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Durable partial response of pulmonary metastases from primary sublingual gland squamous cell carcinoma after pembrolizumab failure: Salvage therapy with paclitaxel plus cetuximab 派姆单抗失败后原发性舌下腺鳞状细胞癌肺转移的持久部分缓解：紫杉醇加西妥昔单抗的挽救治疗

Oral Oncology Reports

Pub Date : 2025-10-20 DOI: 10.1016/j.oor.2025.100768

Kumiko Kamada , Atsushi Uesugi , Yasusei Kudo , Takaaki Tsunematsu , Yoshiaki Kitamura , Naito Kurio

Background

Primary squamous cell carcinoma (SCC) of the sublingual gland is an extremely rare salivary gland malignancy with limited treatment options, particularly once distant metastases develop. Immune checkpoint inhibitors (ICIs) such as pembrolizumab have demonstrated efficacy in PD-L1–positive tumors; however, progression after ICI therapy remains a major clinical challenge.

Case presentation

An 82-year-old man underwent surgical resection of a primary SCC of the sublingual gland in February 2021. Surgical margins were negative, and no recurrence has been observed at the primary or cervical sites up to the present time in 2025. In August 2021, multiple bilateral pulmonary nodules were detected and diagnosed as pulmonary metastases. Pembrolizumab was initiated in January 2022 and administered for 10 cycles, but CT imaging revealed progressive disease with >20 % tumor growth and new lesions. Consequently, paclitaxel plus cetuximab therapy was started in September 2022 and continued until November 2022, when grade 1 interstitial pneumonitis led to discontinuation. CT imaging in October and December 2022 showed marked regression, resulting in a partial response (PR) by RECIST criteria. The PR has been maintained without new lesions or progression through June 2025.

Conclusion

This case highlights the potential efficacy of paclitaxel plus cetuximab as salvage therapy after ICI failure in pulmonary metastases of PD-L1–high primary SCC of the sublingual gland, even in elderly patients.

背景：原发性舌下腺鳞状细胞癌（SCC）是一种极其罕见的涎腺恶性肿瘤，治疗选择有限，特别是一旦发生远处转移。免疫检查点抑制剂（ICIs）如派姆单抗已被证明对pd - l1阳性肿瘤有效；然而，ICI治疗后的进展仍然是主要的临床挑战。病例介绍：一名82岁男性于2021年2月接受了舌下腺原发性鳞状细胞癌的手术切除。手术切缘阴性，到2025年，在原发或宫颈部位没有观察到复发。2021年8月，发现双侧多发肺结节，诊断为肺转移。Pembrolizumab于2022年1月开始使用，并给药10个周期，但CT成像显示疾病进展，肿瘤生长>； 20%，并出现新的病变。因此，紫杉醇加西妥昔单抗治疗于2022年9月开始，一直持续到2022年11月，当时1级间质性肺炎导致停药。2022年10月和12月的CT成像显示明显的消退，根据RECIST标准导致部分缓解（PR）。到2025年6月，PR一直保持无新病变或进展。结论本病例强调了紫杉醇联合西妥昔单抗作为ICI治疗舌下腺pd - l1高原发鳞状细胞癌肺转移失败后的挽救性治疗的潜在疗效，即使在老年患者中也是如此。

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引用次数: 0

The role of artificial intelligence in predicting cancer immunotherapy response 人工智能在预测癌症免疫治疗反应中的作用

Oral Oncology Reports

Pub Date : 2025-10-11 DOI: 10.1016/j.oor.2025.100767

Ravi Bhushan , Sakshi Rai , Preeti Jangra , Palak Sonker , Nitesh Singh , Raj Lakshami , Reya Rene Philip , Saloni Gakhar , Tikam Chand Dakal

