NPJ Precision Oncology最新文献

Relapse-free survival in a pediatric patient with recurrent EZH2-mutant melanoma treated with adjuvant tazemetostat.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-21 DOI: 10.1038/s41698-025-00826-8

Erin E Resch, Stavriani C Makri, Paola Ghanem, Ezra G Baraban, Kenneth J Cohen, Alan R Cohen, Evan J Lipson, Christine A Pratilas

引用次数: 0

Personalized dose selection platform for patients with solid tumors in the PRECISE CURATE.AI feasibility trial.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-21 DOI: 10.1038/s41698-025-00835-7

Agata Blasiak, Anh T L Truong, Nigel Foo, Lester W J Tan, Kirthika S Kumar, Shi-Bei Tan, Chong Boon Teo, Benjamin K J Tan, Xavier Tadeo, Hon Lyn Tan, Cheng Ean Chee, Wei Peng Yong, Dean Ho, Raghav Sundar

{"title":"Personalized dose selection platform for patients with solid tumors in the PRECISE CURATE.AI feasibility trial.","authors":"Agata Blasiak, Anh T L Truong, Nigel Foo, Lester W J Tan, Kirthika S Kumar, Shi-Bei Tan, Chong Boon Teo, Benjamin K J Tan, Xavier Tadeo, Hon Lyn Tan, Cheng Ean Chee, Wei Peng Yong, Dean Ho, Raghav Sundar","doi":"10.1038/s41698-025-00835-7","DOIUrl":"https://doi.org/10.1038/s41698-025-00835-7","url":null,"abstract":"In oncology, the conventional reliance on the maximum tolerated dose (MTD) strategy for chemotherapy may not optimize treatment outcomes for individual patients. CURATE.AI is an AI-derived platform that utilizes a patient's own, small dataset to dynamically personalize only their own dose recommendations. The primary objective of this feasibility trial was to assess the logistical and scientific feasibility of providing dynamically personalized AI-derived chemotherapy dose recommendations for patients with advanced solid tumors at/for treatment with single-agent capecitabine, capecitabine in combination with oxaliplatin (XELOX), or capecitabine in combination with irinotecan (XELIRI). CURATE.AI demonstrated adaptability to clinically relevant situations encountered by patients often treated with palliative intent of care. High rates of user adherence were demonstrated, which could be in part due to the high engagement of the physicians in selecting data and boundaries for CURATE.AI operations.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"49"},"PeriodicalIF":6.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143472750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Opportunities and challenges for patient-derived models of brain tumors in functional precision medicine.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-14 DOI: 10.1038/s41698-025-00832-w

Breanna Mann, Nichole Artz, Rami Darawsheh, David E Kram, Shawn Hingtgen, Andrew B Satterlee

引用次数: 0

Towards an interpretable deep learning model of cancer.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-14 DOI: 10.1038/s41698-025-00822-y

Avlant Nilsson, Nikolaos Meimetis, Douglas A Lauffenburger

引用次数: 0

Author Correction: An automated deep learning pipeline for EMVI classification and response prediction of rectal cancer using baseline MRI: a multi-centre study.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-12 DOI: 10.1038/s41698-025-00827-7

Lishan Cai, Doenja M J Lambregts, Geerard L Beets, Monique Maas, Eduardo H P Pooch, Corentin Guérendel, Regina G H Beets-Tan, Sean Benson

引用次数: 0

An integrated perspective on single-cell and spatial transcriptomic signatures in high-grade gliomas.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-11 DOI: 10.1038/s41698-025-00830-y

Célia Lemoine, Marc-Antoine Da Veiga, Bernard Rogister, Caroline Piette, Virginie Neirinckx

