medRxiv - Oncology最新文献

{"title":"Quantitative Microscopy in Medicine","authors":"Alexandre Matov","doi":"10.1101/2024.07.31.24311304","DOIUrl":"https://doi.org/10.1101/2024.07.31.24311304","url":null,"abstract":"Methods for personalizing medical treatment are the focal point of contemporary biomedical research. In cancer care, we can analyze the effects of therapies at the level of individual cells. Quantitative characterization of treatment efficacy and evaluation of why some individuals respond to specific regimens, whereas others do not, requires additional approaches to genetic sequencing at single time points. Methods for the analysis of changes in phenotype, such as in vivo and ex vivo morphology and localization of cellular proteins and organelles can provide important insights into patient treatment options. Novel therapies are needed to extend survival in metastatic castration-resistant prostate cancer (mCRPC). Prostate-specific membrane antigen (PSMA), a cell surface glycoprotein that is commonly overexpressed by prostate cancer (PC) cells relative to normal prostate cells, provides a validated target. We developed a software for image analysis designed to identify PSMA expression on the surface of epithelial cells in order to extract prognostic metrics. In addition, our software can deliver predictive information and inform clinicians regarding the efficacy of PC therapy. We can envisage additional applications of our software system, beyond PC, as PSMA is expressed in a variety of tissues. Our method is based on image denoising, topologic partitioning, and edge detection. These three steps allow to segment the area of each PSMA spot in an image of a coverslip with epithelial cells. Our objective has been to present the community with an integrated, easy to use by all, tool for resolving the complex cytoskeletal organization and it is our goal to have such software system approved for use in the clinical practice.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"164 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"PRESCRIBING PRACTICES AND CLINICAL IMPACT OF NEXT GENERATION SEQUENCING IN ROUTINE PRACTICE IN SOLID TUMORS REAL WORLD EXPERIENCE IN LMIC\"","authors":"Adeeba Zaki, Nida E Zehra Sameer, Aqsa Sohail, Zeeshan Ansar, Munira Moosajee","doi":"10.1101/2024.08.01.24311330","DOIUrl":"https://doi.org/10.1101/2024.08.01.24311330","url":null,"abstract":"\"Molecular characterization of disease is essential for precision medicine due to novel predictive biomarkers. Multiple next-generation sequencing (NGS) platforms are available, but their expense and clinical utility vary. Even if a targetable mutation is detected, corresponding drugs may not be available or affordable. No prior studies in Pakistan have focused on integrating NGS results into patient care to assist with therapeutic decision-making and survival outcomes.\u0000This retrospective study aimed to evaluate the molecular profiling and therapeutic implications of NGS testing across solid tumors. It included all patients with histologically proven malignancy (metastatic or non-metastatic) who had NGS analysis at Aga Khan University Hospital (AKUH) from June 1, 2020, to June 1, 2023. Foundation One was the NGS platform used. From 2020 to 2023, 192 patients underwent NGS. The majority were male (55.2%) and aged over 50 years (71.9%). The most common indications for NGS were carcinoma of unknown primary (CUP) and lung cancers, representing 26% and 25% respectively, followed by colon (9%) and breast cancers (8%). Most patients had metastatic disease (98.4%). Common mutations in lung cancer were EGFR (16.3%) and KRAS G12C (14.3%). In unknown primary, breast, and colon cancers, the most common mutations were BRAF (8%), PIK3CA (18%), and KRAS (42.1%), respectively. Microsatellite instability (MSI) testing was performed in 95% of patients, with 6% being MSI high. Actionable alterations were detected in 31.8% of patients, but only 17.2% received genotype-matched treatment, mostly as a first-line treatment for lung cancer. The primary barriers were drug availability and affordability.