bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal circulating tumor DNA monitoring in patients with esophageal squamous cell carcinoma.
Authors: Takei Shogo , Kotani Daisuke , Sato Kazuma , Fujiwara Naoto , Kawazoe Akihito , Sharma Shruti , Spickard Erik , Dutta Punashi , Liu Minetta C. , Jurdi Adham A , Shitara Kohei , Kojima Takashi , Fujita Takeo 
Published: June 2023

3041 Background: The clinical utility of longitudinal monitoring with circulating tumor DNA (ctDNA) as a prognostic and a predictive biomarker was recently reported in patients with resectable colorectal cancer (Kotani D, et al. Nature Medicine 2023). Here we report a prospective, observational study of longitudinal ctDNA monitoring in patients with esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant chemotherapy (NAC) followed by surgery. Methods: Patients with ESCC planned for NAC followed by curative surgery, were prospectively enrolled in this study. As per the protocol, plasma samples were collected at 7 timepoints: pre-NAC, post-NAC, and 4,12, 24, 36, and 48-weeks after surgery. CT scans were conducted every 3 months. Longitudinal ctDNA testing was performed using a personalized, tumor-informed ctDNA assay (Signatera, bespoke mPCR, NGS assay). In this initial report, ctDNA results at 3 time points (pre-NAC, post-NAC, and 4 weeks post-surgery) were analyzed and their association with clinical outcomes and tumor regression grade (TRG) scores were assessed. Results: So far, a total of 83 blood samples from 28 patients with ESCC were collected serially at pre-NAC (N=28), post-NAC (N=27), and post-surgical (N=28) time points. Pre-NAC ctDNA was detectable in 96.4% patients (27/28), and detection rates decreased at the post-NAC (37%; 10/27) and post-surgical (11%; 3/28) timepoints. ctDNA-positivity post-NAC and post-surgery was associated with a significantly shorter recurrence free survival (RFS) with HR of 7.0 (95% CI: 1.4-35.0; p = 0.02) and HR of 14 (95% Cl 3.0-62; p <0.001), respectively. Notably, patients who achieved ctDNA clearance with NAC had favorable RFS as compared to the patients who did not (HR=0.15, 95% CI: 0.03 – 0.75; p = 0.02). Post-NAC ctDNA was also associated with tumor regression grade (TRG) score. None of the patients with TRG3 score (N=3) were ctDNA positive, whereas 7.7% (1/13) patients in the TRG2 category and 81.8% (9/11) in the TRG1 category were ctDNA-positive. Conclusions: Our study demonstrates a strong correlation between ctDNA status and clinical outcomes in ESCC patients. Assessment of ctDNA may be useful monitoring in patients with ESCC post NAC/surgery and may be used in the future to direct post-surgical management in this patient population. Clinical trial information: UMIN000042003 .
A 5-hydroxymethylcytosine-based noninvasive model for ultrasensitive early detection of colorectal advanced adenoma and adenocarcinoma: The METHOD-2 study.
Authors: Xu Jianmin , Chang Wenju , Jia Baoqing , Ding Kefeng , Pan Zhizhong , Zhang Wei , Su Guoqiang , Zhang Wei , Ren Li , He Chuan 
Published: June 2023

3042 Background: Detection of colorectal tumors at a time when there are more treatment options is associated with better outcomes. This prospective case-control study (NCT03676075) assessed the performance of 5-hydroxymethycytosine (5hmC) biomarkers in circulating cell-free DNA (cfDNA) to detect advanced colorectal adenomas (ADA) or adenocarcinomas (CRC). Methods: This multi-center study enrolled 2,576 participants, including patients with newly diagnosed CRC (n=1,074), ADA (n=356), other solid tumors (n=80), and healthy individuals (HEA) (n=1,066), followed by genome-wide 5hmC profiling using the 5hmC-Seal, a highly sensitive chemical labeling approach. A weighted diagnostic model for CRC (stage I-III) and ADA was developed using the elastic net regularization in a training set of age-, sex-, region-matched samples and validated in independent samples. Results: Distribution of 5hmC in cfDNA reflected gene regulatory relevance and tissue of origin. In an independent validation set of 482 samples, a 96-gene model trained in stage I-III CRC, ADA, and HEA achieved an AUC (area under the curve) of 92.6% (95% CI [confidence interval], 90.7-94.5%) for distinguishing CRC from HEA, regardless of primary location or mutation. This model also showed high capacity for distinguishing ADA from HEA with an AUC of 87.9% as well as cancer-type specificity. Model performance was further confirmed in samples from multiple centers. Functionally, differential 5hmC features associated with CRC and ADA demonstrated relevance to CRC biology, including pathways such as calcium and MAPK signaling. Conclusions: Genome-wide mapping of 5hmC in cfDNA shows promise as a highly sensitive and specific approach to be integrated in a screening program for improving early detection of CRC and high-risk ADA. Clinical trial information: NCT03676075 .
