Pub Date : 2024-09-10DOI: 10.1038/s41698-024-00701-y
Jacob J. Adashek, Max Brodsky, Mark J. Levis
The cytogenetic abnormality inv(2)(p23q13) in acute myeloid leukemia (AML) results in a fusion of RANBP2 with ALK. This fusion makes ALK constitutively active and acts as a driver for the proliferation of AML cell lines. Gilteritinib, a FLT3 inhibitor approved in AML, also can inhibit ALK among other receptor tyrosine kinases. A 75-year-old-woman with a history of essential thrombocythemia (ET) and a presumed germline DDX41 mutation developed ALK-fusion positive AML and despite standard therapies was transfusion-dependent and globally declining. The patient has been on gilteritinib with an ongoing response of more than one year with near normal blood counts and no evidence of AML. The fact that she was found to harbor a presumed germline DDX41 alteration may account for why she developed, and yet survived, two myeloid neoplasms (ET and AML). Additionally, this demonstrates that gilteritinib is clinically active as an ALK inhibitor, and could be considered for use in any AML patient presenting with an inv(2(p23q13)) translocation. Finally, it is an example of using a disease-agnostic, precision medicine approach to arrive at a beneficial treatment.
{"title":"Complete morphologic response to gilteritinib in ALK-rearranged acute myeloid leukemia","authors":"Jacob J. Adashek, Max Brodsky, Mark J. Levis","doi":"10.1038/s41698-024-00701-y","DOIUrl":"10.1038/s41698-024-00701-y","url":null,"abstract":"The cytogenetic abnormality inv(2)(p23q13) in acute myeloid leukemia (AML) results in a fusion of RANBP2 with ALK. This fusion makes ALK constitutively active and acts as a driver for the proliferation of AML cell lines. Gilteritinib, a FLT3 inhibitor approved in AML, also can inhibit ALK among other receptor tyrosine kinases. A 75-year-old-woman with a history of essential thrombocythemia (ET) and a presumed germline DDX41 mutation developed ALK-fusion positive AML and despite standard therapies was transfusion-dependent and globally declining. The patient has been on gilteritinib with an ongoing response of more than one year with near normal blood counts and no evidence of AML. The fact that she was found to harbor a presumed germline DDX41 alteration may account for why she developed, and yet survived, two myeloid neoplasms (ET and AML). Additionally, this demonstrates that gilteritinib is clinically active as an ALK inhibitor, and could be considered for use in any AML patient presenting with an inv(2(p23q13)) translocation. Finally, it is an example of using a disease-agnostic, precision medicine approach to arrive at a beneficial treatment.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00701-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165809","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}
Pub Date : 2024-09-09DOI: 10.1038/s41698-024-00698-4
Subotheni Thavaneswaran, Frank Lin, John P. Grady, David Espinoza, Min Li Huang, Sarah Chinchen, Lucille Sebastian, Maya Kansara, Tony Mersiades, Chee Khoon Lee, Jayesh Desai, Peter Grimison, Michael Brown, Michael Millward, Rosemary Harrup, Ken O’Byrne, Adnan Nagrial, Paul Craft, John Simes, Anthony M. Joshua, David M. Thomas
This single-arm phase II non-randomised trial (ACTRN12619001265167) evaluated trastuzumab emtansine in solid cancers with HER2 amplification or mutation detected by comprehensive genomic profiling. The primary objective was objective response (OR), while secondary objectives included the time to progression (TTP) on study to TTP on prior therapy ratio, progression-free survival (PFS) and overall survival (OS). The cohort included 16 tumours with HER2 mutations (group 1) and 16 with HER2 amplification (group 2). After 17 months median follow-up, ORs occurred in 19% of group 1 (1 salivary gland carcinoma (SGC), 2 lung cancers) and 25% of group 2 (3 SGCs, 1 uterine carcinoma). Fourteen of 29 TTP-evaluable patients achieved a TTP ratio ≥1.3, including 10 without an OR. Median PFS and OS were 4.5 (95% CI 2.1–7.0) and 18.2 months (95% CI 8.1-not reached) respectively. Trastuzumab emtansine showed modest ORs and a favourable change in disease trajectory in select HER2-altered solid cancers.
