tbuckley/cabot-search huggingface dataset:
Retrospective single-institution application of a deep learning–based radiomic score in metastatic NSCLC: Potential impact on first-line treatment decisions and outcomes.
Authors: Nicholas Campbell Love, Karishma Sewaramani, Ross McCall, Taly Schmidt, Ryan Beasley, Arpan Patel
Journal: Journal of Clinical Oncology (2025)

e20608 Background: Immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis are standard of care for metastatic non-small cell lung cancer (mNSCLC). Yet a minority of patients achieve durable benefit from ICI monotherapy (ICI MT), underscoring the limitations of current predictive biomarkers such as PD-L1 tumor proportion score (TPS). Lung Clinical Management (LCM) is a novel deep learning-based radiomic biomarker that classifies patients as LCM-high or LCM-Low (likelihood of ICI MT benefit). We retrospectively evaluated if LCM could guide the selection of first-line ICI MT vs chemo-immunotherapy (IT) in mNSCLC. Methods: We conducted a single-institution retrospective chart review of 27 patients who received anti-PD-1 ICI treatment (alone or in combination with chemo) for mNSCLC between 2012 and 2025. Patients were excluded if they lacked documented PD-L1 TPS, received &lt;1 full dose of disease-directed therapy, or participated in a clinical trial. The LCM score was generated using a radiomics pipeline comprising imaging quality control, preprocessing, expert lesion annotation, deep learning feature extraction, and Cox-based survival modeling. Baseline CT/PET-CT scans and select variables (age, sex, and line of therapy) served as inputs. Model development was blinded to treatment decisions and outcomes. We compared the first-line therapy chosen without LCM to the LCM recommendation. Endpoints included treatment selection, subsequent therapies, treatment-related adverse events, and mortality. Results: The treatment recommended by a clinician with access to LCM aligned with the original treatment in 14 patients (51.85%) and differed in 13 (48.15%). Among these 13 patients, 3 classified as LCM-high received upfront chemo (2 alone, 1 combined with IT); 2 of the 3 developed severe toxicities. Had these patients received ICI MT as suggested by LCM, they might have avoided chemo-related toxicity. 7 of the 13 had PD-L1 TPS ≥50% but were classified as LCM-low, indicating a low likelihood of ICI MT benefit; yet they received ICI MT. 3 of the 7 ultimately received chemo, and all 7 died (4 within 1 year of diagnosis). The remaining 3 of 13 received chemo alone without IT. Conclusions: The prognostic information provided by LCM identified patients who were likely to respond to ICI MT but were instead treated with chemo, potentially exposing them to preventable treatment-related adverse effects. LCM also identified patients unlikely to respond to frontline ICI MT but received it, with some patients subsequently receiving chemo and others expiring before further therapy. These findings suggest that LCM could refine first-line treatment decisions, helping avoid unnecessary toxicity in patients likely to benefit from ICI MT and guiding earlier use of chemo-IT in those less likely to respond to MT.
Clinical impact of single nucleotide polymorphisms (SNPs) in <i>PDCD1</i> in patients with non-small cell lung cancer (NSCLC) receiving anti-PD1 immunotherapy.
Authors: Foteinos-Ioannis Dimitrakopoulos, Maria Loukopoulou, Anastasia E. Kottorou, Maria Pandi, Fotios Andreas Chrysanthakopoulos, Rafaella Argyriadi, Thomas Makatsoris, Haralabos Kalofonos, Angelos Koutras
Journal: Journal of Clinical Oncology (2025)

e20625 Background: Lung cancer is the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Over the past few years, immunotherapy has emerged as a key treatment option for NSCLC, particularly targeting the PD-1/PD-L1 pathway. Although current biomarkers have significantly improved the treatment of NSCLC, the need for additional biomarkers remains critical. The identification of genetic variations, such as single nucleotide polymorphisms (SNPs) in PDCD1 gene, has gained attention due to their potential prognostic and predictive value. These SNPs may provide valuable information regarding treatment response, side effects, and overall survival in patients undergoing anti-PD1 therapy. In the current study we investigated the clinical significance of specific SNPs in PDCD1 gene and their impact on treatment outcomes in NSCLC patients receiving anti-PD1 immunotherapy. Methods: For this purpose, we studied the polymorphisms rs2227981 (PD1.5) and rs7421861 (PD1.7).The selection of the specific SNPs was based mostly on literature. Blood samples from 90 patients with stage III and IV NSCLC treated with anti-PD1 immunotherapy in the University Hospital of Patras were used. DNA was extracted and utilized for genotyping using Real-Time PCR with appropriate primers and labeled probes. Sanger sequencing was subsequently performed for specific samples for additional confirmation of the results. The genotypes frequencies were correlated with the clinicopathological characteristics and clinical outcomes of the patients. Finally, data analysis was carried out using the statistical software SPSS 28.0. Results: Interestingly, the rs7421861 polymorphism and especially the allele A, was associated with fewer irAEs (Immune-Related Adverse Events) ( p =0.021). In addition, A allele of rs7421861 was also associated with longer time to disease progression (TPP) and longer overall survival (OS, p =0.041 and p =0.003, respectively). On the other hand, no association was found between rs2227981 with the clinical outcome of the patients, however, this polymorphism was associated with the disease stage, specifically the AG genotype with stage III (p=0.016). Conclusions: Our study suggests that the single nucleotide polymorphism rs2227981 may, in the future, be used as prognostic and predictive biomarkers for patients with NSCLC receiving anti-PD1 immunotherapy, however more studies are needed to further validate its clinical significance.
