tbuckley/cabot-search huggingface dataset:
Abstract B009: Individualized-tumor-informed panel approach enables ultra-sensitive ctDNA-based minimal residue disease monitoring for high-risk pediatric cancers
Authors: Rob Salomon, Wenhan Chen, Charles Shale, Mojgan Toumari, Aileen Lowe, Wenyan Li, Jingwei Chen, Sajad Razavi-Bazaz, Paulette Barahona, Louise Cui, Chelsea Mayoh, Sam El-Kamand, Vanessa Tyrrell, Marie Wong-Erasmus, Loretta Lau, Noemi Fuentes-Bolanos, Edwin Cuppen, Dong-Anh Khoung-Quang, Jordan Staunton, Marion K Mateos, Toby Trahair, Michelle Haber, David S Ziegler, Paul Ekert, Peter Priestley, Mark Cowley
Journal: Clinical Cancer Research (2024)

Abstract While the use of ctDNA-based minimal residual disease (MRD) monitoring is gaining popularity in adult cancers, this approach is not yet widely adopted in pediatric cancers (PCs). We developed a robust and sensitive assay to monitor ctDNA in PCs, which overcomes PC-specific challenges including low tumor mutational burden, paucity of hotspot mutations and low blood volume. To address these challenges, our innovations include personalized panel design that targets primary tumor mutations from each patient, a fixed panel targeting hotspot mutations, error suppression from duplex deep sequencing and customized pipeline for tumor burden estimation. We retrospectively analyzed 661 blood or cerebrospinal fluid (CSF) samples from 168 patients. We achieved an average detection limit of 0.005% ctDNA purity leading to MRD detected ranging from 0.001% to 100% with brain tumor consistently showing a low MRD. At disease diagnosis, progression and relapse, our assay identified ctDNA in over 93% of extra- cranial solid tumors, 90% of leukemia, 89% of sarcoma, and 90% of neuroblastoma. For brain tumors, we detected MRD in ∼90% of CSF samples, and in ∼60% of blood samples, a major advance over previous approaches. Importantly, we detected MRD in ∼ 20% of cases with a clinically complete response, predicting relapse up to 6 months before clinical confirmation. Overall, these results demonstrate that our monitoring assay for PCs is an important addition to standard of care for precision-guided treatment. Citation Format: Rob Salomon, Wenhan Chen, Charles Shale, Mojgan Toumari, Aileen Lowe, Wenyan Li, Jingwei Chen, Sajad Razavi-Bazaz, Paulette Barahona, Louise Cui, Chelsea Mayoh, Sam El-Kamand, Vanessa Tyrrell, Marie Wong-Erasmus, Loretta MS Lau, Noemi Fuentes-Bolanos, Edwin Cuppen, Dong-Anh Khoung-Quang, Jordan Staunton, Marion K Mateos, Toby Trahair, Michelle Haber, David S Ziegler, Paul Ekert, Peter Priestley, Mark Cowley. Individualized-tumor-informed panel approach enables ultra-sensitive ctDNA-based minimal residue disease monitoring for high-risk pediatric cancers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B009.
Abstract A067: lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models
Authors: Shivali Singh
Journal: Clinical Cancer Research (2024)

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA-sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5-DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as a biomarker panel for a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel are being conducted, in vitro and in vivo, to create a novel liquid biopsy to assist in the prognostic diagnosis of metastatic progression of pancreatic cancer. Citation Format: Shivali Singh. lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A067.
Abstract B026: Glioblastoma multiforme disseminates outside the central nervous system
Authors: Pavel Stejskal, Josef Srovnal, Alona Rehulkova, Ondrej Kalita, Marek Slachta, Marian Hajduch
Journal: Clinical Cancer Research (2024)