这项单臂 II 期非随机试验（ACTRN12619001265167）评估了曲妥珠单抗埃坦辛在综合基因组图谱检测到 HER2 扩增或突变的实体瘤中的应用。首要目标是客观反应（OR），次要目标包括研究进展时间（TTP）与既往治疗进展时间（TTP）之比、无进展生存期（PFS）和总生存期（OS）。队列中包括16个HER2突变肿瘤（第1组）和16个HER2扩增肿瘤（第2组）。经过17个月的中位随访，19%的第1组（1例唾液腺癌（SGC）、2例肺癌）和25%的第2组（3例SGC、1例子宫癌）发生了OR。29例TTP有效患者中有14例的TTP比值≥1.3，其中10例无OR。中位 PFS 和 OS 分别为 4.5 个月（95% CI 2.1-7.0）和 18.2 个月（95% CI 8.1-未达到）。曲妥珠单抗埃坦新（Trastuzumab emtansine）在部分HER2改变的实体瘤中显示出适度的ORs和有利的疾病轨迹变化。
{"title":"A signal-seeking phase 2 study of Trastuzumab emtansine in tumours harbouring HER2 amplification or mutation","authors":"Subotheni Thavaneswaran, Frank Lin, John P. Grady, David Espinoza, Min Li Huang, Sarah Chinchen, Lucille Sebastian, Maya Kansara, Tony Mersiades, Chee Khoon Lee, Jayesh Desai, Peter Grimison, Michael Brown, Michael Millward, Rosemary Harrup, Ken O’Byrne, Adnan Nagrial, Paul Craft, John Simes, Anthony M. Joshua, David M. Thomas","doi":"10.1038/s41698-024-00698-4","DOIUrl":"10.1038/s41698-024-00698-4","url":null,"abstract":"This single-arm phase II non-randomised trial (ACTRN12619001265167) evaluated trastuzumab emtansine in solid cancers with HER2 amplification or mutation detected by comprehensive genomic profiling. The primary objective was objective response (OR), while secondary objectives included the time to progression (TTP) on study to TTP on prior therapy ratio, progression-free survival (PFS) and overall survival (OS). The cohort included 16 tumours with HER2 mutations (group 1) and 16 with HER2 amplification (group 2). After 17 months median follow-up, ORs occurred in 19% of group 1 (1 salivary gland carcinoma (SGC), 2 lung cancers) and 25% of group 2 (3 SGCs, 1 uterine carcinoma). Fourteen of 29 TTP-evaluable patients achieved a TTP ratio ≥1.3, including 10 without an OR. Median PFS and OS were 4.5 (95% CI 2.1–7.0) and 18.2 months (95% CI 8.1-not reached) respectively. Trastuzumab emtansine showed modest ORs and a favourable change in disease trajectory in select HER2-altered solid cancers.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00698-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165820","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}
Real-time and accurate guidance for tumor resection has long been anticipated by surgeons. In the past decade, the flourishing material science has made impressive progress in near-infrared fluorophores that may fulfill this purpose. Fluorescence imaging-guided surgery shows great promise for clinical application and has undergone widespread evaluations, though it still requires continuous improvements to transition this technique from bench to bedside. Concurrently, the rapid progress of artificial intelligence (AI) has revolutionized medicine, aiding in the screening, diagnosis, and treatment of human doctors. Incorporating AI helps enhance fluorescence imaging and is poised to bring major innovations to surgical guidance, thereby realizing precision cancer surgery. This review provides an overview of the principles and clinical evaluations of fluorescence-guided surgery. Furthermore, recent endeavors to synergize AI with fluorescence imaging were presented, and the benefits of this interdisciplinary convergence were discussed. Finally, several implementation strategies to overcome technical hurdles were proposed to encourage and inspire future research to expedite the clinical application of these revolutionary technologies.