\u0000Our results show that the implementation of NGS analysis supports clinical decision making. However, these results were applicable to a small percentage of patients. For better compliance and applicability, drug availability and cost of treatment needs to be addressed\"","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tissue and Peripheral T-cell Repertoire Predicts Immunotherapy Response and Progression-Free Survival in NSCLC Patients.","authors":"Manuel Pino-Gonzalez, Martin Lazaro-Quintela, Irene Alonso-Alvarez, Maria Gallardo-Gomez, Laura Juaneda-Magdalena, Alejandro Francisco-Fernandez, Silvia Calabuig-Farinas, Eloisa Jantus-Lewintre, Monica Martinez-Fernandez","doi":"10.1101/2024.08.01.24311282","DOIUrl":"https://doi.org/10.1101/2024.08.01.24311282","url":null,"abstract":"Immunotherapy has opened new avenues of treatment for patients with advanced non-small cell lung cancer (NSCLC) without previous hope of survival. Unfortunately, only a small percentage of patients benefit from it, and it is still not well understood which tumor characteristics can be used to predict immunotherapy response. As the key cellular effectors of antitumor immunity, T cells are endowed with specialized T cell receptors (TCRs) to recognize and eliminate cancer cells. Here, we evaluated the potential of TCR repertoire as a predictive biomarker in patients treated with immunotherapy. With this aim, advanced NSCLC patients treated with immunotherapy at first-line were included. After obtaining peripheral blood and tissue samples at baseline, next-generation sequencing targeting TCRbeta/gamma was performed. Beyond TCR metrics, clonal space of the most frequent clones was determined. We found a positive association between uneven tumor-infiltrating TCRbeta repertoire and the immunotherapy response. Moreover, the use of various tumor-infiltrating and circulating TRBV/J genes predicted the immunotherapy response. Our results indicate the importance of evaluating tissue and circulating TCRbeta repertoire prior immunotherapy, showing it as a promising immunotherapy response biomarker in NSCLC patients.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"56 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PRESCRIBING PRACTICES AND CLINICAL IMPACT OF NEXT GENERATION SEQUENCING IN ROUTINE PRACTICE IN SOLID TUMORS – REAL WORLD EXPERIENCE IN LMIC","authors":"nidaezehra zehra, Nida E Zehra, Aqsa Sohail, Zeeshan Ansar, Munira Moosajee","doi":"10.1101/2024.07.31.24311267","DOIUrl":"https://doi.org/10.1101/2024.07.31.24311267","url":null,"abstract":"Molecular characterization of disease is essential for precision medicine due to novel predictive biomarkers. Multiple next-generation sequencing (NGS) platforms are available, but their expense and clinical utility vary. Even if a targetable mutation is detected, corresponding drugs may not be available or affordable. No prior studies in Pakistan have focused on integrating NGS results into patient care to assist with therapeutic decision-making and survival outcomes.\u0000This retrospective study aimed to evaluate the molecular profiling and therapeutic implications of NGS testing across solid tumors. It included all patients with histologically proven malignancy (metastatic or non-metastatic) who had NGS analysis at Aga Khan University Hospital (AKUH) from June 1, 2020, to June 1, 2023. Foundation One was the NGS platform used. From 2020 to 2023, 192 patients underwent NGS. The majority were male (55.2%) and aged over 50 years (71.9%). The most common indications for NGS were carcinoma of unknown primary (CUP) and lung cancers, representing 26% and 25% respectively, followed by colon (9%) and breast cancers (8%). Most patients had metastatic disease (98.4%). Common mutations in lung cancer were EGFR (16.3%) and KRAS G12C (14.3%). In unknown primary, breast, and colon cancers, the most common mutations were BRAF (8%), PIK3CA (18%), and KRAS (42.1%), respectively. Microsatellite instability (MSI) testing was performed in 95% of patients, with 6% being MSI high. Actionable alterations were detected in 31.8% of patients, but only 17.2% received genotype-matched treatment, mostly as a first-line treatment for lung cancer. The primary barriers were drug availability and affordability.\u0000Our results show that the implementation of NGS analysis supports clinical decision making. However, these results were applicable to a small percentage of patients. For better compliance and applicability, drug availability and cost of treatment needs to be addressed","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in pancreatic cancer","authors":"Xutai Li, Pengwu Zhang, Hui Zhang, Chen Sun, Yutong Wu, Huimei Zhou, Zhenjian Ge, Shengjie Lin, Yingqi Li, Wenkang Chen, Wuping Wang, Siwei Chen, Wei Li, Fei Feng, Zewei Lin, Ling Ji, Yongqing Lai","doi":"10.1101/2024.07.30.24311246","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311246","url":null,"abstract":"BACKGROUND: Pancreatic cancer is a serious threat to human health. Ultrasound is widely used in screening or preliminary diagnosis