Pub Date : 2025-12-01Epub Date: 2025-10-23DOI: 10.1080/14796694.2025.2577629
Euclides Avila, Edgar Armando Méndez-Pérez, Lorenza Díaz, Janice García-Quiroz
Vasculogenic mimicry (VM) allows tumor cells to form vessel-like channels, promoting growth, metastasis, and therapy resistance. Persistent infection with high-risk human papillomavirus (HPV), mainly types 16 and 18, is a key factor in various cancers, including anogenital and head and neck cancers. VM has been documented in cervical cancer and oral squamous cell carcinoma (OSCC), but its role in other HPV-associated cancers remains unexplored. This review summarizes literature published between October 2024 and April 2025 in PubMed and Google Scholar, focusing on VM in HPV-related cancers. General mechanisms highlighted include epithelial-mesenchymal transition, hypoxia, and activation of STAT3 and PI3K/AKT pathways. Molecular regulators include TXNDC5, CHI3L1, erythropoietin, and microRNAs miR-124 and miR-29b in cervical cancer; and collagen XVI, LGR5, ALDH1, Beclin 1, VE-cadherin, CD44, HIF-1α, and SOX7 in OSCC. From a translational perspective, elucidating the molecular regulators of VM could reveal therapeutic opportunities through strategies targeting specific signaling pathways in tumor cells.
{"title":"Vasculogenic mimicry in human cancers associated with chronic high-risk human papillomavirus infection.","authors":"Euclides Avila, Edgar Armando Méndez-Pérez, Lorenza Díaz, Janice García-Quiroz","doi":"10.1080/14796694.2025.2577629","DOIUrl":"10.1080/14796694.2025.2577629","url":null,"abstract":"<p><p>Vasculogenic mimicry (VM) allows tumor cells to form vessel-like channels, promoting growth, metastasis, and therapy resistance. Persistent infection with high-risk human papillomavirus (HPV), mainly types 16 and 18, is a key factor in various cancers, including anogenital and head and neck cancers. VM has been documented in cervical cancer and oral squamous cell carcinoma (OSCC), but its role in other HPV-associated cancers remains unexplored. This review summarizes literature published between October 2024 and April 2025 in PubMed and Google Scholar, focusing on VM in HPV-related cancers. General mechanisms highlighted include epithelial-mesenchymal transition, hypoxia, and activation of STAT3 and PI3K/AKT pathways. Molecular regulators include TXNDC5, CHI3L1, erythropoietin, and microRNAs miR-124 and miR-29b in cervical cancer; and collagen XVI, LGR5, ALDH1, Beclin 1, VE-cadherin, CD44, HIF-1α, and SOX7 in OSCC. From a translational perspective, elucidating the molecular regulators of VM could reveal therapeutic opportunities through strategies targeting specific signaling pathways in tumor cells.</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3677-3689"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12674243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145344864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The unsatisfactory prognosis of patients with early-stage hepatocellular carcinoma (HCC) emphasizes the urgent need for perioperative treatment to reduce recurrence after surgery. The combination of transarterial chemoembolization (TACE), tyrosine kinase inhibitor (TKI), and programmed cell death protein 1 (PD-1) inhibitor has emerged as a promising treatment for unresectable HCC, yet its perioperative application was not explored. PERI-START is a prospective, single arm phase II trial which aims to investigate the efficacy and safety of TACE, tislelizumab (PD-1 inhibitor), and lenvatinib (TKI) in perioperative (neoadjuvant and adjuvant) use for resectable, high-risk HCC. Within 1 week after enrollment, TACE will be administered. Subsequently, intravenous tislelizumab will be given every 3 weeks in combination with daily oral lenvatinib. Unless disease progression occurs, liver resection will then be performed. 4-6 weeks after liver resection, tislelizumab and lenvatinib will be resumed for 6 months. The primary endpoint is the major pathological response (MPR) rate, with secondary endpoints including objective response rate (ORR), R0 resection rate, event-free survival (EFS), overall survival (OS), and adverse events (AEs).Clinical trial registration: ChiCTR2400085067 (www.chictr.org.cn).