{"title":"Illuminating the future of precision cancer surgery with fluorescence imaging and artificial intelligence convergence","authors":"Han Cheng, Hongtao Xu, Boyang Peng, Xiaojuan Huang, Yongjie Hu, Chongyang Zheng, Zhiyuan Zhang","doi":"10.1038/s41698-024-00699-3","DOIUrl":"10.1038/s41698-024-00699-3","url":null,"abstract":"Real-time and accurate guidance for tumor resection has long been anticipated by surgeons. In the past decade, the flourishing material science has made impressive progress in near-infrared fluorophores that may fulfill this purpose. Fluorescence imaging-guided surgery shows great promise for clinical application and has undergone widespread evaluations, though it still requires continuous improvements to transition this technique from bench to bedside. Concurrently, the rapid progress of artificial intelligence (AI) has revolutionized medicine, aiding in the screening, diagnosis, and treatment of human doctors. Incorporating AI helps enhance fluorescence imaging and is poised to bring major innovations to surgical guidance, thereby realizing precision cancer surgery. This review provides an overview of the principles and clinical evaluations of fluorescence-guided surgery. Furthermore, recent endeavors to synergize AI with fluorescence imaging were presented, and the benefits of this interdisciplinary convergence were discussed. Finally, several implementation strategies to overcome technical hurdles were proposed to encourage and inspire future research to expedite the clinical application of these revolutionary technologies.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00699-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142165824","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}
Pub Date : 2024-09-08DOI: 10.1038/s41698-024-00693-9
Zhao Sun, Hao Liu, Qian Zhao, Jie-Han Li, San-Fei Peng, Zhen Zhang, Jing-Hua Yang, Yang Fu
Regulated cell death (RCD) plays a crucial role in the immune microenvironment, development, and progression of hepatocellular carcinoma (HCC). However, reliable immune-related cell death signatures have not been explored. In this study, we collected 12 RCD modes (e.g., apoptosis, ferroptosis, and cuproptosis), including 1078 regulators, to identify immune-related cell death genes based on HCC immune subgroups. Using a developed competitive machine learning framework, nine genes were screened to construct the immune-related cell death index (IRCDI), which is available for online application. Multi-omics data, along with clinical features, were analyzed to explore the HCC malignant heterogeneity. To validate the efficacy of this model, more than 18 independent cohorts, including survival and diverse treatment cohorts and datasets, were utilized. These findings were further validated using in-house samples and molecular biological experiments. Overall, the IRCDI may have a wide application in individual therapeutic decision-making and improving outcomes for HCC patients.
{"title":"Immune-related cell death index and its application for hepatocellular carcinoma","authors":"Zhao Sun, Hao Liu, Qian Zhao, Jie-Han Li, San-Fei Peng, Zhen Zhang, Jing-Hua Yang, Yang Fu","doi":"10.1038/s41698-024-00693-9","DOIUrl":"10.1038/s41698-024-00693-9","url":null,"abstract":"Regulated cell death (RCD) plays a crucial role in the immune microenvironment, development, and progression of hepatocellular carcinoma (HCC). However, reliable immune-related cell death signatures have not been explored. In this study, we collected 12 RCD modes (e.g., apoptosis, ferroptosis, and cuproptosis), including 1078 regulators, to identify immune-related cell death genes based on HCC immune subgroups. Using a developed competitive machine learning framework, nine genes were screened to construct the immune-related cell death index (IRCDI), which is available for online application. Multi-omics data, along with clinical features, were analyzed to explore the HCC malignant heterogeneity. To validate the efficacy of this model, more than 18 independent cohorts, including survival and diverse treatment cohorts and datasets, were utilized. These findings were further validated using in-house samples and molecular biological experiments. Overall, the IRCDI may have a wide application in individual therapeutic decision-making and improving outcomes for HCC patients.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00693-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142152370","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}
Pub Date : 2024-09-07DOI: 10.1038/s41698-024-00666-y