of pancreatic cancer, and enhanced CT is widely used in the diagnosis of pancreatic cancer. However, false-positive results of ultrasound and enhanced CT will bring unnecessary mental pain, expensive examination costs, physical injuries, and even adverse consequences such as organ removal and loss of function; while false-negative results of enhanced CT bring delayed treatment, and patients will thus have to bear the adverse consequences of poor prognosis, high treatment costs, poor quality of life, and short survival period. There is an urgent need to find convenient, cost-effective and non-invasive diagnostic methods to reduce the false-positive rate of ultrasound and the false-negative and false-positive rates of enhanced CT in pancreatic tumors. The aim of this study was to evaluate the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in pancreatic cancer.\u0000MATERIALS AND METHODS: 62 subjects (malignant group, n=37; benign group, n=25) were finally included in this study. Remaining serum samples from the subjects were collected and tested by applying the YiDiXie™ all-cancer detection kit to evaluate the sensitivity and specificity of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D, respectively. RESULTS: The sensitivity of YiDiXie™-SS in pancreatic ultrasound-positive patients was 100% (95% CI: 90.6% - 100%) and the specificity was 60.0% (95% CI: 55.4% - 69.7%). Compared with enhanced CT alone, sequential use of YiDiXie™-SS and enhanced CT resulted in comparable sensitivity, but the false-positive rate decreased from 24.0% (95% CI: 11.5% - 43.4%) to 8.0% (95% CI: 1.4% - 25.0%). This means that the application of YiDiXie™-SS reduces the false-positive rate of ultrasound by 60.0% (95% CI: 55.4% - 69.7%) and reduces the false-positive rate of enhanced CT by 66.7% with essentially no increase in the leakage of malignant tumors.YiDiXie™-HS had a sensitivity of 85.7% (95% CI: 48.7% - 99.3%) and a specificity of 84.2% (95% CI: 62.4% - 92.5%) in enhanced CT-negative patients. This means that YiDiXie™-HS reduces the false-negative enhancement CT rate by 84.2% (95% CI: 62.4% - 92.5%). YiDiXie™-D has a sensitivity of 33.3% (95% CI: 19.2% - 51.2%) and a specificity of 100% (95% CI: 61.0% - 100%) in patients with positive enhancement CT. This means that YiDiXie™-D reduces the false positive rate of enhanced CT by 100% (95% CI: 61.0% - 100%). CONCLUSION: YiDiXie™-SS significantly reduces the false-positive rate of ultrasound and enhanced CT in ultrasound-positive pancreatic patients with essentially no increase in delayed treatment of malignant tumors. YiDiXie™-HS significantly reduces the false-negative rate of enhanced CT in patients with pancreatic tumors. YiDiXie™-D significantly reduces the false-positive rate of enhanced CT in patients with pancreatic tumors. The YiDiXie™ test has significant diagnostic value in pancreat","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications of ICG in Breast Cancer for Sentinel Lymph Node Mapping: A Scoping Review Protocol","authors":"Feryal Kurdi, Yahya Kurdi, Igor Vladimirovich Reshetov","doi":"10.1101/2024.07.30.24311256","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311256","url":null,"abstract":"Objective: The objective of this scoping review is to evaluate the current literature on the use of Indocyanine Green (ICG) in sentinel lymph node (SLN) mapping for breast cancer patients. This review aims to assess the accuracy, efficacy, and safety of ICG in this context and to identify gaps in the existing research. The outcomes will contribute to the development of further research as part of a PhD project.\u0000Introduction: Breast cancer is the leading cause of morbidity and mortality worldwide. Accurate SLN mapping is crucial for staging and treatment planning in early-stage breast cancer. ICG has emerged as a promising agent for fluorescence imaging in SLN mapping. However, comprehensive assessment of its clinical utility, including accuracy and adverse effects, remains limited. This scoping review aims to consolidate evidence on the use of ICG in breast cancer SLN mapping.