Cancer immunotherapy has emerged as a groundbreaking approach in oncology, leveraging the immune system's ability to target and eliminate tumor cells. Despite its success, the variability in patient responses to immunotherapy poses a significant challenge, necessitating the development of robust predictive tools. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL) techniques, offers promising solutions by enabling the analysis of complex and multidimensional data to predict treatment outcomes with greater accuracy. This review provides a comprehensive examination of the current advancements in AI-driven models for predicting cancer immunotherapy responses. We discuss the integration of multiomics data, including genomic, transcriptomic, and proteomic information, into AI models to enhance predictive accuracy. Furthermore, we explore the discovery of novel biomarkers through AI methodologies that hold the potential to refine patient stratification and treatment personalization. Despite the promising advancements, several challenges persist, including data quality, model interpretability, and ethical considerations. Addressing these challenges is critical for the successful clinical integration of AI tools in oncology. This review also highlights future directions, emphasizing the need for interdisciplinary collaboration and the development of explainable AI models to ensure their utility in clinical decision-making. In conclusion, AI has the potential to revolutionize the prediction of cancer immunotherapy responses, paving the way for more personalized and effective treatment strategies. Continued research and innovation in this field are essential to fully realize the benefits of AI in enhancing patient outcomes and advancing precision oncology.

癌症免疫疗法已经成为肿瘤学领域的一种突破性方法，利用免疫系统的能力来靶向和消除肿瘤细胞。尽管取得了成功，但患者对免疫治疗反应的可变性提出了重大挑战，需要开发强大的预测工具。人工智能（AI），特别是机器学习（ML）和深度学习（DL）技术，通过分析复杂和多维数据来更准确地预测治疗结果，提供了有前途的解决方案。本文综述了人工智能驱动模型预测癌症免疫治疗反应的最新进展。我们讨论了将多组学数据（包括基因组、转录组学和蛋白质组学信息）整合到人工智能模型中，以提高预测准确性。此外，我们探索通过人工智能方法发现新的生物标志物，这些方法有可能改善患者分层和治疗个性化。尽管取得了有希望的进展，但仍然存在一些挑战，包括数据质量、模型可解释性和伦理考虑。解决这些挑战对于人工智能工具在肿瘤学中的成功临床整合至关重要。这篇综述还强调了未来的方向，强调需要跨学科合作和可解释的人工智能模型的发展，以确保它们在临床决策中的效用。总之，人工智能有可能彻底改变癌症免疫治疗反应的预测，为更个性化和更有效的治疗策略铺平道路。这一领域的持续研究和创新对于充分实现人工智能在提高患者治疗效果和推进精准肿瘤学方面的好处至关重要。

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引用次数: 0

The use of international radiotherapy consensus guidelines for primary clinical target volume delineation for oropharyngeal carcinoma: case series with recurrence pattern analysis 使用国际放射治疗共识指南划定口咽癌的主要临床靶体积：病例系列与复发模式分析

Oral Oncology Reports

Pub Date : 2025-09-19 DOI: 10.1016/j.oor.2025.100765

Alina Kiewell , Lily Bevan , Chinyereugo Umemneku-Chikere , Robin.J.D. Prestwich , Zsuzsanna Iyizoba Ebozue

Background

International consensus guidelines for head and neck cancer primary clinical target volume (CTV) delineation based upon a geometric ‘5 + 5’ expansion and anatomical editing were published in 2018. Analysis of recurrence patterns in relation to target volumes is required to validate this approach.

Methods

Patients with oropharyngeal carcinoma treated between 2019–22 with definitive (chemo)radiotherapy using the guideline approach to primary CTV delineation were identified. Patterns of locoregional recurrence were analysed using combined spatial and dosimetric analysis. Central, high dose recurrences were defined by mapped a centroid of the volume of recurrence (Vrec) to within the high dose planning target volume (PTV) and >95 % of Vrec receiving >95 % of prescribed dose to high dose PTV.