Influence of inhaled corticosteroids on immune checkpoint inhibitor pneumonitis and mortality in patients with COPD and lung cancer.
Authors: Nolan Holley, Shanawar Ali Waris, Adnan Saifuddin, Nanda Siva, Yashan Thakkar, Salah Ud Din Safi
Journal: Journal of Clinical Oncology (2025)

e20628 Background: The use of inhaled corticosteroids (ICS) in patients with chronic obstructive pulmonary disease (COPD) requires careful clinical judgment to balance factors such as disease severity, exacerbation frequency, and peripheral eosinophil counts with the risk of infection. In lung cancer, immune checkpoint inhibitors (ICIs) utilize the host immune system to detect and eliminate malignant cells. However, ICS are inherently immunosuppressive, which raises concerns about their interactions with ICI therapy. The role of ICS specifically in the management of COPD among lung cancer patients receiving ICIs remains underexplored. Methods: The TriNetX global federated research network was utilized to identify real-world cohorts of patients with COPD treated with long-acting beta agonists (LABA) and long-acting muscarinic antagonists (LAMA), with or without ICS, who subsequently developed lung cancer and were treated with an ICI. Patients treated with ICS were compared to a 1:1 propensity score-matched (PSM) cohort of patients not treated with ICS to reduce confounding. Primary outcomes included one-year mortality and the development of ICI pneumonitis within one-year following lung cancer diagnosis and initiation of an ICI. The secondary outcome was the risk of infection. Relative risks (RR) were calculated to assess associations between ICS use and ICI pneumonitis or infection, while Kaplan-Meier analysis was used to determine mortality outcomes between cohorts. Results: Following PSM, two balanced cohorts of 724 patients who were on ICS and 724 patients who were not on ICS were compared. The use of an ICS was associated with a significantly higher risk of developing ICI pneumonitis within the first year of ICI treatment (RR = 1.379 [95% CI, 1.101-1.728]). ICS use was associated with a reduction in one-year mortality (HR = 0.813 [95% CI, 0.676-0.977], p =0.027). There were no significant differences in infections between the two groups (RR = 1.152 [95% CI, 0.998-1.329]). Conclusions: For patients with COPD and lung cancer treated with ICIs, ICS use was associated with an increased risk of ICI pneumonitis at one year and a reduction in mortality, without a significant difference in risk for infection. Taken together, this study suggests that the incorporation of an ICS in the management of COPD for patients also on ICI for lung cancer may have survival benefit without an added risk of infection. However, careful consideration and vigilant monitoring are required for patients on an ICS given the increased risk of ICI pneumonitis.
Prognostic role of pre-treatment eosinophilia in NSCLC patients undergoing immune checkpoint inhibitor therapy: A meta-analysis.
