bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical validation of an activity-based enzyme assay for early stage lung cancer.
Authors: Dempsey Paul W. , Aparicio Cristina-Mihaela Sandu , Gonzalezirias Ricardo , Hantula Spencer , Kagawa Mari , Bossmann Stefan H. , Covarrubias-Zambrano Obdulia , Nagji Alykhan S. , Veeramachaneni Nirmal K , Ermerak Nezih O. , Kocakaya Derya , Lacin Tunc , Yildizeli Bedrettin , Witting Christensen Wen Sara , Nederby Line , Hansen Torben , Hilberg Ole 
Published: June 2023

8533 Background: The USPSTF guidelines recommend annual LDCT scans for 15.5 million adults with a heavy smoking history. While LDCT can reduce deaths by 20%, screening compliance remains low. A blood test with clinically useful, cost effective performance could improve compliance and access when integrated with the standard of care. We describe here a lyophilized nanosensor system for detecting protease enzyme activity in sera with clinically useful diagnostic activity in early stage lung cancer. We evaluated the performance of the assay by examination of prospectively collected sera for detection of cancer in high risk patients. Methods: Sera were obtained in multiple independent studies to include pathologically confirmed, treatment naive lung cancer patients and LDCT confirmed negative individuals. Protease activity was measured on 18 different nanosensors built with protease targets mainly selective for members of the Matrix Metalloproteinase and Cathepsin families. Lyophilized plates were incubated with serum and enzyme activity was measured indirectly as a continuous variable by a fluorescent plate reader. A machine learning modeling tool (Emerge) was used to detect signal associated with a cancer “fingerprint” of protease activity. The analysis stratified allocation into training and testing sets of 250 samples each and reserved a third out of sample validation set (250 samples) for reporting. Results: 750 clinical samples included 30% lung cancers, 63% males, 91% smokers, and an average age of 63 years (SD=9). Cancer cases were distributed across stages I (41%), II (17%), III (20%) and IV (20%) with 5% unknown. Histological classification included 59% adenocarcinoma, 31% squamous cell and 11% other subtypes. Using an Emerge model with only nanosensor activity and gender as inputs, we evolved a balanced algorithm. The algorithm can be further modified to favor sensitivity or specificity depending on the application by applying model weighting factors. We report the performance observed in the 250 out of sample validation set at three points on this spectrum (Table). Among Stage I cancer samples, the balanced algorithm had an accuracy of 90% (26/29). Conclusions: Current LDCT tools show low compliance. We demonstrate clinical validity of a cost effective tool to detect lung cancer in support of LDCT screening. Based on a simple blood sample, the current test may predict early stage lung cancer with an accuracy of 90%. The performance suggests applications in LDCT compliance, post LDCT management, and eventually screening. A clinically validated version of this technology is being evaluated as a triage tool for LDCT screening. [Table: see text]
Validation of recurrence prediction using circulating tumor DNA in patients with curatively treated early stage non-small cell lung cancer.
Authors: Schuurbiers Milou , Smith Christopher Gareth , Hartemink Koen , Rintoul Robert , Monkhorst Kim , van den Broek Daan , Rosenfeld Nitzan , Heuvel Michel van den 
Published: June 2023

8535 Background: Stage II-III non-small cell lung cancer (NSCLC) patients receive adjuvant chemotherapy after surgery as standard-of-care treatment, despite an absolute 5-year disease free survival benefit of only 5.8%. Stage I patients do not receive adjuvant treatment but may benefit. Identification of residual disease by circulating tumor DNA (ctDNA) after curative intent therapy may allow more accurate decisions. Methods: Tumor tissue and serial plasma samples were collected from stage I-III NSCLC patients enrolled in the LEMA trial (NCT02894853). Somatic mutations identified by tumor exome sequencing were used to design