{"title":"PERI-START: a phase II trial of perioperative TACE, tislelizumab, and lenvatinib in early-stage hepatocellular carcinoma.","authors":"Diao Kong, Yongcheng Tang, Yongjie Zhou, Jin Zhou, Chuan Li, Tianfu Wen, Wei Peng","doi":"10.1080/14796694.2025.2577625","DOIUrl":"10.1080/14796694.2025.2577625","url":null,"abstract":"<p><p>The unsatisfactory prognosis of patients with early-stage hepatocellular carcinoma (HCC) emphasizes the urgent need for perioperative treatment to reduce recurrence after surgery. The combination of transarterial chemoembolization (TACE), tyrosine kinase inhibitor (TKI), and programmed cell death protein 1 (PD-1) inhibitor has emerged as a promising treatment for unresectable HCC, yet its perioperative application was not explored. PERI-START is a prospective, single arm phase II trial which aims to investigate the efficacy and safety of TACE, tislelizumab (PD-1 inhibitor), and lenvatinib (TKI) in perioperative (neoadjuvant and adjuvant) use for resectable, high-risk HCC. Within 1 week after enrollment, TACE will be administered. Subsequently, intravenous tislelizumab will be given every 3 weeks in combination with daily oral lenvatinib. Unless disease progression occurs, liver resection will then be performed. 4-6 weeks after liver resection, tislelizumab and lenvatinib will be resumed for 6 months. The primary endpoint is the major pathological response (MPR) rate, with secondary endpoints including objective response rate (ORR), R0 resection rate, event-free survival (EFS), overall survival (OS), and adverse events (AEs).<b>Clinical trial registration:</b> ChiCTR2400085067 (www.chictr.org.cn).</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3611-3617"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12674328/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145344805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aims: To develop and validate a nomogram for predicting high - grade components in primary lung adenocarcinomas using tumor growth rate and clinical radiological characteristics.
Materials & methods: This retrospective study included 735 patients who underwent surgical resection for lung adenocarcinoma. Tumor segmentation was performed on two preoperative CT scans to calculate the specific growth rate (SGR), defined as the natural logarithm of 2 divided by the volume doubling time (VDT) of the tumor. A nomogram was constructed using multivariable logistic regression analysis with significant predictors.
Results: The nomogram included tumor volume, consolidation - to - tumor ratio (CTR), and SGR. The model showed excellent discrimination in the training cohort (AUC = 0.884), validation cohort (AUC = 0.910), and test cohort (AUC = 0.969). Decision curve analysis indicated a higher net benefit compared to imaging or growth models alone.
Conclusions: The nomogram, incorporating clinical and radiological characteristics with tumor growth metrics, accurately predicted high - grade components in primary lung adenocarcinomas. This tool may aid in preoperative planning and personalized treatment. Future work should focus on prospective multic - center validation and exploring automated segmentation methods.
{"title":"A clinical model for growth rate-driven prediction of histological subtypes in invasive pulmonary adenocarcinomas.","authors":"Feiyang Zhong, Zhenxing Liu, Lijun Wu, Wenping Li, Shaohong Zhao","doi":"10.1080/14796694.2025.2577628","DOIUrl":"10.1080/14796694.2025.2577628","url":null,"abstract":"<p><strong>Aims: </strong>To develop and validate a nomogram for predicting high - grade components in primary lung adenocarcinomas using tumor growth rate and clinical radiological characteristics.</p><p><strong>Materials & methods: </strong>This retrospective study included 735 patients who underwent surgical resection for lung adenocarcinoma. Tumor segmentation was performed on two preoperative CT scans to calculate the specific growth rate (SGR), defined as the natural logarithm of 2 divided by the volume doubling time (VDT) of the tumor. A nomogram was constructed using multivariable logistic regression analysis with significant predictors.</p><p><strong>Results: </strong>The nomogram included tumor volume, consolidation - to - tumor ratio (CTR), and SGR. The model showed excellent discrimination in the training cohort (AUC = 0.884), validation cohort (AUC = 0.910), and test cohort (AUC = 0.969). Decision curve analysis indicated a higher net benefit compared to imaging or growth models alone.</p><p><strong>Conclusions: </strong>The nomogram, incorporating clinical and radiological characteristics with tumor growth metrics, accurately predicted high - grade components in primary lung adenocarcinomas. This tool may aid in preoperative planning and personalized treatment. Future work should focus on prospective multic - center validation and exploring automated segmentation methods.</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3821-3832"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12688244/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145336812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1080/14796694.2025.2584284