Authors: Nency Ganatra, Diksha Sanjana Pasnoor, Abhijit Battar, Pragya Jain, Rachna Vashi, Swathi Nimmala, Rupak Desai, Akhil Jain
Journal: Journal of Clinical Oncology (2025)

e20620 Background: Precision management of non-small cell lung cancer (NSCLC) requires biomarkers to predict immunotherapy response. Though eosinophilia can occur as a part of immune-related adverse events, it has also been suggested as a useful simple biomarker for favorable response to immune checkpoint inhibitors (ICI). Given the sparse knowledge and data for the same, we conducted meta-analysis to examine the prognostic significance of eosinophilia in ICI-treated NSCLC patients for progression-free survival (PFS) and overall survival (OS). Methods: A systematic search of PubMed, Google Scholar, and Scopus was done to identify studies published up to 2025 to examine the prognostic value of pre-treatment eosinophilia in NSCLC patients undergoing ICIs. The random effects model was for pooled analyses. Hazard ratios and 95% confidence intervals assessed OS and PFS. Subgroup analyses were based on initial eosinophil levels, location, and treatment. Results: A total of 8 studies with 13,600 patients with a mean/median age of 65 years were included. Pre-treatment eosinophil count showed mixed associations with survival outcomes. For overall survival (OS), unadjusted hazard ratio was 0.79 (95% CI: 0.42–1.51, p=0.48, I²=82.79%), while adjusted hazard ratio was 0.74 (95% CI: 0.53–1.03, p=0.07, I²=73.31%). For progression-free survival (PFS), unadjusted hazard’s ratio was 0.78 (95% CI: 0.54–1.13, p=0.19, I²=70.21%), and adjusted hazard ratio was 0.68 (95% CI: 0.58–0.80, p&lt;0.01, I²=0%), suggesting a significant association between higher eosinophil counts and improved PFS in adjusted analyses. Excluding Takeuchi's study in leave one out sensitivity analysis, the overall odds ratio shifts slightly upward, and the confidence interval narrows, becoming statistically significant. This suggests that Takeuchi's study may have contributed to the broader confidence interval and lack of significance in the overall analysis for OS. Conclusions: Higher eosinophil count is associated with 32% reduced risk of progression. Pre-treatment eosinophilia in NSCLC patients receiving ICIs is significantly associated with improved PFS but shows a borderline association with OS. These results support eosinophilia as a potential prognostic biomarker of PFS for immunotherapy response in NSCLC.
miRNA-mRNA regulatory network analysis of tumor-associated MSCs and cancer-associated fibroblasts (CAFs) in lung cancer microenvironment.
Authors: Sharareh Seifi, Masoumeh Nomani, Babak Salimi, Adnan Khosravi, Maryam Mabani, Parsa Rostami
Journal: Journal of Clinical Oncology (2025)

e20521 Background: Cancer is a complex disease involving not only cancer cells, but also the surrounding microenvironment, which includes various cells, such as cancer-associated fibroblasts (CAFs) and mesenchymal stem cells (MSCs). These cells are essential for tumorigenesis, progression, and metastasis by interacting with cancer cells through a variety of mechanisms, such as the modulation of gene expression through microRNAs (miRNAs) and messenger RNAs (mRNAs). Identifying miRNA-mRNA network in CAFs and MSCs can show novel regulatory mechanisms for developing more effective therapeutic strategies targeting both cancer cells and their supportive microenvironment. Methods: Transcriptomics (GSE104636) and miRNA expression (GSE113805) datasets downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differential expressed miRNAs (DEMs) were identified using TAC and R software. The STRING database and Cytoscape software were employed to identify and analyze hub genes. The related target genes of DEMs were predicted using miRWalk database. Then, the target genes of DEM were overlapped with DEGs to obtain the relationships between DEMs and DEGs. MATLAB software was used to determine the gene-miRNA interactions, and the miRNA-mRNA network was visualized using Cytoscape software. Enrichr Database was used to conduct KEGG pathway enrichment analyses in order to investigate the underlying functions of all DEGs, genes in the network, and modules. Results: In this study, 1496 DEGS were identified between paired tumor- and normal tissue-associated MSCs. Utilizing the String database and cytoscape software, we identified 150 hub proteins from the microarray data through the PPI network analysis. Also, in this analysis, 110 miRNAs were detected as differentially expressed. 478 Gene target of these mirs determined by MirWalk database. The potential interactions between hub genes and DEMs were determined by analyzing DEM and hub gene data using MATLAB software. Subsequently, we constructed the miRNA-mRNA network by Cytoscape and identiﬁed several miRNAs (hsa-miR-1193; hsa-miR-1197; hsa-miR-300; hsa-miR-543; hsa-miR-544a and hsa-miR-665), genes (such as FBXO32, LSM5, MYCBP, NEMP1, FOSL2), and pathways (such as FoxO signaling pathway, PI3K-Akt signaling pathway and p53 signaling pathway). Conclusions: This investigation identified substantial modifications in the expression of genes and miRNAs in fibroblasts and mesenchymal stem cells associated with lung cancer. Our findings provide valuable insights into tumor-stromal interactions, the discovery of hub genes and important miRNAs in lung cancer.