Distinguishing between cancer-related mutations and clonal hematopoiesis using cell-free RNA (cfRNA) expression levels in a machine learning model.
Authors: Albitar Maher , Zhang Hong , Ip Andrew , Estella Jeffrey , Charifa Ahmad , Ma Wanlong , Mohtashamian Arash , Gutierrez Martin , Pecora Andrew L , Goy Andre 
Published: June 2023

3043 Background: Liquid biopsy is currently considered an important part of the clinical practice of oncology. However, proper interpretation of somatic mutations detected in liquid biopsy remains a challenge. Distinguishing cancer-related mutations from mutations resulting from clonal hematopoiesis of indeterminate potential (CHIP) can be difficult and a source of misinterpretation of liquid biopsy findings. We explored using cell-free RNA (cfRNA) profiling as a means for distinguishing between mutations detected as CHIP vs mutations detected as cancer. Methods: cfDNA and cfRNA from 102 patients with confirmed solid tumors, 93 patients with hematologic neoplasms and 40 patients with CHIP abnormalities were sequenced using a panel of 1501 gene for RNA and 284 genes for DNA. The solid tumors included lung, breast, ovarian, and colorectal. The hematologic neoplasms included lymphoid and myeloid neoplasms. Using a machine learning algorithm, we first selected the relative genes that distinguish between two classes using K-fold cross-validation (K=12). The selected genes were used to predict one class from the other using naïve Bayesian classifier, but we applied geometric mean naïve Bayesian (GMNB) to compensate for the expected underflow. Results: Using machine learning with cfRNA, we were able to distinguish between cases with confirmed cancer-related mutations and CHIP mutations with area under the curve (AUC) of 0.808 (95% CI: 0.720-0.895). Precision, recall and f1-score were 0.86, 0.422 and 0.566 for CHIP and 0.359, 0.825 and 0.500 for solid tumor, respectively. The machine learning required 70 genes for this classification. Leave-one-out (LOO) validation showed AUC of 0.766 (95% CI: 0.671-0.859). Distinguishing between hematologic neoplasms and CHIP was achievable using the expression of 30 genes. The AUC for this model was 0.787 (95% CI: 0.696-0.879). Precision, recall and f1-score were 0.906, 0.516, and 0.658 for CHIP and 0.438, 0.875, and 0.583 for hematologic neoplasms, respectively. Validation using LOO showed AUC of 0.736 (95% CI : 0.638-0.835). The top 10 genes that their expression was critical for distinguishing between CHIP and solid tumors were EIF4E, HNF1A, HOOK3, HIPK2, IL1RAP, BRAF, DNAJB1, GADD45B, H2AX, and HDAC6. The top 10 genes for distinguishing hematologic cancers from CHIP were PBX1, CAMTA1, PFDN5, PCBP1, SDC4, PRKACA, NT5C2, NBR1, RPS21, and AHCYL1. Conclusions: Analyzing cfRNA expression levels when used with machine learning may add another level of confidence to the ability of interpreting mutations detected in liquid biopsy testing, especially when these mutations are at low levels. This is particularly important in liquid biopsy testing for minimal residual disease (MRD) when a tissue baseline sample is not tested (tumor-agnostic).
Pan-cancer detection and tissue-of-origin identification by whole-genome sequencing of plasma cell-free DNA.
