Citations

Abstract Rationale: The D'Nerva Targeted Lung Denervation (TLD) System uses radiofrequency energy delivered bronchoscopically to the main bronchi to disrupt parasympathetic nerve innervation to the lung. AIRFLOW-3 clinical trial was a randomized, double blind, sham controlled study to determine the impact of TLD on COPD exacerbations. Methods: AIRFLOW-3 patients had symptomatic COPD (CAT ≥10) with moderate to very severe airflow obstruction (GOLD stage II-IV: 25% ≤ FEV1 ≤ 80% predicted, FEV1/FVC<0.70) and GOLD E status (≥2 moderate or ≥1 severe exacerbation in the prior 12 months) despite optimal medical therapy. The primary endpoint was a time-to-first event comparison of the probability of subjects having a moderate or severe exacerbation, between the Treatment arm (TLD + optimal medical therapy) and the Sham Control arm (optimal medical therapy). Results: 388 patients were randomized 1:1 at 32 clinical sites across the US, EU, and UK. Patients were 67.8 (SD 7.1) years of age, ex-smokers with a 46.7 (22.0) pack-year smoking history, and 41.0 (11.8) post bronchodilator FEV1% pred. SGRQ-C and CAT scores were 62.5 (17.0) and 23.6 (6.3), respectively. Over 90% of patients were on triple therapy (LAMA+LABA+ICS) at baseline and through 1 year of follow up. 42% of patients had prior-year COPD hospitalization(s). There was no difference between groups in the analysis of the primary endpoint. At 1 year, the sham arm exhibited a statistical decline in lung function (decrease in FEV1 and FVC) and worsening of gas trapping (increase in RV). Lung function and gas trapping were stable in the treatment arm. The treatment arm exhibited a statistically significant improvement in dyspnea at one year compared to sham (mMRC, and TDI). These observations led to the identification of a subgroup of TLD treatment responders corresponding to an airway predominant phenotype (lung hyperinflation in the absence of significant emphysema) that demonstrated clinically and statistically significant improvements in lung function and exacerbation frequency and severity (Table). Conclusions: The AIRFLOW-3 clinical trial failed to meet its prespecified primary endpoint. Post-hoc analysis of this robust dataset led to the identification of a responder profile that achieved significant and sustained improvements in lung function, and exacerbation reduction. A future clinical study is being designed to confirm these findings.

Importance A subset of Union for International Cancer Control ( UICC )/ American Joint Committee on Cancer ( AJCC ) eighth edition TNM stage I and II human papillomavirus–positive oropharyngeal carcinoma has undesirable outcomes, which might have contributed to a lack of success in phase III deintensification trials. Refining clinical stage groups, especially in the overabundant cN1/stage I group, has become important for treatment selection. Objective To assess the prognostic importance of pretreatment lymph node (LN) characteristics to optimize case distribution and outcome homogeneity within the N classification system. Design, Setting, and Participants This is an international multi-institutional retrospective prognostic cohort study. Analysis of human papillomavirus–positive oropharyngeal carcinoma treated curatively from 4 institutions (International Collaboration of Oropharyngeal Cancer Network for N-Classification [ICON-N] dataset) provided a refined clinical staging proposal; an independent dataset (Centre Hospitalier de l’Université de Montréal [CHUM] dataset) validated the proposal. Neuroradiologists reviewed pretreatment computed tomography and/or magnetic resonance imaging for nodal features, including presence or absence of abnormal LN(s), retropharyngeal LN, laterality, number of abnormal LN, and imaging-detected extranodal extension (iENE). Data were collected from February to May 2023, and data were analyzed from June to July 2023. Exposures Definitive chemoradiotherapy/radiotherapy or definitive surgery with or without postoperative chemoradiotherapy/radiotherapy. Main Outcomes and Measures The primary end point was overall survival. A Cox proportional hazards multivariable model was used to estimate adjusted hazard ratios (AHRs) and to derive an optimal clinical TNM stage classification (AHR-stage schema) incorporating the strongest prognostic nodal features within the UICC/AJCC eighth edition TNM framework after confirming the prognostication of iENE status. The performance (according to overall normalized scores and ranking) of the AHR-stage schema against the current UICC/AJCC eighth edition TNM staging system was evaluated for hazard consistency, hazard discrimination, prognostic importance, and sample size balance. Validation was performed in the CHUM dataset. Results The ICON-N dataset comprised 2053 patients, including 1898 (92.5%) with cN-positive disease and 155 (7.5%) with cN0 disease; a total of 298 (14.5%) were female, and the mean (SD) age was 60.6 (9.3) years. iENE-positive disease was identified in 710 of 1898 patients with cN-positive disease (37.4%). The median (range) follow-up was 5.1 (0.1-14.7) years. iENE was the strongest prognostic nodal feature in multivariable analysis; the AHR for iENE-positive vs iENE-positive disease was 2.43 (95% CI, 1.96-3.03) in the ICON-N dataset and 2.04 (95% CI, 1.28-3.23) in the CHUM dataset (n = 451). Reclassifying iENE-positive cases 1 stratum higher for N categorization without altering iENE-negative cases yielded an AHR-stage schema that outperformed the current TNM staging system in disease-free and overall survival with a lower (ie, better) overall normalized score (2 vs 3). Conclusions and Relevance In this study, reclassifying each N category 1 stratum higher for iENE-positive disease resulted in better disease-free and overall survival. The proposed new classification outperformed the currently TNM staging system in risk stratification and may facilitate future clinical trial design, outcomes research, and patient care.