Chao You, Guan-Hua Su, Xu Zhang, Yi Xiao, Ren-Cheng Zheng, Shi-Yun Sun, Jia-Yin Zhou, Lu-Yi Lin, Ze-Zhou Wang, He Wang, Yan Chen, Wei-Jun Peng, Yi-Zhou Jiang, Zhi-Ming Shao, Ya-Jia Gu
Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model’s biological implications. DUKE cohort (n = 619) and I-SPY1 cohort (n = 128) were used to test the performance of the radiomic signature in outcome prediction. A thirteen-feature radiomic signature was identified in the FUSCC cohort training set and validated in the FUSCC cohort testing set, DUKE cohort and I-SPY1 cohort for predicting relapse-free survival (RFS) and overall survival (OS) (RFS: p = 0.013, p = 0.024 and p = 0.035; OS: p = 0.036, p = 0.005 and p = 0.027 in the three cohorts). Multiomic analysis uncovered metabolic dysregulation underlying the radiomic signature (ATP metabolic process: NES = 1.84, p-adjust = 0.02; cholesterol biosynthesis: NES = 1.79, p-adjust = 0.01). Regarding the therapeutic implications, the radiomic signature exhibited value when combining clinical factors for predicting the pathological complete response to neoadjuvant chemotherapy (DUKE cohort, AUC = 0.72; I-SPY1 cohort, AUC = 0.73). In conclusion, our study identified a breast cancer outcome-predicting radiomic signature in a multicenter radio-multiomic study, along with its correlations with multiomic features in prognostic risk assessment, laying the groundwork for future prospective clinical trials in personalized risk stratification and precision therapy.
{"title":"Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection","authors":"Chao You, Guan-Hua Su, Xu Zhang, Yi Xiao, Ren-Cheng Zheng, Shi-Yun Sun, Jia-Yin Zhou, Lu-Yi Lin, Ze-Zhou Wang, He Wang, Yan Chen, Wei-Jun Peng, Yi-Zhou Jiang, Zhi-Ming Shao, Ya-Jia Gu","doi":"10.1038/s41698-024-00666-y","DOIUrl":"10.1038/s41698-024-00666-y","url":null,"abstract":"Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model’s biological implications. DUKE cohort (n = 619) and I-SPY1 cohort (n = 128) were used to test the performance of the radiomic signature in outcome prediction. A thirteen-feature radiomic signature was identified in the FUSCC cohort training set and validated in the FUSCC cohort testing set, DUKE cohort and I-SPY1 cohort for predicting relapse-free survival (RFS) and overall survival (OS) (RFS: p = 0.013, p = 0.024 and p = 0.035; OS: p = 0.036, p = 0.005 and p = 0.027 in the three cohorts). Multiomic analysis uncovered metabolic dysregulation underlying the radiomic signature (ATP metabolic process: NES = 1.84, p-adjust = 0.02; cholesterol biosynthesis: NES = 1.79, p-adjust = 0.01). Regarding the therapeutic implications, the radiomic signature exhibited value when combining clinical factors for predicting the pathological complete response to neoadjuvant chemotherapy (DUKE cohort, AUC = 0.72; I-SPY1 cohort, AUC = 0.73). In conclusion, our study identified a breast cancer outcome-predicting radiomic signature in a multicenter radio-multiomic study, along with its correlations with multiomic features in prognostic risk assessment, laying the groundwork for future prospective clinical trials in personalized risk stratification and precision therapy.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00666-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146087","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}
Pub Date : 2024-09-06DOI: 10.1038/s41698-024-00689-5
Ziwen Fan, Dominic Edelmann, Tanwei Yuan, Bruno Christian Köhler, Michael Hoffmeister, Hermann Brenner
While genome-wide association studies are valuable in identifying CRC survival predictors, the benefit of adding blood DNA methylation (blood-DNAm) to clinical features, including the TNM system, remains unclear. In a multi-site population-based patient cohort study of 2116 CRC patients with baseline blood-DNAm, we analyzed survival predictions using eXtreme Gradient Boosting with a 5-fold nested leave-sites-out cross-validation across four groups: traditional and comprehensive clinical features, blood-DNAm, and their combination. Model performance was assessed using time-dependent ROC curves and calibrations. During a median follow-up of 10.3 years, 1166 patients died. Although blood-DNAm-based predictive signatures achieved moderate performances, predictive signatures based on clinical features outperformed blood-DNAm signatures. The inclusion of blood-DNAm did not improve survival prediction over clinical features. M1 stage, age at blood collection, and N2 stage were the top contributors. Despite some prognostic value, incorporating blood DNA methylation did not enhance survival prediction of CRC patients beyond clinical features.