patient-specific RaDaR assays, targeting up to 48 variants per patient, to analyze ctDNA in serial plasma samples. Results were compared and combined with an independent dataset (LUCID; Gale et al, Annals Oncol 2022). Results: In LEMA, 129 patients (53% stage I, 18% stage II and 29% stage III) were treated with curative intent by surgery (n=117), chemoradiation (n=8) or stereotactic radiotherapy (n=4) and followed for a median of 3.4 years. The LUCID dataset included 88 patients (49%/28%/23% in stage I/II/III). Results in the two cohorts were highly concordant (Table) and were assessed in the combined dataset of 808 serial plasma samples. Before treatment, ctDNA was detected in 22%, 72% and 90% of patients with stage I, II and III disease. ctDNA was detected post-treatment (at least one positive samples ≥14 days after the end of therapy) in 41/65 (63%) of patients who developed radiographic recurrence of their primary cancer, and preceded recurrence by a median of 204 days. For recurrence prediction by ctDNA detection post-treatment, the sensitivity, specificity, positive and negative predictive value (PPV and NPV) in stage I patients were 53%, 99%, 91% and 90%. In stage II-III patients, sensitivity was higher but specificity and NPV were lower (67%, 93%, 91% and 74%, respectively). ctDNA detection after treatment was associated with shorter recurrence-free survival (hazard ratio (HR) 11.5, P=1.8x10-32) and overall survival (HR 8.1, P=1.2x10-17). Conclusions: ctDNA detection by RaDaR assays predicted recurrence in two independent cohorts, confirming the potential to identify patients for adjuvant treatment. In stage I patients with positive ctDNA, adjuvant treatment could be offered with confidence due to high specificity of 99% and PPV of 91%. In stage II-III patients, the primary cancer recurred in a quarter of patients with no ctDNA detected post-treatment (NPV 74%). Our results help identify the potential role for ctDNA analysis as a decision support tool for adjuvant therapy in NSCLC. [Table: see text]
EGFR assessment using next generation sequencing as a reflex testing on surgically resected non-squamous non-small cell lung carcinoma.
Authors: Goffinet Samantha , Hofman Veronique , Bontoux Christophe , Benzaquen Jonathan , Cohen Charlotte , Marquette Charles-Hugo , Berthet Jean-Philippe , Ilie Marius , Hofman Paul 
Published: June 2023

8539 Background: EGFR status assessment is mandatory in early stage (IB-IIIA) non-squamous non-small cell lung carcinoma (NS-NSCLC), but whether NGS methods should be used as reflex testing for this evaluation in daily practice is controversial. However, co-occuring mutations, notably TP53 mutations, may have an impact on tumor behavior and prognosis, and so, on future adjuvant therapeutic strategies. Methods: EGFR mutations were assessed prospectively using NGS (Oncomine Precision Assay genes panel) in 720 NS-NSCLC surgically resected between January 2021 and September 2022 in a single institution (LPCE, Nice, France). PD-L1 expression was evaluated in all tumors. Disease free survival (DFS) analysis was available in 675/720 (94%) patients. Results: EGFR mutations were detected in 83/720 (11.5%) cases. A common non-compound EGFR mutation (L858R or del19) was observed in 62/83 (75%) cases. 12/83 (14%) and 9/83 (11%) tumors had a rare non-compound and compound EGFR mutations, respectively. 40/83 (48%) has a co-occuring mutation, including a TP53 (30/40; 75%) mutation, mainly in exon 5, 7 or 8. EGFR/TP53 mutated tumors were significantly associated with higher PD-L1 expression compared to EGFR mutated tumors. A significant correlation was noted between worse DFS and the detection of a mutation in EGFR exon 18 mutation, as well as the detection of a co-mutation in TP53 exon 7 and in MET exon 14. Conclusions: Genomic alteration should be systematically evaluated using an NGS reflex testing in surgically resected NS-NSCLC, since future adjuvant therapeutic decision making may consider the presence of compound EGFR mutations as well as co-occuring mutations in other genes, especially in TP53.
Association of nuclear shape in the tumor epithelium with response to atezolizumab in NSCLC.