Gastric cancer is the fifth leading cause of cancer-related deaths worldwide. Over 95% of gastric cancers are adenocarcinomas, which are typically classified based on anatomic location and histologic type. Gastric cancer generally carries a poor prognosis because it is often diagnosed at an advanced stage. Systemic therapy can provide palliation, improve survival, and enhance the quality of life in patients with locally advanced or metastatic disease. The implementation of biomarker testing has had a significant impact on clinical practice and patient care. Targeted therapies have demonstrated encouraging results in clinical trials for the treatment of patients with locally advanced or metastatic disease. This selection from the NCCN Clinical Practice Guidelines in Oncology for Gastric Cancer highlights recommendations for biomarker testing and discusses updates for the treatment of advanced disease, including peritoneal carcinoma as only disease and unresectable locally advanced, recurrent, or metastatic disease.

Abstract Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a fast-rising global public health problem. About 10% of patients with MASLD will develop hepatocellular carcinoma (HCC), but molecular markers for predicting future risk of HCC development in patients with MASLD are lacking. We investigated whether protein biomarkers in pre-malignant plasma samples can predict susceptibility to HCC in the setting of MASLD. Methods: A nested case-control study was performed among patients with MASLD who later developed HCC (cases) and MASLD patients who never progressed to HCC (controls), matched on age at MASLD diagnosis (± 1-year), sex, the year of blood sample collection, and length of follow-up (± 1-year). MASLD at baseline was determined by the presence of hepatic steatosis (assessed by imaging or biopsy) plus at least one cardiometabolic condition (obesity, diabetes mellitus, hypertension, or dyslipidemia). Archival baseline plasma samples stored at -80oC were used to perform the SomaScan 7k v4.0 assay. We also performed genotyping of the well-established HCC susceptibility variant, PNPLA3-rs738409 (I148M), among the cases and controls. The study sample was split into discovery (70%) and validation (30%) sets, and we selected promising protein biomarkers in the discovery set using differential expression analysis with volcano plots and Bonferroni-corrected p-values. A final set of significant proteins was used for prediction modeling in the validation sample, calculating area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and accuracy. Results: The study sample included 54 MASLD to HCC cases and 54 MASLD controls, split into discovery and validation sets. We identified five significantly differentially expressed proteins in the discovery set, four overexpressed (TSP2, GPR56, MIC-1, TIMP-1) and one under-expressed (IGFALS) in the cases versus controls. Fitting the five proteins in the validation sample yielded an AUC=0.88, sensitivity=0.87, specificity=0.75, and accuracy=0.81. Adding PNPLA3-rs738409 to the model improved the model’s specificity and accuracy (AUC=0.88, sensitivity=0.87; specificity=0.81, accuracy=0.84). Conclusions: Our findings show that a five-protein biomarker panel can robustly predict future HCC development in patients with MASLD. Adding a well-established HCC genetic risk variant, PNPLA3-rs738409, slightly improved the model’s performance. These initial findings provide evidence of HCC prediction with baseline plasma biomarkers and genetic risk variants, toward improving risk stratification and enhancing early detection of HCC in the setting of metabolic perturbations. Citation Format: Ampem Darko Jnr Siaw, Sebastian M. Armasu, Jacob A. Frank, Irene K. Yan, Kirk J. Wangensteen, Tushar Patel, Samuel O. Antwi. Protein biomarkers of HCC development in patients with metabolic liver disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2350.

