status has not been well studied. Our study was designed to test this relationship. One hundred twenty-five patients with localized/untreated or hormone-refractory prostate cancer were identified. Forty-five healthy male blood donors between 50 and 73 years of age served as controls. EDTA plasma was subjected to quantitative sandwich immunoassays for both Hsp70 and prostate-specific antigen (PSA). Wilcoxon rank-sum tests were used to examine differences by category. Maximally selected c2 statistics were used to identify cutoff points to best distinguish between categories. Plasma Hsp70 levels in the patients with localized untreated disease (n = 68; median, 0.8 ng/mL; interquartile range, 0.5-2.0) were significantly higher than those in the control group (n = 45; median, 0.5 ng/mL; interquartile range, 0.3-0.8; P = 0.0037). Although the primary cutoff point (1.15 ng/mL) significantly distinguished the localized untreated patients from the control group, plasma Hsp70 levels did not prove more effective than PSA as a predictor for diagnosis or stratification of patients with prostate cancer in the context of group comparisons. Nonetheless, several patients in the localized untreated group showed higher plasma levels of Hsp70 than the primary cutoff point even though their PSA levels were within normal range (< 4 ng/mL). Heat shock protein 70 is a marker of prostate cancer, although its clinical utility is uncertain. It is possible that when used in conjunction with PSA it might prove useful in identifying patients with early-stage prostate cancer who might otherwise be missed by PSA screening alone.

Aged↗
PubMedDate not supplied

Evidence-based medical perspectives: the evolving role of PSA for early detection, monitoring of treatment response, and as a surrogate end point of efficacy for interventions in men with different clinical risk states for the prevention and progression of prostate cancer.

Following FDA approval and introduction into the clinic in the mid-1980s, PSA testing has become arguably the most versatile serum tumor marker in urologic oncology with clinical use for early detection (screening) of prostate cancer (PC), risk stratification for clinical staging, prognosis, intermediate biomarker for monitoring tumor recurrence, and more recently as an intermediate biomarker for assessing therapeutic response to antiandrogens, radiation therapy, and chemotherapy. PSA now routinely guides health care providers for the clinical management of PC over a wide range of clinical risk states for men at risk of PC, after local definitive therapy and after systemic therapy to prevent progression to metastatic bone disease, and to palliate men with hormone refractory prostate cancer (HRPC). To further assess the evidence that supports these clinical applications, this commentary reviews and critically evaluates the emerging body of new data focusing on several recently published seminal articles by D'Amico et al and Thompson et al, the new National Comprehensive Cancer Network 2004 recommendations for starting PSA testing at the age of 40 years old, the latest results from 2 phase 3 randomized, controlled trials of taxane-based regimens showing improved survival for men with HRPC, and the recent US FDA Public Workshop on Clinical Trial Endpoints in Prostate Cancer that helped to distill and synthesize the current state of the art and the progress toward validation of PSA metrics (eg, PSA velocity) as a surrogate end point (SE) for treatment efficacy with taxane-based regimens. Furthermore, several randomized, controlled chemoprevention trials in progress evaluating agents such as selenium and vitamin E in high-risk cohorts are well poised to confirm the validity of PSA as an SE for clinical efficacy for the prevention and progression of PC. Although there continues to be a need to validate better biomarkers before diagnosis of PC (more sensitive and specific) and after diagnosis to discern between indolent and aggressive forms of PC, it is very likely that some metric of PSA as a biomarker alone or as part of a panel of other serum proteomic markers or tissue-derived multiplex gene expression arrays will be around for years to come as a useful tool for risk stratification, early detection, prognosis, prediction, and as an SE of efficacy for prevention and treatment of PC.

Biomarkers, Tumor↗
PubMed2006

Proteomics and heart disease: identifying biomarkers of clinical utility.

Cardiovascular disease is the leading cause of mortality and morbidity in the industrialized world. Total worldwide deaths due to this disease are currently estimated at 17 million per year, and this number is expected to increase over the next several decades. To address this epidemic, a major effort has begun to develop new cardiovascular disease markers through the use of proteomic analysis, the global study of proteins. This review discusses strategies, recent technological advances and other issues in plasma/serum biomarker discovery for cardiovascular diseases. Emphasis lies on the needs for standardizing specimen collection, methods for reducing plasma proteome complexity to subproteomes, selection of appropriate technology platforms and strategies to evaluate candidates by multiplexed immune assays. The overall goal of this effort is to identify serum biomarkers for diagnosis, therapeutic monitoring and risk stratification of cardiovascular diseases.

