Abstract Non-small cell lung cancer (NSCLC) exhibits strikingly different responses to antiangiogenic therapies between its two major histologic subtypes, lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), suggesting an histotype-specific regulation of angiogenesis. Cancer-associated fibroblasts (CAFs) commonly exhibit an activated/myofibroblast-like phenotype in NSCLC, and are emerging as key modulators of tumor progression; however, their contribution to angiogenic control remains undefined. Here, we investigated angiogenesis and hypoxia signatures in NSCLC and integrated bulk RNA-seq, scRNA-seq, CAF secretome profiling, genetic perturbations, and functional in vitro and in vivo assays to dissect the histotype-dependent production of pro-angiogenic factors by CAFs. We observed greater angiogenesis and reduced necrosis/hypoxia in LUAD compared to LUSC across multiple patient cohorts. The LUAD-CAF secretome was primed for angiogenesis through SMAD3-dependent overproduction of key regulators, most notably TIMP-1 and VEGF-A. We also uncovered a previously unrecognized role for TIMP-1 in promoting endothelial hyper-branching. In contrast, LUSC-CAFs displayed attenuated angiogenic activity despite robust HIF-1α upregulation and an hypoxia-associated transcriptional program, due to their epigenetic repression of SMAD3 and compensatory increase in SMAD2. Collectively, these results reveal that CAFs critically shape the distinct angiogenic landscapes of LUAD and LUSC through opposing SMAD2/3 regulation of TIMP-1, VEGF-A, and hypoxia signaling. These results further highlight the therapeutic potential of targeting stromal SMAD3/TIMP-1 in LUAD or microenvironmental stressors such as hypoxia and acidosis in LUSC. In addition, these findings provide a biological framework for understanding histotype-specific patterns of dissemination, immune evasion, and response to antiangiogenic therapies in NSCLC. Citation Format: Jordi Alcaraz, Natalia Isabel Diaz Valdivia, Paula Duch, Marselina Arshakyan, Amelia Parker, Alejandro Bernardo Suarez, Danielle Park, Erik Sahai, Noemi Reguart, Derek C. Radisky, Oriol Casanovas. Antagonistic SMAD2/3 control of TIMP-1, VEGF-A, and hypoxia signaling in myofibroblasts shapes histotype-specific angiogenesis in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4797.

Abstract Background Building on evidence linking urinary glyphosate to chronic liver disease (CLD) and hepatocellular carcinoma (HCC), we developed urinary pesticide profiling integrated with machine learning risk prediction (MLRP) to stratify risk in high-exposure populations.Methods We conducted a case-control study within the Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC; 2011-2016; n=593): 228 CLD, 116 HCC, and 249 controls. Eight urinary pesticides were quantified by LC-MS/MS (pendimethalin, oxadiazon, metsulfuron-methyl, butachlor, 2,4-dichlorophenoxyacetic acid [2,4-D], cypermethrin, flocoumafen, bromadiolone). A composite Pesticide Load Score (PLS), with and without glyphosate, estimated burden. Two predictive models were developed: a logistic-regression Pesticide-Informed Liver Cancer Risk Score (PILCRS) and an Extreme Gradient Boosting (XGBoost) classifier that incorporated age, sex, alcohol use, occupation, and PLS. Internal validity used 1,000 bootstrap resamples with optimism-corrected calibration.Findings Predicted CLD probability increased from 30% in the lowest PLS quartile to over 70% in the highest, and HCC from 10% to 40% (p<0ꞏ0001). Relative estimates were consistent; the highest versus lowest quartile yielded odds ratios of 2ꞏ84 (95% CI 1ꞏ66-4ꞏ91) for CLD and 4ꞏ76 (2ꞏ30- 10ꞏ29) for HCC. Cypermethrin remained independently associated. After optimism correction, both models demonstrated strong discrimination and calibration.Interpretation This framework establishes a scalable, exposure-informed tool for liver disease prediction. Findings underscore pesticide burden as a modifiable risk factor and align with Sustainable Development Goal 3ꞏ9 and WHO-FAO priorities in low- and middle-income countries (LMICs). External validation is essential. Citation Format: Daxeshkumar P. Patel, Christopher Loffredo, Majda Haznadar, Mohammed Khan, Amelia Parker, Benjarath Pupacdi, Siritida Rabibhadana, Panida Navasumrit, Nirush Lertprasertsuke, Anon Chotirosniramit, Chawalit Pairojkul, Vor Luvira, Ake Pugkhem, Wattana Sukeepaisarnjaroen, Teerapat Ungtrakul, Thaniya Sricharunrat, Kannika Phornphutkul, Frank J. Gonzalez, Anuradha Budhu, Chulabhorn Mahidol, Xin Wei Wang, Mathuros Ruchirawat, Curtis C. Harris, TIGER-LC Consortium.. Urinary pesticide biomarkers and liver disease risk in Thailand: A machine-learning-based risk-prediction model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2443.