Sikander Ailawadhi, Timothy J Inocencio, Carol Mansfield, Phani Chintakayala, Cooper Bussberg, Lei Chi, James Harnett, Glenn S Kroog, Karen Rodriguez-Lorenc, Jenny Ahlstrom, Qiufei Ma
{"title":"A plain language summary of patient preferences for treatments for multiple myeloma that has relapsed or is refractory to prior therapy.","authors":"Sikander Ailawadhi, Timothy J Inocencio, Carol Mansfield, Phani Chintakayala, Cooper Bussberg, Lei Chi, James Harnett, Glenn S Kroog, Karen Rodriguez-Lorenc, Jenny Ahlstrom, Qiufei Ma","doi":"10.1080/14796694.2025.2584284","DOIUrl":"10.1080/14796694.2025.2584284","url":null,"abstract":"","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3701-3711"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12688239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145648320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-21DOI: 10.1080/14796694.2025.2577631
Ruobing Li, Xinyou Su, Zhongyuan Li, Ning Wang, Haitao Sun, Aimei Ouyang
Aims: This retrospective study aimed to assess the potential of radiomic features extracted from dual-energy computed tomography (DECT) images, combined with machine learning algorithms, for the noninvasive prediction of microvessel density (MVD) in clear cell renal cell carcinoma (ccRCC).
Methods: We manually segmented regions of interest (ROIs) on corticomedullary phase (CMP) images to extract radiomic features. Tumor microvessel parameters were determined by immunohistochemical staining. Prediction models for MVD were developed using both multi-energy and monoenergetic sequence DECT images. Subsequently, a combined model was constructed based on the best-performing radiomics score and statistically significant clinical features, and was visualized as a nomogram. Furthermore, an external validation cohort was recruited from Center II to evaluate the performance of the nomogram.
Results: The support vector machine (SVM) classifier achieved the best performance for the multi-energy sequence MVD prediction model, with an AUC of 0.914 in the validation set. The MVD prediction model based on iodine-based material decomposition images (IMDI), constructed using the SVM classifier, achieved an AUC of 0.889 in the validation set. The nomogram showed good calibration, achieving an AUC of 0.757 in the external validation cohort.
Conclusions: DECT-based radiomic features show potential for noninvasive predicting microangiogenesis in patients with ccRCC.
{"title":"The predictive value of dual-energy computed tomography radiomics in microvessel of clear cell renal cell carcinoma.","authors":"Ruobing Li, Xinyou Su, Zhongyuan Li, Ning Wang, Haitao Sun, Aimei Ouyang","doi":"10.1080/14796694.2025.2577631","DOIUrl":"10.1080/14796694.2025.2577631","url":null,"abstract":"<p><strong>Aims: </strong>This retrospective study aimed to assess the potential of radiomic features extracted from dual-energy computed tomography (DECT) images, combined with machine learning algorithms, for the noninvasive prediction of microvessel density (MVD) in clear cell renal cell carcinoma (ccRCC).</p><p><strong>Methods: </strong>We manually segmented regions of interest (ROIs) on corticomedullary phase (CMP) images to extract radiomic features. Tumor microvessel parameters were determined by immunohistochemical staining. Prediction models for MVD were developed using both multi-energy and monoenergetic sequence DECT images. Subsequently, a combined model was constructed based on the best-performing radiomics score and statistically significant clinical features, and was visualized as a nomogram. Furthermore, an external validation cohort was recruited from Center II to evaluate the performance of the nomogram.</p><p><strong>Results: </strong>The support vector machine (SVM) classifier achieved the best performance for the multi-energy sequence MVD prediction model, with an AUC of 0.914 in the validation set. The MVD prediction model based on iodine-based material decomposition images (IMDI), constructed using the SVM classifier, achieved an AUC of 0.889 in the validation set. The nomogram showed good calibration, achieving an AUC of 0.757 in the external validation cohort.</p><p><strong>Conclusions: </strong>DECT-based radiomic features show potential for noninvasive predicting microangiogenesis in patients with ccRCC.</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3629-3638"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12674250/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145344793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-11-15DOI: 10.1080/14796694.2025.2567838
Paresh Vyas, Sam Salek, Susana Vives, Christian Recher, Hartmut Döhner, Adriano Venditti, Hélène Derrien, Stéphanie Chatin, Anne-Marie De La Bigne, Jana Pelouchova, Ralph Hills, Samantha Nier
Introduction: Ivosidenib is an inhibitor of mutant isocitrate dehydrogenase 1 (mIDH1) that is approved alone or in combination with azacitidine in patients with mIDH1 acute myeloid leukemia (AML) that are ineligible to receive intensive chemotherapy.
