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IntroductionLung-MAP S1400K was designed to evaluate the response to telisotuzumab vedotin, an antibody-drug conjugate targeting c-MET, in patients with c-MET-positive squamous cell carcinoma (SCC).Patients and methodsPatients with previously treated SCC with c-MET-positive tumors (H score ≥ 150, Ventana SP44 assay) were enrolled into 2 cohorts: Cohort 1 (immune checkpoint inhibitor-naive) and Cohort 2 (immune checkpoint inhibitor refractory). Telisotuzumab vedotin 2.7 mg/kg was administered intravenously every 3 weeks until disease progression or unacceptable toxicity. Response assessments were performed every 6 weeks. The primary endpoint was response by Response Evaluation Criteria in Solid Tumors (RECIST) v1.1. Secondary endpoints included progression-free survival, overall survival, response within cohort, duration of response, and toxicities. Interim analysis was planned after 20 evaluable patients, with ≥ 3 responses needed to continue enrollment.ResultsForty-nine patients (14% of screened patients) were assigned to S1400K, 28 patients enrolled (15 in Cohort 1 and 13 in Cohort 2), and 23 were eligible. S1400K closed on December 21, 2018 owing to lack of efficacy. Two responses (response rate of 9%; 95% confidence interval, 0%-20%) were reported in cohort 1 (1 complete and 1 unconfirmed partial response), whereas 10 patients had stable disease, with a disease control rate of 52%. The median overall and progression-free survival was 5.6 and 2.4 months, respectively. There were 3 grade 5 events (2 pneumonitis, in Cohort 2, and 1 bronchopulmonary hemorrhage, in Cohort 1).ConclusionTelisotuzumab vedotin failed to meet the pre-specified response needed to justify continuing enrollment to S1400K. Pneumonitis was an unanticipated toxicity observed in patients with SCC.

AbstractDespite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.

As anticancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. Although traditional, anatomic CT, and MRI examinations are useful in many settings, increasing evidence suggests that these methods cannot answer the fundamental biologic and physiologic questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients and to provide a more efficient path for the development of improved targeted therapies.

PurposeTo determine the variability of lesion size measurements in computed tomography data sets of patients imaged under a "no change" ("coffee break") condition and to determine the impact of two reading paradigms on measurement variability.Method and materialsUsing data sets from 32 non-small cell lung cancer patients scanned twice within 15 minutes ("no change"), measurements were performed by five radiologists in two phases: (1) independent reading of each computed tomography dataset (timepoint): (2) a locked, sequential reading of datasets. Readers performed measurements using several sizing methods, including one-dimensional (1D) longest in-slice dimension and 3D semi-automated segmented volume. Change in size was estimated by comparing measurements performed on both timepoints for the same lesion, for each reader and each measurement method. For each reading paradigm, results were pooled across lesions, across readers, and across both readers and lesions, for each measurement method.ResultsThe mean percent difference (±SD) when pooled across both readers and lesions for 1D and 3D measurements extracted from contours was 2.8 ± 22.2% and 23.4 ± 105.0%, respectively, for the independent reads. For the locked, sequential reads, the mean percent differences (±SD) reduced to 2.52 ± 14.2% and 7.4 ± 44.2% for the 1D and 3D measurements, respectively.ConclusionEven under a "no change" condition between scans, there is variation in lesion size measurements due to repeat scans and variations in reader, lesion, and measurement method. This variation is reduced when using a locked, sequential reading paradigm compared to an independent reading paradigm.

Although progression-based endpoints, such as progression-free survival, are often key clinical trial endpoints for anticancer agents, the clinical meaning of "objective progression" is much less certain. As scrutiny of progression-based endpoints in clinical trials increases, it should be remembered that the Response Evaluation Criteria In Solid Tumors (RECIST) progression criteria were not developed as a surrogate for survival. Now that progression-free survival has come to be an increasingly important trial endpoint, the criteria that define progression deserve critical evaluation to determine whether alternate definitions of progression might facilitate the development of stronger surrogate endpoints and more meaningful trial results. In this commentary, we review the genesis of the criteria for progression, highlight recent data that question their value as a marker of treatment failure, and advocate for several research strategies that could lay the groundwork for a clinically validated definition of disease progression in solid tumor oncology.

Simple Summary: Radiation therapy has long been reported to affect tumors distal to the site of irradiation, in what is known as the abscopal effect; the synergy of radiation with immune-oncological agents has also been studied and exploited for greater anti-cancer effect. We believe that PET/CT imaging can offer insight into the mechanism of this synergy and thereby optimize the dosing and timing as well as monitoring the response to and adverse effects of radiation therapy in tandem with immunotherapy. Herein, we offer a commentary to better integrate PET/CT into recently released joint guidelines, to exploit radiation and immunotherapy synergy. [18F]-FDG positron emission tomography with computed tomography (PET/CT) imaging is widely used to enhance the quality of care in patients diagnosed with cancer. Furthermore, it holds the potential to offer insight into the synergic effect of combining radiation therapy (RT) with immuno-oncological (IO) agents. This is achieved by evaluating treatment responses both at the RT and distant tumor sites, thereby encompassing the phenomenon known as the abscopal effect. In this context, PET/CT can play an important role in establishing timelines for RT/IO administration and monitoring responses, including novel patterns such as hyperprogression, oligoprogression, and pseudoprogression, as well as immune-related adverse events. In this commentary, we explore the incremental value of PET/CT to enhance the combination of RT with IO in precision therapy for solid tumors, by offering supplementary insights to recently released joint guidelines. [ABSTRACT FROM AUTHOR]