Authors: Leo Patrick , Patil Namrata Srivastava , Ruderman Daniel , Giltnane Jennifer M. , Fuentes Eloisa , Schedlbauer Amber , Nabet Barzin , Kozlowski Cleopatra 
Published: June 2023

8543 Background: Anti-PD-(L)1 treatment is the standard of care for advanced non-small cell lung cancer (NSCLC). However, additional biomarkers are needed to identify patients who will benefit from these therapies. In this study, we demonstrate the atezolizumab response score (ARS), which uses digital pathology features of the shape and size of nuclei in the tumor epithelium to predict response to the anti-PD-L1 antibody atezolizumab in NSCLC. Methods: Patients were drawn from two trials comparing atezolizumab to docetaxel in second-line advanced NSCLC. A single digitized slide stained for the epithelial cell marker pan-cytokeratin (CK) and CD8 was selected for each patient. OAK, a phase III trial, had 819 patients with images available and was used for training the ARS model. POPLAR, the phase II trial preceding OAK, had 168 evaluable patient images for validating ARS. Color deconvolution was used to identify the CK-positive regions in each image. Nuclei were segmented using the hematoxylin channel. The area, perimeter, eccentricity, solidity, and minor/major axis lengths were extracted from each nucleus in the CK-positive compartment of the pathologist-annotated tumor lesion, excluding necrosis and artifacts. Each measure’s mean, median, standard deviation, skewness, and kurtosis across the slide was calculated, for a total of 30 features. Features with an interaction p< 0.35 with trial arm in a Cox model were used to fit an elastic-net regularized Cox model on the atezolizumab-treated training set patients, producing ARS. The ARS threshold maximizing atezolizumab overall survival (OS) benefit in the ARS-high group was identified in OAK and applied to POPLAR (the validation set). ARS performance was assessed in the validation set by OS concordance index (c-index) and by atezolizumab benefit in the high- vs. low-ARS groups by hazard ratio (HR) [95% confidence interval]. Results: ARS employs five features. Lower nuclear median and standard deviation of major axis length, higher perimeter mean and standard deviation, and higher area were associated with better atezolizumab response. In the validation set, high-ARS (prevalence = 42%) patients had longer OS on atezolizumab vs. docetaxel (HR = 0.42 [0.24-0.72]) while low-ARS patients did not (HR = 0.95 [0.62-1.47]). ARS was positively associated with OS in the validation set atezolizumab arm (c-index = 0.60 [0.54-0.66]), but not the docetaxel arm (c-index = 0.47 [0.41-0.54]). Conclusions: We validated a nuclear morphology-based biomarker for atezolizumab response in advanced NSCLC. This demonstrates the utility of digital pathology for biomarker development and motivates study into the identified responder phenotype. Combination of ARS with additional markers, such as PD-L1 expression, might further improve stratification.
A systematic comparison of whole genome sequencing and targeted panel sequencing for precision oncology.
Authors: Park Ji-Hyung , Connolly-Strong Erin , Kim Young Tae , Ju Young Seok 
Published: June 2023

8546 Background: The analysis of the cancer genome provides clinically meaningful information such as actionable cancer driver mutations. Whole genome sequencing (WGS) provides a complete mutational landscape at an affordable cost thereby having increase clinical utility compared to the usual approach of targeted panel sequencing (TPS). To understand the capabilities of WGS in oncology, we conducted a study in lung adenocarcinomas. Methods: We produced WGS (surgically resected tumor tissues and matched blood; mean coverage 42x) and TPS (tumor only; SNUH panel encompassing 75 cancer genes; mean coverage 904x) through the Illumina sequencing platform and conducted comprehensive bioinformatic analyses. Oncogenic driver events, including single base substitution (SBS), insertion or deletion (INDEL), complex deletion-insertion, and fusion oncogene, were investigated in both datasets. Lastly, we compared the pattern-based mutational features, such as tumor mutational burden (TMB), mutational signatures, and copy number changes which is associated with genomic instability. Results: In 60 lung adenocarcinomas, the TPS method identified 120 driver mutations from the 75 targeted genes. Of these, 114 mutations were also detected by the WGS method, showing 95.0% sensitivity of WGS in detection of core driver mutations. In uncovered genomic regions by TPS, WGS captured 9 additional driver mutations (such as loss-of-function mutations in PIK3R2, ARID2, and APC) and 37 copy number variations (such as amplification of LMO and SMO, deletion of PIK3R1 and APC) in the cancer genes. TMB calculation is straightforward in WGS however, sophisticated considerations were necessary in TPS for TMB, to remove false positives and germline mutations. TPS showed a good capability for identifying hypermutator tumor samples, but a quantitative estimation was not always feasible due to the substantial background fluctuation, particularly for INDELs. Mutational signatures are unique combinations of mutation types in a given sample, which can give important clues to the mechanism underlying mutations. TPS showed adequate mutational signatures (cosine similarity > 0.7), but was not constantly satisfactory in tumors with high TMB ( > 20,000 genome wide SBS and INDELs). In TPS, approximately 30% of high TMB tumors represented marginal cosine similarity (0.5-0.7), and tobacco smoking related signature (SBS 4) found in WGS was captured only in 50% of the associated cases (9 out of 18). For DNA copy number changes and loss-of-heterozygosity analyses, WGS showed a much higher resolution. Conclusions: Our study demonstrates that WGS has comparable capabilities for the detection of driver mutations in core oncogenes and tumor suppressor genes. WGS was superior for pattern-based features, such as TMB, mutational signatures, and copy number changes. WGS is a medically necessary more comprehensive approach to precision oncology.