{"title":"Developing survival prediction models in colorectal cancer using epigenome-wide DNA methylation data from whole blood","authors":"Ziwen Fan, Dominic Edelmann, Tanwei Yuan, Bruno Christian Köhler, Michael Hoffmeister, Hermann Brenner","doi":"10.1038/s41698-024-00689-5","DOIUrl":"10.1038/s41698-024-00689-5","url":null,"abstract":"While genome-wide association studies are valuable in identifying CRC survival predictors, the benefit of adding blood DNA methylation (blood-DNAm) to clinical features, including the TNM system, remains unclear. In a multi-site population-based patient cohort study of 2116 CRC patients with baseline blood-DNAm, we analyzed survival predictions using eXtreme Gradient Boosting with a 5-fold nested leave-sites-out cross-validation across four groups: traditional and comprehensive clinical features, blood-DNAm, and their combination. Model performance was assessed using time-dependent ROC curves and calibrations. During a median follow-up of 10.3 years, 1166 patients died. Although blood-DNAm-based predictive signatures achieved moderate performances, predictive signatures based on clinical features outperformed blood-DNAm signatures. The inclusion of blood-DNAm did not improve survival prediction over clinical features. M1 stage, age at blood collection, and N2 stage were the top contributors. Despite some prognostic value, incorporating blood DNA methylation did not enhance survival prediction of CRC patients beyond clinical features.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00689-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140686","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}
Pub Date : 2024-09-06DOI: 10.1038/s41698-024-00682-y
Ricardo Rivera-Soto, Benjamin Henley, Marian A. Pulgar, Stacey L. Lehman, Himanshu Gupta, Kia Z. Perez-Vale, Megan Weindorfer, Smruthi Vijayaraghavan, Tsun-Wen Sheena Yao, Sylvie Laquerre, Sheri L. Moores
Amivantamab is an FDA-approved bispecific antibody targeting EGF and Met receptors, with clinical activity against EGFR mutant non-small cell lung cancer (NSCLC). Amivantamab efficacy has been demonstrated to be linked to three mechanisms of action (MOA): immune cell-mediated killing, receptor internalization and degradation, and inhibition of ligand binding to both EGFR and Met receptors. Among the EGFR ligands, we demonstrated that amphiregulin (AREG) is highly expressed in wild-type (WT) EGFR (EGFRWT) NSCLC primary tumors, with significantly higher circulating protein levels in NSCLC patients than in healthy volunteers. Treatment of AREG-stimulated EGFRWT cells/tumors with amivantamab or with an AREG-targeting antibody inhibited ligand-induced signaling and cell/tumor proliferation/growth. Across 11 EGFRWT NSCLC patient-derived xenograft models, amivantamab efficacy correlated with AREG RNA levels. Interestingly, in these models, amivantamab anti-tumor activity was independent of Fc engagement with immune cells, suggesting that, in this context, the ligand-blocking function is sufficient for amivantamab maximal efficacy. Finally, we demonstrated that in lung adenocarcinoma patients, high expression of AREG and EGFR mutations were mutually exclusive. In conclusion, these data 1) highlight EGFR ligand AREG as a driver of tumor growth in some EGFRWT NSCLC models, 2) illustrate the preclinical efficacy of amivantamab in ligand-driven EGFRWT NSCLC, and 3) identify AREG as a potential predictive biomarker for amivantamab activity in EGFRWT NSCLC.