Abstract Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects about 32% of adults worldwide and is projected to increase in many parts of the world. Liver cancer is a recognized complication of end-stage MASLD. An estimated 20% of patients with MASLD will progress to cirrhosis, a premalignant state in liver cancer evolution. Because MASLD is usually asymptomatic, its progression to cirrhosis can be difficult to detect early for timely intervention. There are currently no known biological markers for predicting cirrhosis risk in patients with MASLD, making it challenging to identify patients at risk of disease progression. The aim of this study was to identify plasma protein biomarkers that can predict future cirrhosis development in patients with MASLD. Methods: We performed a nested case-control study among patients with MASLD at baseline who later progressed to cirrhosis and control patients with MASLD at baseline who never progressed to cirrhosis, matched on age at MASLD diagnosis (± 1-year), sex, race, year of blood sample collection, and length of follow-up (± 1-year). An aptamer-based array (SOMAscan™) platform was used to measure over 7000 proteins in baseline plasma samples obtained from the participants. The study sample was split 70/30 for training and validation analyses. We identified plasma protein biomarkers significantly differentially expressed in the training sample, adjusting for multiple testing with Bonferroni-corrected p-values. The significant set of proteins from the training set was used for prediction modeling in the validation sample, computing prediction metrics (area under the curve [AUC], sensitivity, specificity, and accuracy). Results: A total of 64 MASLD to cirrhosis cases matched to 64 MASLD controls were included in the analysis. Six protein biomarkers (PTPRU, ATL2, MFAP4, C7, CSTN2, and COLEC11) were overexpressed in cases, compared to controls, in the training data. Prediction modeling of the six-protein biomarker panel in the validation sample yielded an AUC = 0.85, sensitivity = 0.72, specificity = 0.78, and accuracy = 0.75. Conclusions: We have identified a panel of six plasma protein biomarkers that predict risk of cirrhosis development in patients with MASLD. These proteins could serve as candidates for future mechanistic studies on MASLD progression to advanced liver disease. If validated in larger studies and with assays suitable for clinical laboratory testing (e.g., ELISA), these protein biomarkers could be useful clinically for cirrhosis risk prediction in MASLD patients, and hence those at risk of liver cancer, enabling timely surveillance or interventions to prevent disease progression. Citation Format: Pasang Sherpa, Sebastian M. Armasu, Jacob A. Frank, Irene K. Yan, Kirk J. Wangensteen, Tushar Patel, Samuel O. Antwi. Predicting cirrhosis risk in patients with metabolic dysfunction-associated steatotic liver disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2335.

Abstract Background: Mutant BRAF(V600E) is present in 8-12% of human colorectal cancers (CRCs) and is associated with treatment resistance and poor survival. Targeted therapy with inhibitors of BRAF and EGFR is associated with only an incremental survival benefit. Methods: We studied the novel CDK2/CDK9 inhibitor, fadraciclib, alone and in combination with the BRAF inhibitor encorafenib on isogenic CRC cells with two, one, or no BRAFV600E alleles (RKO+/+, A19+/-, T29-/-). Analysis of apoptosis, colony formation, and the cell cycle was performed. The effect of drug treatment on growth of tumor xenografts was determined in a zebrafish model. Results: Fadraciclib induced apoptosis and inhibited colony formation in a gene dose-dependent manner. Its growth inhibitory effect when combined with encorafenib was synergistic. Mechanistically, fadraciclib suppressed the expression of pro-survival MCL-1 and decreased the phosphorylation of RNA polymerase II indicating suppression of RNA transcription. Fadraciclib also impaired Rb phosphorylation and promoted a DNA damage response indicated by the cleavage of PARP, pH2AX (ser139), and activation of p53. Drug treatment was associated with a greater suppression of Rb phosphorylation, cell cycle inhibition, and apoptosis in RKO+/+ versus A19+/- and T29-/- cells. In a zebrafish tumor xenograft model, fadraciclib plus encorafenib significantly reduced the tumor xenograft size concurrent with increased caspase-3 activation. Conclusion: Fadraciclib plus encorafenib potently induced apoptosis and synergistically suppressed tumor cell growth in a gene dose-dependent manner in BRAFV600E CRC cells, and exerted anti-tumor effects in a tumor xenograft model. These data suggest a novel therapeutic strategy in this CRC subtype. Citation Format: Md Mohiuddin, Vanda Póvoa, Rita Fior, Frank A. Sinicrope. Novel CDK2/CDK9 inhibitor fadraciclib targets cell survival and DNA damage pathways and synergizes with encorafenib in human colorectal cancer cells with BRAF(V600E). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1682.