Animals↗
PubMed2026

Large-Scale Plasma Proteomics Identifies Early Molecular Deviations and Improves Risk Prediction for Heart Failure Among Individuals With Obesity.

AIMS: Heart failure (HF) is a major global public health challenge, with obesity being one of its key risk factors. Although several HF risk prediction models have been developed in the general population, few are specifically tailored to individuals with obesity. This underscores the urgent need for precise biomarkers to improve individual risk stratification and enable personalized prevention strategies. We aimed to develop and validate a plasma proteomics-based protein risk score (PRS) to predict incident HF among individuals with obesity. MATERIALS AND METHODS: We analysed 9831 participants with obesity (BMI &#x2265;&#x2009;30&#x2009;kg/m2) from the UK Biobank with baseline measurements of 2911 circulating proteins and up to 16&#x2009;years of follow-up. Multivariable Cox regression identified proteins associated with incident HF after comprehensive covariate adjustment. A PRS was constructed using LASSO regression and evaluated in a held-out test set. Protein trajectories before HF onset were reconstructed using LOESS modelling. To enhance clinical feasibility, a minimal protein panel was identified using LightGBM with forward feature selection. RESULTS: A total of 727 participants developed HF during follow-up. Multivariable cox analyses identified 578 proteins significantly associated with HF. LASSO regression further selected 81 proteins to build the PRS, which showed a strong association with HF risk in both training (HR 3.57; 95% CI 3.19-4.00) and test cohorts (HR 2.45; 95% CI 2.20-2.74). Adding the PRS improved prediction beyond age and sex (&#x394;C&#x2009;=&#x2009;0.091) and beyond the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) model (&#x394;C&#x2009;=&#x2009;0.052), with consistent gains in NRI and IDI. Proteomic deviations were detectable up to 16&#x2009;years before diagnosis. A four-protein panel (GDF15, NT-proBNP, TNFRSF10B, CTHRC1) achieved robust discrimination (AUC 0.789), outperforming NT-proBNP alone (AUC 0.695) and complementing the PCP-HF model (combined AUC 0.803). DISCUSSION: Large-scale plasma proteomics substantially improves HF risk prediction in individuals with obesity and reveals long-standing molecular alterations preceding clinical onset. A simplified four-protein panel maintains robust predictive accuracy and provides a practical approach for the early detection and targeted prevention of obesity-related HF.

Humans↗
PubMed2026

Adjuvant CDK4/6 inhibitors in early-stage breast cancer: Clinical evidence and considerations for risk stratification and treatment selection.

Hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer is the most common biologic subtype and carries a persistent risk of recurrence, particularly in patients with high-risk, early-stage disease. Cyclin-dependent kinase 4 and 6 inhibitors, initially established as a standard component of first-line therapy in the metastatic setting based on improvements in progression-free and overall survival, have since been evaluated in the adjuvant setting. While adjuvant palbociclib did not improve invasive disease-free survival, the monarchE and NATALEE trials demonstrated that abemaciclib and ribociclib, respectively, reduce recurrence risk in patients with high-risk, early-stage disease, with emerging overall survival data further supporting their use. However, the absolute magnitude of benefit varies substantially with baseline risk, and treatment-related toxicity and adherence challenges must be considered, as approximately 20% to 25% of patients discontinue therapy before completion. The integration of these agents into clinical practice also intersects with ongoing efforts to deescalate axillary surgery, as treatment eligibility has been largely defined by anatomic staging, particularly nodal status. Available data suggest that the incremental impact of axillary surgery on identifying candidates for cyclin-dependent kinase 4 and 6 inhibition is modest, especially among the favorable-risk populations now eligible for surgical deescalation. As the field evolves, advances in molecular risk stratification, genomic profiling, and dynamic biomarkers are poised to shift treatment selection from anatomic staging toward biologically driven approaches. Multidisciplinary decision-making that integrates tumor biology, anticipated absolute benefit, toxicity, patient preferences, and surgical considerations will be essential to ensure individualized care.

Humans↗