Abstract Introduction: The liquid biopsy (LB) concept has gained significant attention in the last decade and has the potential to revolutionize cancer care. However, more validation in clinical trials is required on the value of LB in medical settings. Here, we focus on glioblastoma multiforme (GBM), a highly invasive and fatal subtype of the central nervous system malignant tumors. Circulating tumor cells (CTCs) are primary tumor cells released into the peripheral blood and migrating to distant organs. CTC presence is related to tumor spread and recurrence. In GBM, factors like short patient survival, the blood-brain barrier (BBB), and lack of lymphatic drainage in brain tissue make systemic dissemination rare but possible. Thus, noninvasive CTC detection can hold potential for diagnostic, predictive, and prognostic applications. Material and Methods: For cell stability preservation before sample processing, the peripheral blood samples from curatively resected GBM patients were collected preoperatively in Cell-Free DNA BCT® tubes (Streck, Inc.). CTCs were identified using CytoTrack CT11TM (2/C), a semi-automated immunofluorescence microscopy using glial fibrillary acidic protein, vimentin, and CD45 immunostaining, and DAPI counterstaining. The preliminary Kaplan-Maier survival analysis based on CTC positivity was performed in 39 patients with a follow-up longer than two years. Results: We analyzed the CTC presence in 100 GBM patient peripheral blood samples. The CTCs or cancer cell clusters were found in 35% of GBM patients. The Kaplan-Maier survival analysis did not show a correlation between CTC presence and survival. This phenomenon may be associated with the generally short survival of these patients, which is expected to increase with advances in oncology and palliative care and/or a possible suppression of tumor cell growth outside the CNS. Conclusions: We have observed the CTCs in the peripheral blood of GBM patients. The patient enrollment and clinical data recording are still ongoing. Citation Format: Pavel Stejskal, Josef Srovnal, Alona Rehulkova, Ondrej Kalita, Marek Slachta, Marian Hajduch. Glioblastoma multiforme disseminates outside the central nervous system [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B026.
Abstract A061: A cost-effective two-step approach for multi-cancer early detection in general population
Authors: Mao Mao, None Geng shuai peng, None Li shi yong, Wu Wei, Chang Yin Yin
Journal: Clinical Cancer Research (2024)

Abstract In population-wide cancer screening, three key issues need to be focused on: number of cancer cases identified, the issue of false positives, and cost. A high false positive rate can result in a significant waste of healthcare resources. Large-scale screening inevitably leads to significant financial burdens on the healthcare system which is a key factor constraining nationwide screening. OncoSeek is a multi-cancer early detection (MCED) test using a panel of seven plasma protein tumor markers (PTMs) and artificial intelligence (AI). SeekInCare is a MCED test that integrates the seven PTMs and four cancer genomic features (aneuploidy, fragment size, end motifs, and oncogenic viruses) from cell-free DNA (cfDNA) by shallow whole-genome sequencing (sWGS). In a two-step approach, the initial screening is conducted using OncoSeek and SeekInCare is then used as the secondary test for those individuals who tested positive by OncoSeek. In a case-control study (n = 1197) including both OncoSeek and SeekInCare testing results, OncoSeek showed 49.9% sensitivity at 91.0% specificity, while SeekInCare demonstrated 60.0% sensitivity at 98.3% specificity. In the two-step process, specificity significantly increased from 91.0% to 99.3%, while sensitivity decreased from 49.9% to 39.9%. We modeled a screening in five million adults aged ≥ 50 years with a cancer incidence rate of 1.9%. The simulated real-world sensitivities of OncoSeek and two-step were adjusted downward proportionally to 28.0% and 22.4% based on the sensitivity differences observed between GRAIL’s CCGA study (case-control, 51.5%) and PATHFINDER study (prospective, 28.9%). While at 91.0% specificity OncoSeek had 441,450 cases of false positives, using the two-step approach significantly reduced false positives to 34,335 (0.7%). Although Galleri ($949 per test) identified more cancer cases than the two-step MCED, with 27,455 and 21,280 cases respectively, its total cost for the former reached $4,745 million. As the positive predictive value (PPV) of two-step (38.3%) was the same as Galleri (38.3%), it reduced cost 6.6-fold, amounting to a total cost of $713.6 million and a cost of $143 per individual screened. The cost of per cancer case detected using Galleri is $172,828 compared to $33,534 using the two-step MCED, which represents a 5.2-fold difference. In conclusion, the two-step approach not only significantly reduces false positives, but also cuts the screening cost down substantially, making it a cost-effective strategy for population-wide cancer screening. Citation Format: Mao Mao, Geng shuai peng, Li shi yong, Wu Wei, Chang Yin Yin. A cost-effective two-step approach for multi-cancer early detection in general population [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A061.
Abstract A065: Estimation of HPV16-induced cervical cancer cells in routine Thin-prep cytology samples of cancer patients
Authors: Srishty Raman, Pranay Tanwar, Neerja Bhatla, Subhash Chandra Yadav
Journal: Clinical Cancer Research (2024)