Prospective dynamic sampling and molecular residual disease monitoring to predict clinical outcomes for patients with unresectable, locally advanced non-small cell lung cancer undergoing radical radiotherapy.
Authors: Zhang Jia-Tao , Pan Yi , Gao Xuan , Chen Zhi-yong , Yan Bingfa , Tan Pei-Xin , Yang Xiao-Rong , Lin Hui , Yan Hong-Hong , Dong Song , Wang Bin-Chao , Yang Jin-Ji , Tu Hai-Yan , Yang Xue-Ning , Zhong Wenzhao , Xia Xuefeng , Yi Xin , Zhou Qing , Wu Yi-Long 
Published: June 2023

8549 Background: The role of molecular residual disease (MRD) detection in non-small cell lung cancer (NSCLC) patients after definitive resection has been progressively elaborated. However, the dynamic patterns of circulating tumor DNA (ctDNA) during and after radical radiotherapy (RT) remain unclear but are critical for detecting MRD in this context. Methods: We enrolled 139 patients with locally advanced NSCLC treated with radical RT in this prospective study. And 761 blood samples were successfully detected by ctDNA-MRD assay at different preset timepoints before, during and after RT. Results: There was a declining trend in ctDNA concentrations of “during RT” time point (RT reached 40 Gy) relative to those after RT. Patients with negative ctDNA of “during RT” and “after RT” time points may indicate an early response to RT, and had better progression-free survival (PFS) than those with late response to RT(ctDNA clearance only at “after RT” time point, HR = 0.30, 95%CI: 0.12-0.75, p = 0.004). Moreover, patients with both negative ctDNA of “during RT” and “after RT” time points could not benefit from consolidation therapy (HR = 0.72, 95%CI: 0.29-1.78, p = 0.478), while patients with any positive ctDNA of them could (HR = 0.59, 95%CI: 0.38-0.93, p = 0.023).The sensitivity of longitudinal MRD was 97.8% and only two patients with local progression were overlooked. The 2-year cancer-specific PFS of patients with longitudinal undetectable MRD was 88.4%, which corresponds to the potentially cured population. For patients with only blood-informed MRD detection, the sensitivity and median lead time of longitudinal MRD were 97.7% and 3.9 months, respectively, which indicating the feasibility and efficacy of blood-informed MRD detection strategy. Conclusions: These data shed new light on the ctDNA-MRD detection for localized NSCLC patients who received radical RT.
Assessing the efficacy and safety of DEB-BACE combined with intravenous chemotherapy for the treatment of intermediate to advanced lung adenocarcinoma after progression of targeted drug resistance.