Univariate and multivariate regression analysis for factors associated with survival in nonsmokers from both cohorts.

K-M plots of overall survival of lung cancer cases stratified by the median cutoff value of CR and NANA for smokers in (A) Exploratory cohort and (B) Validation cohort.

Box plots showing the distribution of CR and NANA urinary metabolite levels in the (A) exploratory cohort and (B) validation cohort were quantitatively measured by UPLC–MS/MS in the study participants. Kruskal–Wallis ANOVA; posthoc multiple comparisons, ****P < 0.0001; **P < 0.01. LCC, lung cancer cases; x͂ = median.

Abstract Purpose: Nonsmokers account for 10% to 13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose CT (LDCT). Experimental Design: Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort). The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA), were analyzed and quantified using liquid chromatography–mass spectrometry to determine if nonsmoker cases can be distinguished from sex and age-matched controls in comparison with tobacco smoker cases and controls, potentially leading to more precise eligibility criteria for LDCT screening. Results: Urinary levels of CR and NANA were significantly higher and comparable in nonsmokers and tobacco smoker cases than population controls in both cohorts. Receiver operating characteristic analysis for combined CR and NANA levels in nonsmokers of the exploratory cohort resulted in better predictive performance with the AUC of 0.94, whereas the validation cohort nonsmokers had an AUC of 0.80. Kaplan–Meier survival curves showed that high levels of CR and NANA were associated with increased cancer-specific death in nonsmokers as well as tobacco smoker cases in both cohorts. Conclusions: Measuring CR and NANA in urine liquid biopsies could identify nonsmokers at high risk for lung cancer as candidates for LDCT screening and warrant prospective studies of these biomarkers.

Distribution of CR and NANA metabolite levels in late-stage (III & IV) cases. **** p<0.0001, *** p<0.001; LS, late-stage (III & IV); x͂ = median

ROC curves represent the accuracy of metabolite CR, NANA, and the combination with AUC for smoking status in both cohorts: (A) nonsmokers and (B) smokers. PC, population controls.

K–M plots of the overall survival of lung cancer cases stratified by the median cutoff value of CR and NANA for nonsmokers in the (A) exploratory cohort and (B) validation cohort.

Distribution of CR and NANA metabolite levels in early-stage (I & II) cases. ****, p < 0.0001, ***, p < 0.001; ES, early-stage (I & II); x͂ = median

The diagnostic efficiency of models in non-smoking exploratory and validation cohorts. LCC, Lung cancer cases; PC, Population controls; AUC, area under the curve; CI, confidence interval; SN, Sensitivity; SP, Specificity; NPV, negative predictive values; PPV, positive predictive values; CR, Creatine riboside; NANA- N-acetyl neuraminic acid.

Distribution of CR and NANA metabolite levels in AA and EA participants. **** p<0.0001* p<0.05; AA, African American; EA, European American; LCC, lung cancer cases; x͂ = median

In recent decades, the role of tumor biomechanics on cancer cell behavior at the primary site has been increasingly appreciated. However, the effect of primary tumor biomechanics on the latter stages of the metastatic cascade, such as metastatic seeding of secondary sites and outgrowth remains underappreciated. This work sought to address this in the context of triple negative breast cancer (TNBC), a cancer type known to aggressively disseminate at all stages of disease progression. Using mechanically tuneable model systems, mimicking the range of stiffness's typically found within breast tumors, it is found that, contrary to expectations, cancer cells exposed to softer microenvironments are more able to colonize secondary tissues. It is shown that heightened cell survival is driven by enhanced metabolism of fatty acids within TNBC cells exposed to softer microenvironments. It is demonstrated that uncoupling cellular mechanosensing through integrin β1 blocking antibody effectively causes stiff primed TNBC cells to behave like their soft counterparts, both in vitro and in vivo. This work is the first to show that softer tumor microenvironments may be contributing to changes in disease outcome by imprinting on TNBC cells a greater metabolic flexibility and conferring discrete cell survival advantages.