Authors: Guo Wei , Wang Wei , Zhou Yanqing , An Heng , Lv Yanhua , Yang Zuoquan , Lu Chao , Zhang Xiaoni , Xu Mingyan , Chen Shifu 
Published: June 2023

3055 Background: Despite notable advances in cancer therapeutics, much of the mortality of human cancers results from late diagnosis. The early detection of cancer remains an unmet need that can benefit the effective treatments and better prognosis. Cell-free DNA (cfDNA) in the circulation provides an emerging diagnostic method for non-invasive cancer screening. The fragmentation signatures of cfDNA originating from different cell types or malignancies display distinct patterns, suggesting the potential as cancer biomarkers. This study aims to investigate the fragmentation profiles of cfDNA in several cancer types, and to develop a new approach for pan-cancer detection and tissue-of-origin identification. Methods: Plasma samples from 739 patients with lung (N=577), colorectal (N=98), breast (N=51) and liver (N=13) cancers, as well as 716 healthy individuals were collected in this study. Cell-free DNA was isolated and used to generate the whole-genome sequencing data. We developed an approach called PatternWGS (Pan-cancer detection and tissue-of-origin identification by whole-genome sequencing) to analyze the DNA fragmentation patterns comprehensively. Fragmentation features integrating cfDNA fragment size distribution, frequency of end motif sequence, and copy number variation were utilized to construct the optimal prediction model. We presented a multi-cancer detection model for distinguishing individuals with and without cancer using Generalized Linear Models (glmnet), and further built a cancer-origin model to predict cancer types using Random Forest algorithm. Training and testing occurred on randomly selected sampling splits of 60% and 40% of the data, respectively. Features selection and model construction were performed by only training cohort, and the test set was solely used for performance evaluation. Results: A larger proportion of shorter cfDNA fragments in cancers was observed. We proposed a fragment score indicating the degree of short fragmentation, and this fragment score was significantly higher in cancers (p<0.001). Several end motifs were identified to be specifically enriched in cancer patients. The multi-cancer detection model reached an area under the curve (AUC) of 0.98, with the sensitivity of 93% at 95% specificity. The sensitivity of detecting lung, colorectal, breast, and liver cancers reached 94.2%, 87%, 100% and 100% respectively, at 95% specificity. The cancer-origin model demonstrated an overall accuracy of 81.7% for the identification of tissue of origin. Conclusions: Our prediction model demonstrated a superior performance for multi-cancer detection and cancer origin prediction, suggesting the potential of plasma cfDNA fragmentation signatures as non-invasive biomarkers for early cancer detection in clinical. The distinct fragmentation patterns in cancer provide new insight to understand the mechanism of tumorigenesis.
Clonal hematopoiesis (CH) associated mutations in patients with advanced solid tumors enrolled in phase I clinical trials.
Authors: Rodriguez Julieta , Bayle Arnaud , Pages Arnaud , Danlos Francois-Xavier , Vasseur Damien , Rouleau Etienne , Lacroix Ludovic , Alonso de Castro Beatriz , Goldschmidt Vincent , Seknazi Lauren , Hollebecque Antoine , Michot Jean-Marie , Champiat Stephane , Marabelle Aurelien , Ouali Kaissa , Marzac Christophe , Ponce Aix Santiago , Italiano Antoine , Micol Jean Baptiste , Baldini Capucine 
Published: June 2023

3056 Background: An increased number of CH associated mutations has been identified in patients (pts) with solid tumors. Their impact on pts outcomes remains unclear. This study aims to integrate molecular data and clinical characteristics of CH in pts enrolled phase I clinical trials. Methods: Data was collected retrospectively from medical records and molecular profile reports (Foundation One Liquid CDx Assay – 309 genes) performed before first study drug administration at the Drug Development department in Gustave Roussy (Villejuif, France) within the STING trial (NCT04932525). CH prevalence was assessed according to a variant allele frequency (VAF) threshold of 1% in epigenetic modifiers ( DNMT3A, TET2 and ASXL1). Results: From January 2021 to December 2022, 255 pts were enrolled in a phase I clinical trial and had a liquid biopsy. In total, 55% of patients were male with a median age of 62 years [24-86]. Most common tumor locations were gastrointestinal (27%), genitourinary (21%) and thorax (18%). Patients received a median of 2 prior lines of treatment before investigational study drug and CH assessment. At the end of the data cut off, 81% of pts discontinued phase I treatment mostly due to progression disease. Overall, 104 pts (41%) had at least 1 CH mutation in liquid biopsy at baseline with 55 pts (22%) at a VAF of ³ 1%. Mutation frequency was DNMT3A in 42% (n= 23), ASXL1 in 38% (n=21) and TET2 in 31% (n=17). Co-mutations were present in 26 patients, with the most frequent being DNMT3A + ASXL1. Median PFS and OS were 3.7 months (m) for CH group vs 3.5m for no-CH (p=0.3) and 24m CH vs 15m no-CH (p=0.5), respectively. Conclusions: CH is commonly found in pts with solid tumors treated in phase I trials, with a prevalence in our cohort of 22%. Most frequent mutated gene was DNMT3A. Prognostic implications of the impact of these mutations in patient´s outcomes remain to be elucidated and will be presented at the meeting.