{"title":"Amivantamab efficacy in wild-type EGFR NSCLC tumors correlates with levels of ligand expression","authors":"Ricardo Rivera-Soto, Benjamin Henley, Marian A. Pulgar, Stacey L. Lehman, Himanshu Gupta, Kia Z. Perez-Vale, Megan Weindorfer, Smruthi Vijayaraghavan, Tsun-Wen Sheena Yao, Sylvie Laquerre, Sheri L. Moores","doi":"10.1038/s41698-024-00682-y","DOIUrl":"10.1038/s41698-024-00682-y","url":null,"abstract":"Amivantamab is an FDA-approved bispecific antibody targeting EGF and Met receptors, with clinical activity against EGFR mutant non-small cell lung cancer (NSCLC). Amivantamab efficacy has been demonstrated to be linked to three mechanisms of action (MOA): immune cell-mediated killing, receptor internalization and degradation, and inhibition of ligand binding to both EGFR and Met receptors. Among the EGFR ligands, we demonstrated that amphiregulin (AREG) is highly expressed in wild-type (WT) EGFR (EGFRWT) NSCLC primary tumors, with significantly higher circulating protein levels in NSCLC patients than in healthy volunteers. Treatment of AREG-stimulated EGFRWT cells/tumors with amivantamab or with an AREG-targeting antibody inhibited ligand-induced signaling and cell/tumor proliferation/growth. Across 11 EGFRWT NSCLC patient-derived xenograft models, amivantamab efficacy correlated with AREG RNA levels. Interestingly, in these models, amivantamab anti-tumor activity was independent of Fc engagement with immune cells, suggesting that, in this context, the ligand-blocking function is sufficient for amivantamab maximal efficacy. Finally, we demonstrated that in lung adenocarcinoma patients, high expression of AREG and EGFR mutations were mutually exclusive. In conclusion, these data 1) highlight EGFR ligand AREG as a driver of tumor growth in some EGFRWT NSCLC models, 2) illustrate the preclinical efficacy of amivantamab in ligand-driven EGFRWT NSCLC, and 3) identify AREG as a potential predictive biomarker for amivantamab activity in EGFRWT NSCLC.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00682-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146086","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}
Pub Date : 2024-09-05DOI: 10.1038/s41698-024-00672-0
Lorena Incorvaia, Tancredi Didier Bazan Russo, Valerio Gristina, Alessandro Perez, Chiara Brando, Clarissa Mujacic, Emilia Di Giovanni, Marco Bono, Silvia Contino, Carla Ferrante Bannera, Maria Concetta Vitale, Andrea Gottardo, Marta Peri, Antonio Galvano, Daniele Fanale, Giuseppe Badalamenti, Antonio Russo, Viviana Bazan
Homologous recombination (HR) and mismatch repair (MMR) defects are driver mutational imprints and actionable biomarkers in DNA repair-defective tumors. Although usually thought as mutually exclusive pathways, recent preclinical and clinical research provide preliminary evidence of a functional crosslink and crosstalk between HRR and MMR. Shared core proteins are identified as key players in both pathways, broadening the concept of DNA repair mechanism exclusivity in specific tumor types. These observations may result in unexplored forms of synthetic lethality or hypermutable tumor phenotypes, potentially impacting the cancer risk management, and considerably expanding in the future the therapeutic window for DNA repair-defective tumors.