\u0000Inclusion criteria: Patients with early-stage breast cancer (T1, T2), selected T3 cases where sentinel lymph node biopsy is accurate, and clinically node-negative breast cancer. The intervention includes studies using ICG for SLN mapping and assessment of fluorescence imaging cameras. Methods: Five electronic databases will be searched (PubMed, EMBASE, MEDLINE, Web of Science, and SCOPUS) using search strategies developed in consultation with the academic supervisor. The search strategy is set to human studies published in English within the last 11 years. All retrieved citations will be imported to Zotero and then uploaded to Covidence for screening of titles, abstracts, and full text according to pre-specified inclusion criteria. Citations meeting the inclusion criteria for full-text review will have their data extracted by two independent reviewers, with disagreements resolved by discussion. A data extraction tool will be developed to capture full details about the participants, concept, and context, and findings relevant to the scoping review will be summarized.\u0000Keywords: Indocyanine Green, ICG, Sentinel Lymph Node, Breast Cancer, Fluorescence, Axillary Lymph Node Mapping, NIR","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"151 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urinary Biomarkers for Disease Detection","authors":"Alexandre Matov","doi":"10.1101/2024.07.30.24311186","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311186","url":null,"abstract":"The current healthcare system relies largely on a passive approach toward disease detection, which typically involves patients presenting a 'chief complaint' linked to a particular set of symptoms for diagnosis. Since all degenerative diseases occur slowly and initiate as changes in the regulation of individual cells within our organs and tissues, it is inevitable that with the current approach to medical care we are bound to discover some illnesses at a point in time when the damage is irreversible and meaningful treatments are no longer available. There exist organ-specific sets (or panels) of nucleic acids, such as microRNAs (miRNAs), which regulate and help to ensure the proper function of each of our organs and tissues. Thus, dynamic readout of their relative abundance can serve as a means to facilitate real-time health monitoring. With the advent and mass utilization of next-generation sequencing (NGS), such a proactive approach is currently feasible. Because of the computational complexity of customized analyses of 'big data', dedicated efforts to extract reliable information from longitudinal datasets is key to successful early detection of disease. Here, we present our preliminary results for the analysis of healthy donor samples and drug-naive lung cancer patients.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Evaluation Of Machine Learning Classifiers For Brain Tumor Detection","authors":"Umair Ali","doi":"10.1101/2024.07.28.24311114","DOIUrl":"https://doi.org/10.1101/2024.07.28.24311114","url":null,"abstract":"Brain tumors, which are abnormal growths of cells in the brain, represent a significant health concern, necessitating prompt and accurate detection for effective treatment. If left untreated, brain tumors can lead to severe complications, including cognitive impairment, paralysis, and even death. This study evaluates six machine learning classifiers: Support Vector Classifier (SVC), Logistic Regression Classifier, K-Nearest Neighbors (KNN) Classifier, Naive Bayes Classifier, Decision Tree Classifier, and Random Forest Classifier - on a comprehensive brain tumor dataset. Our results showed that Random Forest achieved the highest accuracy of 98.27%, demonstrating its potential in detecting brain tumors. However, Support Vector Classifier (SVC) emerged as the top performer, achieving an impressive accuracy of 97.74%, showcasing its exceptional ability to detect brain tumors accurately. This significant improvement in SVC's performance highlights its potential as a reliable tool for medical diagnostics, contributing to the development of efficient and accurate automated systems for early brain tumor diagnosis, ultimately aiming to improve patient outcomes and treatment efficacy","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"213 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Pediatric Brain Tumor Imaging Assessment Tool from CBTN: Enhancing Suprasellar Region Inclusion and Managing Limited Data with Deep Learning","authors":"Deep B Gandhi, Nastaran Khalili, Ariana Familiar, Anurag Gottipati, Neda Khalili, Wenxin Tu, Shuvanjan Haldar, Hannah Anderson, Karthik Viswanathan, Phillip B Storm, Jeffrey B Ware, Adam C Resnick, Arastoo Vossough, Ali Nabavizadeh, Anahita Fathi Kazerooni","doi":"10.1101/2024.07.29.24311006","DOIUrl":"https://doi.org/10.1101/2024.07.29.24311006","url":null,"abstract":"Background: Fully-automatic skull-stripping and tumor segmentation are crucial for monitoring pediatric brain tumors (PBT). Current methods, however, often lack generalizability, particularly for rare tumors in the sellar/suprasellar regions and when applied to real-world clinical data in limited data scenarios. To address these challenges, we propose AI-driven techniques for skull-stripping and tumor segmentation.