Abstract Persistent infection with human papillomavirus has been implicated in the etiology of cervical cancer and sustained expression of its E7 oncoprotein has been rendered suggestive of malignant transformation. However, there are limited E7 protein-based detection assays. This might be due to paucity of data on steady-state expression level of E7 protein and the number of HPV-induced cervical cancer cells in routine Thin-prep cytology samples. So, the objective of the present study was to identify and estimate HPV16-induced cervical cancer cells in cytology samples of cancer patients, with the goal to generate a quantitative immunological method in the cytological diagnosis of cervical lesions. We collected 25 Thin-prep cytology samples of cervical cancer patients (PAP test confirmed) from Obstetrics and Gynecology department, AIIMS, New Delhi. Samples were conditioned to enrich cellular components and were then quantified using hemocytometer for total cell count, PAP staining for cancerous cell count and immunofluorescence using HPV16 E7 antibody for HPV16-induced cancerous cell count. The method devised efficiently found an average number of 7 × 103 cells/ ml to be E7 positive, out of total 27 x 104 cells/ ml. Although PAP test detected 71 x 103 cells/ ml to be abnormal or cancerous, only 10% of them were found to be HPV16 transformed, suggesting HPV E7 as the primary marker for detecting transformed cells and thereby, identifying patients at-risk and prompting a better prognosis. This simple and efficient method deduced allows optimizing the number of HPV16-induced cervical cancer cells from cytology samples which directly correlates to the amount of HPV-16 major oncoprotein- E7 expression, and the disease severity. Citation Format: Srishty Raman, Pranay Tanwar, Neerja Bhatla, Subhash Chandra Yadav. Estimation of HPV16-induced cervical cancer cells in routine Thin-prep cytology samples of cancer patients [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A065.
Abstract A015: Validation of a cancer early-detection assay on liquid biopsies using DNA methylation
Authors: Ekaterina Gracheva
Journal: Clinical Cancer Research (2024)

Abstract There is growing awareness of the benefits of early cancer detection. Early intervention can improve patient outcomes, leading to a reduction in the health care burden associated with cancer, and can also provide critical information for personalized treatments. Liquid biopsies enable quick, easy, non-invasive, and real-time testing that is suitable for screening and increases accessibility, particularly in developing countries. The use of epigenomic techniques, such as DNA methylation profiling, enhances the depth and breadth of screening beyond what standard genetic analysis can offer. Universal Diagnostics (UDx), a respected pioneer in the field of early cancer detection, has partnered with Hologic Diagenode, which brings 20 years of experience in epigenomics, to develop a customized early detection workflow for colorectal cancer (CRC). This analysis relies on DNA methylation biomarkers identified within cell-free DNA (cfDNA) from plasma. The UDx assay provides not only easy screening but also a more comprehensive analysis than that possible with conventional markers. Genome-wide methylation profiles from healthy individuals and cancer patients were used to identify biomarkers. These biomarker candidates were then validated for performance; the results of which are presented in this poster. Citation Format: Ekaterina Gracheva. Validation of a cancer early-detection assay on liquid biopsies using DNA methylation [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A015.
Abstract B004: Biological insights into tissue-agnostic plasma cfDNA methylation signature for surveillance of head and neck tumor recurrence
Authors: Yulia Newton, Justin Burgener, Margaret Gruca, Collin Melton, Jun Min, Abel Licon, Scott Bratman, Alan Williams, Daniel D De Carvalho
Journal: Clinical Cancer Research (2024)

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR004) of the Conference Program/Proceedings. Citation Format: Yulia Newton, Justin Burgener, Margaret Gruca, Collin Melton, Jun Min, Abel Licon, Scott Bratman, Alan Williams, Daniel D De Carvalho. Biological insights into tissue-agnostic plasma cfDNA methylation signature for surveillance of head and neck tumor recurrence [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B004.
Abstract B041: High purity CTC RNA sequencing identifies poor prognosis lineage states in castrate resistant prostate cancer
Authors: Marina N Sharifi, Jamie M Sperger, Amy K Taylor, Katharine E Tippins, Shannon R Reese, Viridiana Carreno, Katherine R Kaufmann, Alex H Chang, Luke A Nunamaker, Charlotte Linebarger, Kyle T Helzer, Matthew Bootsma, Grace C Blitzer, John Floberg, David Kosoff, Rana R McKay, Xiao X Wei, Shuang G Zhao, Joshua M Lang
Journal: Clinical Cancer Research (2024)