Aims: Here we describe the design of ALIDHE, an international, multicenter, single-arm, open-label Phase 3b study of ivosidenib + azacitidine for treatment of newly diagnosed mIDH1 AML in usual clinical practice.
Methods: The primary endpoints are adverse events (AEs), clinical laboratory anomalies assessed as AEs, patients requiring transfusion and number of units transfused, and infection rate. The impact of ivosidenib + azacitidine treatment on health-related quality of life, healthcare resource utilization and measurable residual disease will also be assessed.
{"title":"ALIDHE phase 3b study design: ivosidenib + azacitidine in adults with newly diagnosed <i>IDH1</i> mutant acute myeloid leukemia.","authors":"Paresh Vyas, Sam Salek, Susana Vives, Christian Recher, Hartmut Döhner, Adriano Venditti, Hélène Derrien, Stéphanie Chatin, Anne-Marie De La Bigne, Jana Pelouchova, Ralph Hills, Samantha Nier","doi":"10.1080/14796694.2025.2567838","DOIUrl":"10.1080/14796694.2025.2567838","url":null,"abstract":"<p><strong>Introduction: </strong>Ivosidenib is an inhibitor of mutant isocitrate dehydrogenase 1 (mIDH1) that is approved alone or in combination with azacitidine in patients with mIDH1 acute myeloid leukemia (AML) that are ineligible to receive intensive chemotherapy.</p><p><strong>Aims: </strong>Here we describe the design of ALIDHE, an international, multicenter, single-arm, open-label Phase 3b study of ivosidenib + azacitidine for treatment of newly diagnosed mIDH1 AML in usual clinical practice.</p><p><strong>Methods: </strong>The primary endpoints are adverse events (AEs), clinical laboratory anomalies assessed as AEs, patients requiring transfusion and number of units transfused, and infection rate. The impact of ivosidenib + azacitidine treatment on health-related quality of life, healthcare resource utilization and measurable residual disease will also be assessed.</p><p><strong>Clinical trial registration number: </strong>NCT05907057 (ClinicalTrials.gov).</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3721-3729"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12688220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145530681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-11-21DOI: 10.1080/14796694.2025.2591213
Friederike C Althoff, Fabian Acker, Sebastian Koschade, Sophie Heinzen, Lukas Aguinarte, Maximilian Rost, Hanna Schulte, Gernot Rohde, Melanie Winter, Waldemar Schreiner, Katrin Krause, Viktor Grünwald, Hubert Serve, Thomas Oellerich, Martin Sebastian
Perioperative chemoimmunotherapy improves pathological complete response (pCR), EFS, and OS in patients with resectable NSCLC versus chemotherapy, as shown in several phase-III-trials. However, approximately 17-22% of patients did not proceed to surgery, partly due to toxicity, highlighting the need for more efficacious and tolerable regimens. NeoTRACE is a phase II, multicenter, single-arm study to evaluate neoadjuvant sacituzumab govitecan (SG) and the PD-1 inhibitor zimberelimab (ZIM) in resectable stage II to IIIB (N2) NSCLC with no known EGFR/ALK alterations. The trial plans to enroll 50 participants, with neoadjuvant treatment administered for four cycles before resection, followed by adjuvant ZIM with/without SG at the physicians' discretion. The primary endpoint is the rate of pCR in tumor and lymph nodes. Secondary endpoints include major pathological response, surgical resection rate, disease-free survival, OS, safety, and quality of life. The study also explores circulating tumor DNA (ctDNA) dynamics, TROP2 expression, and spatial transcriptomics to identify biomarkers. NeoTRACE assesses a platinum-sparing approach in resectable NSCLC. Previous studies showed ADC and immunotherapy combinations are effective in advanced NSCLC, suggesting potential perioperative benefit. This study aims to improve pCR rate, reduce toxicity, enhance surgical eligibility, and personalize adjuvant treatment to improve long-term outcomes.Clinical Trial Registration: EudraCT: 2024-517561-16.