The phase II study of pembrolizumab plus lenvatinib for patients with unresectable cutaneous angiosarcoma (Pembro-Lenva for cAS/PLAS trial).
Authors: Dai Ogata, Eiji Nakano, Takeru Funakoshi, Akira Takahashi, Jun Asai, Motoki Nakamura, Kenjiro Namikawa, Ryunosuke Machida, Masayuki Yokoyama, Haruhiko Fukuda, Yukari Nagasaka, Kazumi Kurishita, Yoshie Shuda, Kenta Anjo, Kanako Kondo, Masako Inaba, Satoshi Kawashima, Takako Hitomi, Natsuko Tsuda Okita, Naoya Yamazaki
Journal: Journal of Clinical Oncology (2025)

TPS11586 Background: Cutaneous angiosarcoma (cAS) is a rare cancer that often occurs in elderly people with common recurrence and metastasis after surgery. Chemotherapy, radiation therapy, and their combination are widely used, but their effectiveness is insufficient. With the increasing number of cAS patients due to the aging population, the development of effective treatment is urgently required. Previously, it has been reported that cancer shrank in 18% (5 out of 27) of patients after 2 months of paclitaxel administration in a clinical trial. Therefore, paclitaxel has become more commonly used for cAS. Other options include anthracycline anticancer drugs and gemcitabine. However, even with these anticancer drugs (and radiation therapy), cAS progresses quickly, and some reports have said that the 5-year survival rate is 9%. This study is planned to develop safer and more effective treatment for cAS. Pembrolizumab is an immune checkpoint inhibitor with PD-1 receptor-ligand interaction and lenvatinib is a multikinase inhibitor that inhibits tumor angiogenesis. The combination is expected to have strong therapeutic efficacy due to the immunomodulatory effects of pembrolizumab and the inhibitory effects of lenvatinib. Methods: This investigator-initiated, prospective, multicenter, non-randomized phase II trial evaluates the efficacy and safety of pembrolizumab plus lenvatinib for patients with unresectable cAS. Eligible patients are aged ≥18 years (≤85 years), histologically diagnosed with cAS, and both untreated and previously treated patients. The primary endpoint of this study is to confirm the response rate of pembrolizumab plus lenvatinib combination therapy for unresectable cAS based on RECST 1.1 at central review. The secondary endpoints are response rate (primary investigator assessment), progression-free survival, overall survival, disease control rate, duration of response, time to response, incidence of adverse events (AEs), incidence of drug-related adverse events (adverse drug reactions, ADRs), and incidence of serious AEs/ADRs. We estimated a threshold response rate of 18% and an expected response rate of 35%. The planned sample size is 38 patients (25 untreated patients and 13 treated) to provide a power of 70% with one-sided alpha of 5%. The planned accrual period is 2 years, and the follow-up period is 2 years; interim analysis will be performed at the enrollment of 20 patients is completed. The trial began in February 2025. Clinical trial information: NCT06673628 .
Impact of gut microbiota (GM) and antibiotic (ATB) use on immunotherapy efficacy in patients with lung cancer (LC): Preliminary results from a prospective trial.