Authors: Lai Lingqiang , Tu Jianfei , Zhang Dengke , Ying Xihui , Wu Jiahao , Chen Jie , Chen Li 
Published: June 2023

8555 Background: To compare the efficacy and safety of drug-eluting bead bronchial arterial chemoembolization (DEB-BACE) combined with intravenous chemotherapy versus systemic intravenous chemotherapy for intermediate to advanced lung adenocarcinoma with positive driver genes after progression of targeted therapy. Methods: A total of 131 patients with intermediate to advanced lung adenocarcinoma were retrospectively recruited from 2018-2022 and divided into Group A (standard chemotherapy regimen, N=62) and Group B (DEB-BACE and intravenous chemotherapy, N=69). The short-term efficacy, hemoptysis remission rate, dyspnea remission rate, and incidence of adverse effects were compared between the two groups using the χ2 test. Survival estimates were performed by Kaplan-Meier, and a Log-rank test was performed to examine survival differences between groups. Results: The three-month disease control rate (DCR: 82.6% vs 58.1%) and objective remission rate (ORR: 60.9% vs 38.7%) were better in group B than in group A (both P<0.05). Median progression-free survival (PFS, 10.0 vs 7.9 months) and median overall survival (OS, 33.0 vs 18.0 months) were better in group B than in group A (both P < 0.05). The PFS rates at 6, 12, and 24 months were 67.3%, 40.8%, and 0.0% and 54.1%, 23.2%, and 0.0% in groups B and A, respectively; and the OS rates at 6, 12, and 24 months were 100%, 95.7%, 72%, 88.6%, 66.1%, and 21.8% in group B and group A, respectively, with statistically significant differences (P < 0.05). Within one month after treatment, group B had better hemoptysis relief (83.3% vs. 20.0%) and dyspnea relief (57.5% vs. 30.0%) than group A (both P < 0.05). During the follow-up period, the incidence of adverse reactions was significantly lower in group B than in group A (P < 0.05). Conclusions: For patients with intermediate to advanced lung adenocarcinoma who have failed to progress on targeted therapy, DEB-BACE combined with intravenous chemotherapy has shown superior efficacy and survival benefit and lower adverse effects, while significantly improving patients' symptoms of hemoptysis and dyspnea, with important application prospects.
Development and validation of a prediction model for the recurrence of stage 1 EGFR mutation positive NSCLC in patients using machine learning with WES-based gene sets.
Authors: Tateishi Akiko , Horinouchi Hidehito , Takasawa Ken , Kouno Nobuji , Mizuno Takaaki , Okubo Yu , Yoshida Yukihiro , Watanabe Shun-ichi , Miyake Mototaka , Kusumoto Masahiko , Inaba Koji , Igaki Hiroshi , Yatabe Yasushi , Mukai Masami , Tanaka Katsuya , Mihara Naoki , Shiraishi Kouya , Kohno Takashi , Ohe Yuichiro , Hamamoto Ryuji 
Published: June 2023

8563 Background: Predicting the risk of postoperative recurrence is becoming increasingly important in EGFR mutation positive ( EGFR-m) non-small cell lung cancer (NSCLC). Only a few reports conducted whole exome sequencing (WES) for genomic profiling in large scale EGFR-m NSCLC cases. Methods: We conducted WES and analyzed the clinical course of patients (pts) with NSCLC who underwent surgery between 1985 and 2019 in the PRISM project of our institute. We evaluated the EGFR-m patients’ characteristics, recurrence-free survival (RFS), and developed a prediction model using machine learning, Overlapping Group LASSO to predict whether the EGFR-m patients will recur within 5 years or not as "high-risk" and "low-risk". To develop and validate the prediction model, we divided the data from 2006 as the training cohort data set and the data before 2006 as the validation cohort data set. After the development of the prediction model, we performed a stratified Cox proportional hazards model to compare the RFS between the predicted groups. Results: A total of 585/1351(43.3%) pts were EGFR-m included in the PRISM project. Of all pts, stage I, EGFR-m were 205 pts. The median RFS of the stage I, EGFR-m 123.1 months (m). In the training cohort, the model detected 43 pts for high-risk and 88 pts for low-risk. In the validation cohort, the model predicted 29 pts for high-risk and 45 pts for low-risk. Median RFS of high-risk vs. low-risk were 52.2 m vs. 105 m (HR 2.43, p=0.01). The 1-year RFS rate, 2-year RFS rate, and 5-year RFS rates for high-risk and low-risk pts were 100% vs. 98.5%, 66.7% vs. 89.2%, and 41.7% vs. 66.1%, respectively. Twenty-eight gene set coefficients were non-zero in the prediction model. The gene sets with large positive coefficients that were considered important for prediction as "high risk" were the gene sets affected by KRAS gene overexpression and p53 gene knockdown. In contrast, gene sets repressed by mTOR inhibition and genes repressed by TBK1 gene knockdown and KRAS gene overexpression had large negative coefficients. Conclusions: We developed and validated the prediction model whether the EGFR-m patients will recur within 5 years or not. EGFR-m NSCLC recurrence appears to be high risk with pathways associated with KRAS and p53 genes, and low risk with mutations in the gene sets suppressed by the mTOR pathway and TBK1 gene. [Table: see text]