同源重组（HR）和错配修复（MMR）缺陷是 DNA 修复缺陷肿瘤的突变驱动因素和可操作的生物标记物。尽管人们通常认为两者是相互排斥的途径，但最近的临床前和临床研究提供了初步证据，证明HRR和MMR之间存在功能性交叉联系和相互影响。共同的核心蛋白被确定为这两种途径中的关键角色，从而拓宽了特定肿瘤类型中 DNA 修复机制排他性的概念。这些观察结果可能会导致尚未探索的合成致死或超可变肿瘤表型，从而对癌症风险管理产生潜在影响，并在未来大大扩展 DNA 修复缺陷肿瘤的治疗窗口。
{"title":"The intersection of homologous recombination (HR) and mismatch repair (MMR) pathways in DNA repair-defective tumors","authors":"Lorena Incorvaia, Tancredi Didier Bazan Russo, Valerio Gristina, Alessandro Perez, Chiara Brando, Clarissa Mujacic, Emilia Di Giovanni, Marco Bono, Silvia Contino, Carla Ferrante Bannera, Maria Concetta Vitale, Andrea Gottardo, Marta Peri, Antonio Galvano, Daniele Fanale, Giuseppe Badalamenti, Antonio Russo, Viviana Bazan","doi":"10.1038/s41698-024-00672-0","DOIUrl":"10.1038/s41698-024-00672-0","url":null,"abstract":"Homologous recombination (HR) and mismatch repair (MMR) defects are driver mutational imprints and actionable biomarkers in DNA repair-defective tumors. Although usually thought as mutually exclusive pathways, recent preclinical and clinical research provide preliminary evidence of a functional crosslink and crosstalk between HRR and MMR. Shared core proteins are identified as key players in both pathways, broadening the concept of DNA repair mechanism exclusivity in specific tumor types. These observations may result in unexplored forms of synthetic lethality or hypermutable tumor phenotypes, potentially impacting the cancer risk management, and considerably expanding in the future the therapeutic window for DNA repair-defective tumors.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00672-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140687","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}
Pub Date : 2024-09-05DOI: 10.1038/s41698-024-00684-w
Jordan Phillipps, George Nassief, Renee Morecroft, Tolulope Adeyelu, Andrew Elliott, Farah Abdulla, Ari Vanderwalde, Soo Park, Omar Butt, Alice Zhou, George Ansstas
Modern advancements in targeted therapy and immunotherapy have significantly improved survival outcomes for advanced melanoma; however, there remains a need for novel approaches to overcome disease progression and treatment resistance. In recent years, PARPi therapy has shown great promise both as a single regimen and in combination with other therapeutics in melanoma. Here, we describe three unique cases of advanced BRAF V600 mutated melanoma that progressed on targeted BRAF/MEK agents that subsequently exhibited partial to near-complete responses to combinatory PARPi and BRAF/MEK inhibitors. This highlights both a potential synergy underlying this combinatory approach and its efficacy as a treatment option for patients with advanced melanoma refractory to targeted and/or immunotherapies. Prospective clinical trials are needed to explore this synergic effect in larger melanoma cohorts to investigate this combination for treating refractory advanced melanoma.