{"title":"Study design and rationale for the NeoTRACE trial: a multicenter phase II study of neoadjuvant sacituzumab govitecan plus zimberelimab followed by adjuvant zimberelimab with or without sacituzumab govitecan in patients with resectable non-small cell lung cancer.","authors":"Friederike C Althoff, Fabian Acker, Sebastian Koschade, Sophie Heinzen, Lukas Aguinarte, Maximilian Rost, Hanna Schulte, Gernot Rohde, Melanie Winter, Waldemar Schreiner, Katrin Krause, Viktor Grünwald, Hubert Serve, Thomas Oellerich, Martin Sebastian","doi":"10.1080/14796694.2025.2591213","DOIUrl":"10.1080/14796694.2025.2591213","url":null,"abstract":"<p><p>Perioperative chemoimmunotherapy improves pathological complete response (pCR), EFS, and OS in patients with resectable NSCLC versus chemotherapy, as shown in several phase-III-trials. However, approximately 17-22% of patients did not proceed to surgery, partly due to toxicity, highlighting the need for more efficacious and tolerable regimens. NeoTRACE is a phase II, multicenter, single-arm study to evaluate neoadjuvant sacituzumab govitecan (SG) and the PD-1 inhibitor zimberelimab (ZIM) in resectable stage II to IIIB (N2) NSCLC with no known EGFR/ALK alterations. The trial plans to enroll 50 participants, with neoadjuvant treatment administered for four cycles before resection, followed by adjuvant ZIM with/without SG at the physicians' discretion. The primary endpoint is the rate of pCR in tumor and lymph nodes. Secondary endpoints include major pathological response, surgical resection rate, disease-free survival, OS, safety, and quality of life. The study also explores circulating tumor DNA (ctDNA) dynamics, TROP2 expression, and spatial transcriptomics to identify biomarkers. NeoTRACE assesses a platinum-sparing approach in resectable NSCLC. Previous studies showed ADC and immunotherapy combinations are effective in advanced NSCLC, suggesting potential perioperative benefit. This study aims to improve pCR rate, reduce toxicity, enhance surgical eligibility, and personalize adjuvant treatment to improve long-term outcomes.<b>Clinical Trial Registration</b>: EudraCT: 2024-517561-16.</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"3749-3757"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12688237/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145563527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-12-16DOI: 10.1080/14796694.2025.2597405
Shahd Hamran, Zaineh Alnoubani, Aly Mostafa Hassan, Amani A Al-Rajhi, Humam Emad Rajha, Munirah Altaissan, Giridhara R Babu, Zoran Gatalica, Semir Vranić
Aim: Gene fusions involving Neurotrophic Receptor Tyrosine Kinase (NTRK) genes lead to Tropomyosin Receptor Kinases (TRK) overexpression. Detecting NTRK1-3 fusions through advanced molecular techniques has revolutionized cancer care through personalized medicine, such as TRK inhibitors.
Methods: We conducted a comprehensive search of databases (PubMed/MEDLINE, SCOPUS, Web of Science) and extracted data on study characteristics, molecular characteristics, and clinical outcomes. Data synthesis involved narrative and thematic analysis and study quality assessment using the Methodological Standard for Epidemiological Research (MASTER) scale.
Results: We included 136 studies with 18,077 patients. The most common tumor categories were unclassified soft tissue sarcomas (11.09%), gynecological sarcomas (5.64%), and liposarcomas (3.37%). Most tumors were gynecologic (5.64%), followed by the limbs (1.45%). Genomic sequencing was the predominant diagnostic method used in 110 studies. Overall, 551 patients with sarcoma tested positive for NTRK1-3 gene fusions, primarily involving NTRK1 and NTRK3 (~93%), with ETV6-NTRK3 fusion being the most frequently reported fusion. Larotrectinib was used in 142 patients, demonstrating an 83.80% response rate, with low mortality (2.82%) and recurrence (2.11%) rates. Entrectinib had a lower response rate of 63.64%.
Conclusions: We confirm the rarity of NTRK1-3 fusions in sarcomas. TRK inhibitors show high efficacy in sarcomas, emphasizing the necessity of genomic testing in all cases.Protocol registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024563594.