{"title":"An integrated perspective on single-cell and spatial transcriptomic signatures in high-grade gliomas.","authors":"Célia Lemoine, Marc-Antoine Da Veiga, Bernard Rogister, Caroline Piette, Virginie Neirinckx","doi":"10.1038/s41698-025-00830-y","DOIUrl":"10.1038/s41698-025-00830-y","url":null,"abstract":"High-grade gliomas (HGG) are incurable brain malignancies in children and adults. Breakthrough advances in transcriptomic technologies unveiled the intricate diversity of cellular states and their spatial organization within HGGs. We qualitatively integrated 55 neoplastic transcriptomic signatures described in 17 single-cell and spatial RNA sequencing-based studies. Our review delineates a spectrum of cellular states, represented by the expression of specific genes, which can be conceptualized along a \"reactive-developmental programs\" axis. Additionally, we discussed the potential cues influencing these cellular states, including how spatial organization may impact transcriptomic dynamics. Leveraging these insightful discoveries, we discussed a novel, evolutive way to integrate the different transcriptomic signatures in two or three dimensions, incorporating developmental states, their proliferative capacity, and their possible transition towards reactive states. This integrated analysis illuminates the diverse cellular landscape of HGGs and provides a valuable resource for further elucidation of malignant mechanisms, and for the design of therapeutic endeavors.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"44"},"PeriodicalIF":6.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11814291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143399733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RevCAR-mediated T-cell response against PD-L1-expressing cells turns suppression into activation.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-09 DOI: 10.1038/s41698-025-00828-6

Eugenia Crespo, Liliana R Loureiro, Antonia Stammberger, Lydia Hoffmann, Nicole Berndt, Anja Hoffmann, Claudia Dagostino, Karla E G Soto, Luise Rupp, Claudia Arndt, Martin Schneider, Claudia R Ball, Michael Bachmann, Marc Schmitz, Anja Feldmann

{"title":"RevCAR-mediated T-cell response against PD-L1-expressing cells turns suppression into activation.","authors":"Eugenia Crespo, Liliana R Loureiro, Antonia Stammberger, Lydia Hoffmann, Nicole Berndt, Anja Hoffmann, Claudia Dagostino, Karla E G Soto, Luise Rupp, Claudia Arndt, Martin Schneider, Claudia R Ball, Michael Bachmann, Marc Schmitz, Anja Feldmann","doi":"10.1038/s41698-025-00828-6","DOIUrl":"10.1038/s41698-025-00828-6","url":null,"abstract":"Applying CAR T-cell therapy to treat solid tumors is especially challenging due to the immunosuppressive tumor microenvironment (TME). While our modular RevCAR system enhances the safety and controllability of CAR T-cell therapy, effectively targeting solid tumors remains difficult. Since PD-L1 is an immune checkpoint frequently upregulated by cancer cells and their microenvironment, it is a relevant target for solid tumors. Here, we introduce a novel PD-L1 RevTM capable of redirecting RevCAR T-cells to specifically target and kill PD-L1-expressing tumor cells, becoming activated and secreting pro-inflammatory cytokines. This is shown in vitro with monolayer and 3D models, including patient-derived cultures, and in vivo. Furthermore, we demonstrate in vitro and in vivo an AND-gated targeting of cells simultaneously expressing PD-L1 and another tumor-associated antigen by the Dual RevCAR system. Our findings suggest that RevCAR-mediated targeting of PD-L1 could be a promising therapeutic approach for modulating the TME and improving solid tumor treatment.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"42"},"PeriodicalIF":6.8,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11808103/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143382928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Streptococcus lutetiensis inhibits CD8⁺ IL17A⁺ TRM cells and leads to gastric cancer progression and poor prognosis.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-09 DOI: 10.1038/s41698-025-00810-2

Huiyu Wang, Wenhua You, Zining Zhu, Yuhan Zhang, Chupeng Hu, Jinying Lu, Yeding Huang, Rui Peng, Ruimin Shan, Ran Li, Yun Chen, Fuzhen Qi, Feng Yan, Qiang Zhan