{"title":"Efficacy of PARP inhibitor therapy after targeted BRAF/MEK failure in advanced melanoma","authors":"Jordan Phillipps, George Nassief, Renee Morecroft, Tolulope Adeyelu, Andrew Elliott, Farah Abdulla, Ari Vanderwalde, Soo Park, Omar Butt, Alice Zhou, George Ansstas","doi":"10.1038/s41698-024-00684-w","DOIUrl":"10.1038/s41698-024-00684-w","url":null,"abstract":"Modern advancements in targeted therapy and immunotherapy have significantly improved survival outcomes for advanced melanoma; however, there remains a need for novel approaches to overcome disease progression and treatment resistance. In recent years, PARPi therapy has shown great promise both as a single regimen and in combination with other therapeutics in melanoma. Here, we describe three unique cases of advanced BRAF V600 mutated melanoma that progressed on targeted BRAF/MEK agents that subsequently exhibited partial to near-complete responses to combinatory PARPi and BRAF/MEK inhibitors. This highlights both a potential synergy underlying this combinatory approach and its efficacy as a treatment option for patients with advanced melanoma refractory to targeted and/or immunotherapies. Prospective clinical trials are needed to explore this synergic effect in larger melanoma cohorts to investigate this combination for treating refractory advanced melanoma.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11374802/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142133305","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}
Pub Date : 2024-09-05DOI: 10.1038/s41698-024-00695-7
Anthony Bozzo, Alex Hollingsworth, Subrata Chatterjee, Aditya Apte, Jiawen Deng, Simon Sun, William Tap, Ahmed Aoude, Sahir Bhatnagar, John H. Healey
The objective of this study is to develop a multimodal neural network (MMNN) model that analyzes clinical variables and MRI images of a soft tissue sarcoma (STS) patient, to predict overall survival and risk of distant metastases. We compare the performance of this MMNN to models based on clinical variables alone, radiomics models, and an unimodal neural network. We include patients aged 18 or older with biopsy-proven STS who underwent primary resection between January 1st, 2005, and December 31st, 2020 with complete outcome data and a pre-treatment MRI with both a T1 post-contrast sequence and a T2 fat-sat sequence available. A total of 9380 MRI slices containing sarcomas from 287 patients are available. Our MMNN accepts the entire 3D sarcoma volume from T1 and T2 MRIs and clinical variables. Gradient blending allows the clinical and image sub-networks to optimally converge without overfitting. Heat maps were generated to visualize the salient image features. Our MMNN outperformed all other models in predicting overall survival and the risk of distant metastases. The C-Index of our MMNN for overall survival is 0.77 and the C-Index for risk of distant metastases is 0.70. The provided heat maps demonstrate areas of sarcomas deemed most salient for predictions. Our multimodal neural network with gradient blending improves predictions of overall survival and risk of distant metastases in patients with soft tissue sarcoma. Future work enabling accurate subtype-specific predictions will likely utilize similar end-to-end multimodal neural network architecture and require prospective curation of high-quality data, the inclusion of genomic data, and the involvement of multiple centers through federated learning.
{"title":"A multimodal neural network with gradient blending improves predictions of survival and metastasis in sarcoma","authors":"Anthony Bozzo, Alex Hollingsworth, Subrata Chatterjee, Aditya Apte, Jiawen Deng, Simon Sun, William Tap, Ahmed Aoude, Sahir Bhatnagar, John H. Healey","doi":"10.1038/s41698-024-00695-7","DOIUrl":"10.1038/s41698-024-00695-7","url":null,"abstract":"The objective of this study is to develop a multimodal neural network (MMNN) model that analyzes clinical variables and MRI images of a soft tissue sarcoma (STS) patient, to predict overall survival and risk of distant metastases. We compare the performance of this MMNN to models based on clinical variables alone, radiomics models, and an unimodal neural network. We include patients aged 18 or older with biopsy-proven STS who underwent primary resection between January 1st, 2005, and December 31st, 2020 with complete outcome data and a pre-treatment MRI with both a T1 post-contrast sequence and a T2 fat-sat sequence available. A total of 9380 MRI slices containing sarcomas from 287 patients are available. Our MMNN accepts the entire 3D sarcoma volume from T1 and T2 MRIs and clinical variables. Gradient blending allows the clinical and image sub-networks to optimally converge without overfitting. Heat maps were generated to visualize the salient image features. Our MMNN outperformed all other models in predicting overall survival and the risk of distant metastases. The C-Index of our MMNN for overall survival is 0.77 and the C-Index for risk of distant metastases is 0.70. The provided heat maps demonstrate areas of sarcomas deemed most salient for predictions. Our multimodal neural network with gradient blending improves predictions of overall survival and risk of distant metastases in patients with soft tissue sarcoma. Future work enabling accurate subtype-specific predictions will likely utilize similar end-to-end multimodal neural network architecture and require prospective curation of high-quality data, the inclusion of genomic data, and the involvement of multiple centers through federated learning.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00695-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140684","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}
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