Survival analysis for Non-smokers and Smokers by stage and histology. K-M plot for (A) Early-stage (I &II) Lung cancer cases; Late-stage (III & IV) Lung cancer cases and (B) LUAD cases; LUSC cases. NS, Non-smokers; SK, Smokers; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma

Distribution of CR and NANA metabolite levels in non-smoker cases without and with (A) Childhood parental smoking exposure and (B) Secondhand smoking exposure. **** p<0.0001; NS, non-smokers; CPS, Childhood parental smoking exposure; SHS, Secondhand smoking exposure, LCC, lung cancer cases; x͂ = median

Cox proportional analysis for factors associated with survival

Clinical characteristics of the study participants by smoking status.

Introduction: Never smokers account for 10-13% of all lung cancer cases in the United States. The etiology is attributed to multiple causes including exposure to passive smoking, parental smoking, asbestos and radon. However, these lung cancer cases do not fit the current United States Government-funded criterion of low-dose computed tomography that identifies early stages of lung cancer with higher survival following surgical removal. Methods: The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA), were analyzed and quantified by liquid chromatography-mass spectrometry to determine if never smokers with non-small cell lung cancer (NSCLC) can also be identified alongside tobacco smoker NSCLC cases as compared with gender and age-matched non-cancer population controls. Results: These cancer biomarkers were significantly higher and comparable in never-smokers and tobacco smokers cases compared to population controls. Receiver Operating Characteristics (ROC) analysis in never smokers was equivalent for CR and NANA levels area under the curve (AUC) 0.91. In contrast, combined CR and NANA levels resulted in better predictive performance (AUC 0.94). Kaplan-Meier survival curves showed that high levels of CR and NANA were associated (p<0.05) with increased cancer-specific death in never-smokers and tobacco smokers. Therefore these metabolites are independent of Tobacco smoking. NANA metabolite category factor, histology and stage were independent predictors of survival (p<0.05) in multivariate analyses for never smokers as shown in Table 1. Conclusions: These results indicate that measuring CR and NANA in liquid biopsy urine could identify never-smoking lung cancer candidates for LDCT screening and warrant prospective studies of these biomarkers in high-risk environments. Table 1. Univariate and multivariate regression analysis for factors associated with survival in the never smokers population Univariate Analysis Multivariate analysis Factors Levels N HR 95%CI P-value HR 95%CI P-value Stage Early Stage (I & II); Late Stage (III & IV) 145 3.52 2.3, 5.3 <0.001 3.94 2.2, 6.8 <0.001 Histology Adenocarcinoma; Squamous cell carcinoma 114 1.62 0.7, 3.5 0.26 3.42 1.4, 7.9 0.01 CR Category Low; High 166 1.34 0.8-2.1 0.19 1.67 0.9, 3.0 0.08 NANA Category Low; High 166 2.11 1.1-3.9 0.009 2.31 1.0, 5.0 0.02 Age N=166 166 1.00 0.9, 1.0 0.50 0.99 0.9, 1.0 0.4 Sex Male; Female 166 0.87 0.5, 1.2 0.49 0.90 0.5, 1.5 0.7 Race African American; European American 166 0.82 0.2, 2.5 0.75 0.40 0.1, 1.3 0.2 Citation Format: Bhavik Dalal, Takeshi Tada, Daxesh P. Patel, Mohammed Khan, Takahiro Oike, Yasuyuki Kanke, Amelia Parker, Majda Haznadar, Leila Toulabi, Kristopher Krausz, Ana Robles, Elise Bowman, Frank Gonzalez, Curtis Harris. Urinary metabolite diagnostic and prognostic liquid biopsy biomarkers of lung cancer - never smokers versus tobacco smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1001.

Two-Dimensional Difference Gel Electrophoresis (2D-DIGE) of cytoplasmic and nuclear extracts of H460 NSCLC cells expressing βIII-tubulin or control shRNA.

<p>Suppression of βIII-tubulin increases cell adhesion and decreases cell migration in NSCLC cells.</p>