Authors: Gisele Fraga Moreira, Imanuely Borchardt, Gisele Farias, Fernanda Carneiro Dias, Fernanda Telles Lins Taveira, Wilza Arantes Ferreira Peres, Tatiane Caldas Montella, Carolina Alves Costa Silva, Carlos G. M. Ferreira, Andreia Cristina De Melo
Journal: Journal of Clinical Oncology (2025)

e20610 Background: LC is the leading cause of cancer death globally. Immune checkpoint inhibitors (ICI) have changed cancer treatment, but surpass resistance is still a challenge. The GM impact cancer immune-surveillance, and it can be modulated through diet/lifestyle and comedications (such as ATB). Microbiota-based biomarkers and interventions are promising strategies to overcome ICI resistance. We conducted a prospective trial (NCT04965129) to evaluate the impact of GM and ATB in non-small cell LC (NSCLC) patients (pts) treated with ICI. Methods: Pts with NSCLC eligible for ICI were assessed by monthly pharmaceutical visits and weekly telemonitoring to record the use of comedications up to 3 months before ICI start (T0) and from T0 to 4 months post-ICI start (T4), interaction assessment and pharmacotherapeutic follow-up. GM was analyzed at T0 and T4 by 16S rRNA sequencing. Alpha diversity was assessed using Shannon, Simpson, and InvSimpson indices; beta diversity by Bray-Curtis dissimilarity and differential relative frequency analysis using the Mann-Whitney test. Treatment response was evaluated according to RECIST v1.0, considering disease control (DC) if complete response, partial response, or stable disease. Results: We included 27 pts from February 2022 to February 2024: mean age of 70,6 years ± 7,5 [SD], mostly male (59%), with two or more comorbidities (63%), and polypharmacy (74%). Overall, 37% required pharmaceutical interventions and 47% used ATB. Progressive disease (PD) occurred in 88% of ATB users versus 12% of ATB non-users. ATB users and non-users did not differ in alpha or beta diversity. Clostridium difficile was detected in 75% of ATB users versus 0% non-ATB users. The relative frequency analysis brought up 8 species that significantly changed (p&lt;0.05) between T0 and T4 among ATB users, including the pro- inflammatory Bacteroides clarus and Prevotella spp. Inversely, ATB non-users lost oral taxa Streptococcus spp. and gained the health-related Alistipes finegoldii . 81 species differed significantly between PD and DC (p&lt;0.05) pts. All DC pts were positive for Akkermansia muciniphila versus 33% in PD pts, and they were enriched with health-related Lachnospiraceae (Roseburia spp., Blautia spp.) and Alistipes spp. Bacteroides caccae (p=0.035) and Prevotella copri (p=0.045) were present at TO and T4 in all patients. Conclusions: ATB use is associated to PD and pro-inflammatory taxa. Our study is a pioneer in the evaluation of Brazilian pts with LC treated with ICI. We contribute to equity and diversity in GM research towards more robust biomarkers for precision medicine. Clinical trial information: NCT04965129 .
Circulating free DNA derived from active chromatin as a predictive biomarker for clinical benefit to checkpoint inhibitor-based therapies in metastatic leiomyosarcoma.
Authors: Carlos Diego Holanda Lopes, Hsin-Ta Wu, Abdulazeez Salawu, Lee-Anne Stayner, Katharine Dilger, Abha A. Gupta, Aaron Richard Hansen, Anna Spreafico, Philippe Bedard, Maggie C Louie, Lillian L. Siu, Albiruni Ryan Abdul Razak
Journal: Journal of Clinical Oncology (2025)

11539 Background: Leiomyosarcoma (LMS) is a common subtype of soft tissue sarcoma with a poor prognosis in the metastatic setting. LMS shows minimal benefit from monotherapy immune checkpoint inhibitors (CPI), however combinatorial CPI strategies may be effective in part due to tumor enrichment of epigenetic alterations. The DAPPER trial (NCT03851614) was a randomized, single center phase II study of durvalumab combined with olaparib or cediranib. Of the 30 LMS patients enrolled, 36.3% (n = 11) experienced disease stabilization or shrinkage. The present study aims to leverage a novel active chromatin cell-free DNA (cfDNA ac ) platform to investigate the epigenetic and genomic profiles of LMS patients in the DAPPER trial, with the goal of identifying biomarkers associated with clinical benefit from CPI-based therapies. Methods: Baseline plasma samples (n = 30) from LMS patients in the DAPPER trial were processed using a proprietary cfDNA ac capture assay that enriches active chromatin cfDNA. Following whole genome sequencing, univariate analysis and machine learning-based recursive feature selection were used to identify genomic features associated with clinical benefit rate (CBR, defined as RECIST v1.1 complete or partial response, or stable disease lasting &gt; 6 months). Results: We identified 918 promoter and exon features that were significantly different (p &lt; 0.01) at baseline and could segregate patients who achieved CBR from those who did not. Over-representation analysis of these gene features using Gene Ontology (p adj &lt; 0.05) showed enrichment in biological pathways associated with double-strand break repair, inflammatory response, and immune response - specifically T-cell receptor activation and signaling, and macrophage homeostasis in patients with CBR. Conclusions: This study highlights the utility of cfDNA ac profiling as a non-invasive method for identifying biomarkers that predict clinical benefit from CPI-based therapy in patients with advanced LMS. Further analyses are ongoing to evaluate whether the genomic-derived features correlate with other clinical outcomes, such as progression-free survival, overall survival, and orthogonal data (e.g. tumor tissue RNA-seq).