68Ga-FAPI-46 PET for cancer imaging: A prospective single-arm clinical trial.
Authors: Fendler Wolfgang P. , Bartel Timo , Pabst Kim M. , Hamacher Rainer , Hirmas Nader , Seifert Robert , Kasper Stefan , Nader Michael , Kesch Claudia , von Tresckow Bastian , Berliner Christoph , Kuemmel Sherko , Harter Philipp , Reinacher-Schick Anke C. , Lugnier Celine , Uhl Waldemar , Hadaschik Boris A. , Siveke Jens T. , Grünwald Viktor , Herrmann Ken 
Published: June 2023

3064 Background: Fibroblast activation protein (FAP) is expressed at high levels on tumor associated fibroblasts. FAP-directed radioligand positron-emission-tomography (FAP-PET) is a novel diagnostic tool for cancer. However, we currently do not understand the diagnostic performance of FAP-PET as compared to standard FDG-PET. Here we aim to compare tumor detection by FDG- vs. FAP-PET with independent validation of discrepant findings. Methods: Patients with (a) proven or suspected malignancy, (b) longest tumor diameter >1 cm, (c) intended surgery or biopsy, and (d) no prior external beam radiation or systemic tumor therapy within 3 months underwent FDG- and FAP-PET for tumor localization on subsequent days. Clinical reads were analyzed prospectively on a per-patient and per-region basis (local, locoregional nodal, distant organ or soft tissue, bone). Discrepant findings were validated as true vs. false positive by histopathology or image follow-up. Tracer uptake in tumor tissue was assessed by SUVmax. Results: In total n=100 patients (median 62 years, male/female n=68/32) underwent FDG- and FAP-PET. Five most frequent tumor entities and respective median FDG vs FAP uptake were RCC (n=19; SUVmax 8.4 vs. 7.1), sarcoma (n=18; 10.3 vs. 10.9), NSCLC (n=10; 12.4 vs. 13.7), lymphoma (n=9; 18.3 vs. 10.9), and PDAC (n=8; 4.1 vs. 7.3). On a per-patient basis, FDG- vs FAP-PET localized malignancy in n=93/94 patients. FDG- vs FAP-PET was concordant for the assessment of 362/400 (91%) regions. n=16/400 (4%) regions were negative on FDG- and positive on FAP-PET (88% true, 12% false positive). n=22/400 (6%) regions were negative on FAP- and positive on FDG-PET (57% true, 43% false positive). Two false positive FDG-PET findings were due to tracer uptake in reactive lymph nodes. There were no PET-related adverse events. Conclusions: In patients with various tumor entities, standard FDG- and novel FAP-PET localized tumor equally well. Additionally, FAP-PET was associated with a lower rate of false positive findings, especially in lymph node assessments. Clinical trial information: NCT05160051 . [Table: see text]
Utility of artificial intelligence-based genomic classification of occult malignancies in clinical practice.
Authors: Darabi Sourat , Zuazo Carlos E , Brodie Taylor , Demeure Michael J. , Braxton David R. 