\u0000Methods: Multi-institutional, multi-parametric MRI scans from 527 pediatric patients (n=336 for skull-stripping, n=489 for tumor segmentation) with various PBT histologies were processed to train separate nnU-Net-based deep learning models for skull-stripping, whole tumor (WT), and enhancing tumor (ET) segmentation. These models utilized single (T2/FLAIR) or multiple (T1-Gd and T2/FLAIR) input imaging sequences. Performance was evaluated using Dice scores, sensitivity, and 95% Hausdorff distances. Statistical comparisons included paired or unpaired two-sample t-tests and Pearsons correlation coefficient based on Dice scores from different models and PBT histologies. Results: Dice scores for the skull-stripping models for whole brain and sellar/suprasellar region segmentation were 0.98±0.01 (median 0.98) for both multi- and single-parametric models, with significant Pearsons correlation coefficient between single- and multi-parametric Dice scores (r > 0.80; p<0.05 for all). WT Dice scores for single-input tumor segmentation models were 0.84±0.17 (median=0.90) for T2 and 0.82±0.19 (median=0.89) for FLAIR inputs. ET Dice scores were 0.65±0.35 (median=0.79) for T1-Gd+FLAIR and 0.64±0.36 (median=0.79) for T1-Gd+T2 inputs. Conclusion: Our skull-stripping models demonstrate excellent performance and include sellar/suprasellar regions, using single- or multi-parametric inputs. Additionally, our automated tumor segmentation models can reliably delineate whole lesions and enhancing tumor regions, adapting to MRI sessions with missing sequences in limited data context.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A phase I clinical trial of intrahepatic artery delivery of TG6002 in combination with oral 5-fluorocytosine in patients with liver-dominant metastatic colorectal cancer","authors":"Emma West, Alain Sadoun, Kaidre Bendjama, Philippe Erbs, Cristina Smolenschi, Philippe Cassier, Thierry De Baere, Sophie Sainte-Croix, Maud Brandely, Alan Melcher, Fay Ismail, Karen Scott, Angela Bennett, Emma Banks, Ewa Gasior, Sarah Kent, Marta Kurzawa, Christopher Hammond, Jai Patel, Fiona Collinson, Chris Twelves, D Alan Anthoney, Daniel Swinson, Adel Samson","doi":"10.1101/2024.07.30.24311046","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311046","url":null,"abstract":"Background: Effective treatment for patients with metastatic cancer is limited, particularly for colorectal cancer patients with metastatic liver lesions (mCRC), where accessibility to numerous tumours is essential for favourable clinical outcomes. Oncolytic viruses (OVs) selectively replicate in cancer cells; however, direct targeting of inaccessible lesions is limited when using conventional intravenous (i.v.) or intratumoural (i.t.) administration routes. Methods: We conducted a multi-centre, dose-escalation, phase I study of vaccinia virus, TG6002, via intrahepatic artery (IHA) delivery in combination with the oral pro-drug 5-fluorocytosine (5-FC) to fifteen mCRC patients. Results: Successful IHA delivery of replication-competent TG6002 was achieved, as demonstrated by virus within tumour biopsies. Functional transcription of the FCU1 transgene indicates viral replication within the tumour, with higher plasma concentrations of 5-fluorouracil (5-FU) associated with patients receiving the highest dose of TG6002. IHA delivery of TG6002 correlated with a robust systemic peripheral immune response to virus with activation of peripheral blood mononuclear cells, associated with a proinflammatory cytokine response and release of calreticulin, potentially indicating immunogenic cell death. Gene Ontology analyses of differentially-expressed genes reveal a significant immune response at the transcriptional level in response to treatment. Moreover, an increase in the number and frequency of T cell receptor clones against both cancer- and neo-antigens, with elevated functional activity, may be associated with improved anti-cancer activity. Despite these findings, no clinical efficacy was observed. Conclusions: In summary, these data demonstrate delivery of OV to tumour via IHA administration, associated with viral replication and significant peripheral immune activation. Collectively, the data supports the need for future studies using IHA administration of OVs.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"358 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}