Results

133 patients were treated using the consensus outlining guidelines. Median follow up was 3.9 years. 78.9 % had p16 positive disease. 3-year local and regional control rates were 96 % and 94.7 %. Locoregional recurrence occurred in 6/133 (4.5 %) of patients including 3 patients with primary site recurrences. All primary site recurrences were classified as central high dose recurrences.

Conclusions

All primary tumour site recurrences were within the high dose volume with no evidence of marginal or out-of-field recurrences. There results provide evidence for the safety of the consensus outlining approach for primary tumour CTVs.

基于几何“5 + 5”扩展和解剖编辑的头颈癌主要临床靶体积（CTV）划定的国际共识指南于2018年发布。需要分析与目标体积相关的复发模式来验证这种方法。方法对2019 - 2022年间接受终期（化疗）放疗的口咽癌患者进行初步CTV划定指南。局部区域复发的模式分析使用联合空间和剂量分析。中心、高剂量复发是通过将复发体积（Vrec）的质心映射到高剂量计划目标体积（PTV）内来定义的，并且95%的Vrec接受了95%的规定剂量到高剂量PTV。结果133例患者采用共识提纲治疗。中位随访时间为3.9年。78.9%为p16阳性。3年局部控制率96%，区域控制率94.7%。133例患者中有6例（4.5%）发生局部复发，其中3例为原发部位复发。所有原发部位复发均归为中心性高剂量复发。结论所有原发肿瘤部位复发均在高剂量范围内，无边缘或场外复发。这些结果为原发性肿瘤CTVs的共识概述方法的安全性提供了证据。

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引用次数: 0

Corrigendum to “Photodynamic therapy for cancer” [Oral Oncol Rep 9 (2024) 100129] “癌症光动力疗法”的勘误表[Oral Oncol Rep 9 (2024) 100129]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100742

Shrikant B. Mali, Sachinkumar Dahivelkar

引用次数: 0

Corrigendum to “Delta Radiomics — Potential role in Head Neck Cancer” [Oral Oncol Rep 12 (2024) 100676] “Delta放射组学-头颈癌的潜在作用”的勘误表[Oral Oncol Rep 12 (2024) 100676]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100745

Shrikant Balasaheb Mali

引用次数: 0

Corrigendum to “Role of Cold atmospheric plasma in cancer management” [Oral Oncol Rep 9 (2024) 100133] “低温大气血浆在癌症治疗中的作用”的勘误表[Oral Oncol Rep 9 (2024) 100133]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100751

Shrikant Balasaheb Mali

引用次数: 0

Corrigendum to “Social media in health care - Ethically challenging - Dangerous but attractive- -use with caution” [Oral Oncol Rep 7 (2023) 100079] “医疗保健中的社交媒体-伦理挑战-危险但有吸引力-谨慎使用”的勘误表[Oral Oncol Rep 7 (2023) 100079]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100753

Shrikant Balasaheb Mali

引用次数: 0

Corrigendum to “End of life and palliative care decisions in advanced head neck cancer” [Oral Oncol Rep 11 (2024) 100569] “晚期头颈癌的生命终结和姑息治疗决策”的勘误表[Oral Oncol Rep 11 (2024) 100569]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100744

Shrikant Balasaheb Mali

引用次数: 0

Corrigendum to “Nanotechnology in photodynamic therapy” [Oral Oncology Reports 10 (2024) 100307] “光动力治疗中的纳米技术”的勘误表[口腔肿瘤学报告10 (2024)100307]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100750

Shrikant B. Mali, Sachinkumar Dattatray Dahivelkar

引用次数: 0

Corrigendum to “Panoptosis – new frontier in research in head neck cancer” [Oral Oncol Rep 10 (2024) 100310] “Panoptosis -头颈癌研究的新前沿”的勘误表[Oral Oncol Rep 10 (2024) 100310]

Oral Oncology Reports

Pub Date : 2025-09-01 DOI: 10.1016/j.oor.2025.100752

Shrikant Balasaheb Mali

引用次数: 0

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