Published: June 2023

3065 Background: Occult primary malignancies (OPM) are a significant clinical problem, representing 3 to 5% of advanced cancers. Patients with OPM have a worse prognosis and fewer treatment options than when the primary site of origin of cancer can be confidently identified. Novel artificial intelligence-based genomic classification of occult malignancies has been validated for clinical use by previous studies, but reports of clinical utility have not yet been published. We report our experience of consecutive cases where a commercial AI-based genomic classifier was used in routine practice at a high-volume community cancer center. Methods: Malignancies with uncertain pathological classification or site of origin were subjected to molecular profiling and AI-based genomic classification (GPSai) capable of recognizing a set of 115 distinct primary tumor sites and histology classes. Molecular profiling consisted of whole exome and whole transcriptome sequencing of FFPE tumor samples along with other predictive biomarkers assays performed by a commercial laboratory (Caris Life Sciences). The identification of targetable mutations was reported, but variants of unknown significance were excluded when reporting genomic alterations. Results: From 1,316 patients between October 2021-November 2022, we analyzed 70 (5.3%) patients with OPM, including 44 (62.9%) females and 26 (37.1%) males, with 34 (48.6%) being 65 or older. GPSai classification was ordered for 73 samples from 70 patients, which resulted in the classification of 33 (45.2%) tumors, inconclusive results in 36 (49.3%), and insufficient tissue quantity in 4 (5.5%). Of the 33 cases with a GPSai classification, the putative pathology diagnosis was concordant in 26 (78.8%) and discordant in 7 (21.2%) cases. We investigated discordance between the GPSai and pathological diagnoses in discordant cases . The pathological classification was favored over GPSai in all 7 discordant cases. Of the 36 cases that could not be confidently assigned a classification, 14 (38.9%) possessed potentially actionable alterations . 23 of the 36 had no presumptive site of origin. Of these, 10 of 23 (43.5%) were PD-L1 positive, 4 of 23 (17.4%) had a high TMB, and 1 of 23 (4.4%) had MMR deficiency. Additionally, based on molecular profile and examination of RNA expression levels, 2 cases were able to be classified with subsequent IHC confirmation. Based on the results from genomic testing, 55.7% of patients (39 of 70) had FDA-approved treatment options. Conclusions: Over a third of patients with OPM were able to be assigned a cancer diagnosis concordant with diagnoses by pathologists. Of those which could not be classified, targetable biomarkers were commonly found. AI-based genomic classification of occult primaries is useful in clinical practice to help discern the site of origin and identify treatment options.
Systematic review and meta-analysis of the accuracy and applicability of blood-based multi-cancer early detection (MCED) in the general population.
Authors: Park Joo Hee , Oh Youjin , Chung Liam Il-Young , Duan Richard , Djunadi Trie Arni , Yoon Sung Mi , Shah Zunairah , Jung Chan Mi , Hong Ilene , Kim Leeseul , Chae Young Kwang 
Published: June 2023

3069 Background: Globally, cancer results in 10.08 million deaths per year. A single blood-based screening tool that detects multiple cancer types could significantly reduce cancer burden. We systematically reviewed and statistically examined both the accuracy and applicability of blood-based MCED tests to strategize their utilization in improving cancer detection. Methods: Original articles were searched from PubMed, Cochrane, and Embase for blood-based screening tests analyzing multiple cancer types and asymptomatic human subjects. We excluded studies with small sample sizes (n<30), hypothesis-generating/diagnostic tests, and non-blood-based tests. For cfDNA-based assays, measurements of diagnostic accuracy were pooled for meta-analysis. Results: Of 1,074 records identified and screened, 15 case-control and 4 cohort studies were analyzed, most of which utilized cfDNA-based diagnostic tests. Twelve cfDNA studies selected for meta-analysis had pooled sensitivity of 0.623 (95%CI 0.517 - 0.719) and specificity of 0.975 (0.942 - 0.990). Summary ROC curve shows variability in sensitivity and specificity between studies. However, sensitivity and specificity were not affected by study type, gender, or assay type. Sensitivity was higher for advanced staged cancers (III/IV 0.774 (0.697 - 0.837)) than early-stage cancers (I/II 0.503 (0.366 - 0.639)). Among cancer types, no significant differences were detected. Lastly, false positive and false negative rates were 0.025 (0.010 - 0.058) and 0.447 (0.438 - 0.456), respectively. Conclusions: Given high sensitivities and specificities, MCED tests show promise as additional screening tools. However, in the general population, misdiagnosis burden from false positive and negative rates is anticipated. Although multiple barriers exist to their application in the clinic, MCED tests may improve patient outcomes for cancers with no conventional screening tools and provide additional credibility when combined with existing tools. Future prospective studies with large and diverse populations are warranted. [Table: see text]