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR010) of the Conference Program/Proceedings. Citation Format: Marina N Sharifi, Jamie M Sperger, Amy K Taylor, Katharine E Tippins, Shannon R Reese, Viridiana Carreno, Katherine R Kaufmann, Alex H Chang, Luke A Nunamaker, Charlotte Linebarger, Kyle T Helzer, Matthew Bootsma, Grace C Blitzer, John Floberg, David Kosoff, Rana R McKay, Xiao X Wei, Shuang G Zhao, Joshua M Lang. High purity CTC RNA sequencing identifies poor prognosis lineage states in castrate resistant prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B041.
Abstract A073: The potential of multi-cancer early detection screening for reducing cancer mortality
Authors: Jagpreet Chhatwal, Jade Xiao, Andrew ElHabr, Christopher Tyson, Xiting Cao, Sana Raoof, A. Mark Fendrick, A. Burak Ozbay, Paul Limburg, Tomasz M. Beer, Ashish Deshmukh, Andrew Briggs
Journal: Clinical Cancer Research (2024)

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR006) of the Conference Program/Proceedings. Citation Format: Jagpreet Chhatwal, Jade Xiao, Andrew ElHabr, Christopher Tyson, Xiting Cao, Sana Raoof, A. Mark Fendrick, A. Burak Ozbay, Paul Limburg, Tomasz M. Beer, Ashish Deshmukh, Andrew Briggs. The potential of multi-cancer early detection screening for reducing cancer mortality [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A073.
Abstract A040: Using mitochondrial abundance in tumor-derived extracellular vesicles for pancreatic cancer screening
Authors: Dali Sun
Journal: Clinical Cancer Research (2024)

Abstract Pancreatic cancer, marked by a high mortality rate and rising incidence, often goes undetected until advanced stages, complicating treatment. Tumor-derived extracellular vesicles (EVs) have emerged as promising cancer biomarkers due to their cargo from parent cells. However, current detection methods are often time-consuming, expensive, and complex. To overcome these challenges, we developed a screening assay for pancreatic cancer that uses the mitochondrial DNA to nuclear DNA ratio in tumor-derived EVs as a distinguishing feature. This assay combines immunoprecipitation with qPCR quantification for direct detection of tumor-derived EVs from serum, utilizing DNA-isolation-free techniques and duplexing probes for qPCR, thus saving at least 3 hours. Clinical sample testing demonstrated the assay's potential as a translational tool for cancer screening, showing a weak correlation with prognosis biomarkers and sufficient discriminatory power between healthy controls, pancreatitis, and pancreatic cancer cases. Citation Format: Dali Sun. Using mitochondrial abundance in tumor-derived extracellular vesicles for pancreatic cancer screening [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A040.
Abstract A048: Screening early detection of HPV-associated oropharynx cancers with multi- feature HPV whole genome sequencing liquid biopsy
Authors: Krystle Kuhs, Hilary Robbins, Dipon Das, Michael Bryan, Ling Aye, Yana Al-Inaya, Shun Hirayama, Viktor Adalsteinsson, Michael Lawrence, Tim Waterboer, Daniel L Faden
Journal: Clinical Cancer Research (2024)

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR007) of the Conference Program/Proceedings. Citation Format: Krystle Kuhs, Hilary Robbins, Dipon Das, Michael Bryan, Ling Aye, Yana Al-Inaya, Shun Hirayama, Viktor Adalsteinsson, Michael Lawrence, Tim Waterboer, Daniel L Faden. Screening early detection of HPV-associated oropharynx cancers with multi- feature HPV whole genome sequencing liquid biopsy [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A048.
Abstract A033: Leveraging mass cytometry for phenotyping CTCs in SCLC liquid biopsies: Tracking therapy resistance at a personalized level
Authors: Loukia G Karacosta, Sayantan Bhattacharyya, Allison Stewart, Ashley Victorian, Ester F Lujan, Shafqat Ehsan, Subin Kim, Alberto Duarte, Runsheng Wang, Benedict Anchang, Jing Wang, Lauren Byers
Journal: Clinical Cancer Research (2024)

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR005) of the Conference Program/Proceedings. Citation Format: Loukia G Karacosta, Sayantan Bhattacharyya, Allison Stewart, Ashley Victorian, Ester F Lujan, Shafqat Ehsan, Subin Kim, Alberto Duarte, Runsheng Wang, Benedict Anchang, Jing Wang, Lauren Byers. Leveraging mass cytometry for phenotyping CTCs in SCLC liquid biopsies: Tracking therapy resistance at a personalized level [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A033.