目的:神经营养受体酪氨酸激酶(NTRK)基因融合导致原肌球蛋白受体激酶(TRK)过表达。通过先进的分子技术检测NTRK1-3融合物,通过个性化药物(如TRK抑制剂)彻底改变了癌症治疗。方法:全面检索数据库(PubMed/MEDLINE、SCOPUS、Web of Science),提取研究特征、分子特征和临床结果数据。数据综合包括叙述和专题分析,以及使用流行病学研究方法标准(MASTER)量表进行研究质量评估。结果:我们纳入了136项研究,18,077例患者。最常见的肿瘤类型为未分类软组织肉瘤(11.09%)、妇科肉瘤(5.64%)和脂肪肉瘤(3.37%)。以妇科肿瘤居多(5.64%),其次为四肢肿瘤(1.45%)。基因组测序是110项研究中使用的主要诊断方法。总体而言,551例肉瘤患者检测出NTRK1-3基因融合阳性,主要涉及NTRK1和NTRK3(约93%),其中ETV6-NTRK3融合是最常见的融合。142例患者使用larorectinib,有效率为83.80%,死亡率(2.82%)和复发率(2.11%)较低。恩替尼的有效率较低,为63.64%。结论:我们证实了NTRK1-3在肉瘤中的罕见性。TRK抑制剂在肉瘤中显示出很高的疗效,强调了在所有病例中进行基因组检测的必要性。协议注册:https://www.crd.york.ac.uk/PROSPERO/view/CRD42024563594。
{"title":"<i>NTRK1-3</i> fusions in sarcomas: prevalence, significance, and clinical implications - a systematic review.","authors":"Shahd Hamran, Zaineh Alnoubani, Aly Mostafa Hassan, Amani A Al-Rajhi, Humam Emad Rajha, Munirah Altaissan, Giridhara R Babu, Zoran Gatalica, Semir Vranić","doi":"10.1080/14796694.2025.2597405","DOIUrl":"10.1080/14796694.2025.2597405","url":null,"abstract":"<p><strong>Aim: </strong>Gene fusions involving Neurotrophic Receptor Tyrosine Kinase (<i>NTRK</i>) genes lead to Tropomyosin Receptor Kinases (TRK) overexpression. Detecting <i>NTRK1-3</i> fusions through advanced molecular techniques has revolutionized cancer care through personalized medicine, such as TRK inhibitors.</p><p><strong>Methods: </strong>We conducted a comprehensive search of databases (PubMed/MEDLINE, SCOPUS, Web of Science) and extracted data on study characteristics, molecular characteristics, and clinical outcomes. Data synthesis involved narrative and thematic analysis and study quality assessment using the Methodological Standard for Epidemiological Research (MASTER) scale.</p><p><strong>Results: </strong>We included 136 studies with 18,077 patients. The most common tumor categories were unclassified soft tissue sarcomas (11.09%), gynecological sarcomas (5.64%), and liposarcomas (3.37%). Most tumors were gynecologic (5.64%), followed by the limbs (1.45%). Genomic sequencing was the predominant diagnostic method used in 110 studies. Overall, 551 patients with sarcoma tested positive for <i>NTRK1-3</i> gene fusions, primarily involving <i>NTRK1</i> and <i>NTRK3</i> (~93%), with <i>ETV6-NTRK3</i> fusion being the most frequently reported fusion. Larotrectinib was used in 142 patients, demonstrating an 83.80% response rate, with low mortality (2.82%) and recurrence (2.11%) rates. Entrectinib had a lower response rate of 63.64%.</p><p><strong>Conclusions: </strong>We confirm the rarity of <i>NTRK1-3</i> fusions in sarcomas. TRK inhibitors show high efficacy in sarcomas, emphasizing the necessity of genomic testing in all cases.<b>Protocol registration</b>: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024563594.</p>","PeriodicalId":12672,"journal":{"name":"Future oncology","volume":" ","pages":"4011-4024"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145762232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-11-28DOI: 10.1080/14796694.2025.2592722
Bertrand Tombal, Fred Saad, Enrique Gallardo, Andrey Soares, Yohann Loriot, Ray McDermott, Erik Briers, Mikael Lagström, Corneel Coens, Coralie Poncet, Beatrice Fournier, Silke Gillessen
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