{"title":"Streptococcus lutetiensis inhibits CD8+ IL17A+ TRM cells and leads to gastric cancer progression and poor prognosis.","authors":"Huiyu Wang, Wenhua You, Zining Zhu, Yuhan Zhang, Chupeng Hu, Jinying Lu, Yeding Huang, Rui Peng, Ruimin Shan, Ran Li, Yun Chen, Fuzhen Qi, Feng Yan, Qiang Zhan","doi":"10.1038/s41698-025-00810-2","DOIUrl":"10.1038/s41698-025-00810-2","url":null,"abstract":"In many solid tumours, including gastric cancer (GC), the beginning and progression of the tumour are closely correlated with the tumour microbiome. Here, we show the changes in the gastric microbiota and their influence on immune regulation and the promotion of GC progression through 16s rRNA sequencing and single cell RNA sequencing. Streptococcus lutetiensis (S. lutetiensis) was found to be enriched in the tumour tissues of GC patients. Further analysis using single-cell sequencing and flow cytometry showed that S. lutetiensis notably affects the antitumour immunity by suppressing IL17 signalling and reducing the population of CD8+IL17A+ tissue-resident memory T (TRM) cells by activating Nrf2-mediated oxidative stress response. Mouse models confirm S. lutetiensis promotes GC progression by impairing immune responses in CD8+IL17A+TRM cells, suggesting it as a potential GC prognosis indicator and immunotherapy target, highlighting the microbiome's role in cancer progression.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"43"},"PeriodicalIF":6.8,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11808082/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143382931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Molecular characterization of mixed-histology endometrial carcinoma provides prognostic and therapeutic value over morphologic findings.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-08 DOI: 10.1038/s41698-025-00803-1

Paulina J Haight, Ashwini Esnakula, Courtney J Riedinger, Adrian A Suarez, Jessica Gillespie, Ashley Patton, Alexis Chassen, David E Cohn, Casey M Cosgrove

{"title":"Molecular characterization of mixed-histology endometrial carcinoma provides prognostic and therapeutic value over morphologic findings.","authors":"Paulina J Haight, Ashwini Esnakula, Courtney J Riedinger, Adrian A Suarez, Jessica Gillespie, Ashley Patton, Alexis Chassen, David E Cohn, Casey M Cosgrove","doi":"10.1038/s41698-025-00803-1","DOIUrl":"10.1038/s41698-025-00803-1","url":null,"abstract":"We performed molecular analysis of a single-institution cohort of clinically diagnosed mixed-histology endometrial carcinoma (MEC). A gynecologic pathologist confirmed that 72 cases met diagnostic criteria for MEC based on WHO 2020 guidelines, and these were molecularly classified using both a DNA-based and histologic approach. Tumors were classified as: POLE-mutated (13.9%), microsatellite instability (MSI)-high/mismatch repair deficient (MMRd) (26.4%), TP53/p53 abnormal (p53abnl) (48.6%), no specific molecular profile (NSMP) (11.1%). Recurrence risk significantly differed based upon molecular class, but not histology. 44% of MEC cases had a HER2 IHC score of 2-3+, and this was not limited to p53abnl tumors. Transcriptional analysis demonstrated 93 differentially expressed genes between p53abnl and NSMP tumors, including many associated with the innate immune response and DNA damage repair. While p53abnl and NSMP tumors have similarly poor outcomes, transcriptome analysis revealed biologic differences that could impact targeted therapeutics in this high-risk group.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"41"},"PeriodicalIF":6.8,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143374489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An automatic pipeline for temporal monitoring of radiotherapy-induced toxicities in head and neck cancer patients.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-02-07 DOI: 10.1038/s41698-025-00824-w

Parsa Bagherzadeh, Khalil Sultanem, Gerald Batist, Shirin Abbasinejad Enger

{"title":"An automatic pipeline for temporal monitoring of radiotherapy-induced toxicities in head and neck cancer patients.","authors":"Parsa Bagherzadeh, Khalil Sultanem, Gerald Batist, Shirin Abbasinejad Enger","doi":"10.1038/s41698-025-00824-w","DOIUrl":"10.1038/s41698-025-00824-w","url":null,"abstract":"Radiotherapy for head and neck cancer often causes a spectrum of toxicities. Such toxicities are usually unavailable as structured data and are reported within textual clinical reports. To reduce the burden of manual assessment of toxicities, we propose a language processing model for the automatic extraction of toxicities. The cohort consists of 384 patients with head and neck cancer who underwent radiotherapy, either as monotherapy or in combination with chemotherapy or surgery. A total of 3510 notes were extracted. The toxicities were then manually annotated. Two tasks of toxicity mention detection and toxicity extraction were defined. Pre-trained language models such as BERT, Clinical BioBERT, and Clinical Longformer were fine-tuned. Our best model achieves an F1 score of 90% for automatic extraction of toxicity mentions. An automatic system enables real-time extraction of toxicities and insights into their temporal patterns, offering actionable data to support dose optimization and minimize toxicities in personalized treatments.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"40"},"PeriodicalIF":6.8,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11805912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143370828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0