Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care. A Report of a Multidisciplinary Workshop Coordinated by the RECIST Working Group.

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials.

FDA Approval Summary: Sotorasib for KRAS G12C-Mutated Metastatic NSCLC.

On May 28, 2021, the FDA granted accelerated approval to sotorasib (Lumakras, Amgen) for the treatment of adults with advanced non-small cell lung cancer (NSCLC) with a Kirsten rat sarcoma proto-oncogene (KRAS) G12C mutation who have received at least one prior systemic therapy. The approval was based on CodeBreaK 100 (Study 20170543), a dose-escalation and dose-expansion trial in patients with an advanced, KRAS G12C-mutated, solid tumor. The overall response rate (ORR) observed in patients with KRAS G12C-mutated NSCLC treated with sotorasib (n = 124) was 36% [95% confidence interval (CI), 28-45]. The median duration of response was 10.0 months (95% CI, 6.9-not estimable). The most common adverse reactions (≥20%) were diarrhea, musculoskeletal pain, nausea, fatigue, hepatotoxicity, and cough. This is the first approval of a targeted therapy for KRAS G12C-mutated NSCLC. Because of pharmacokinetic data and ORRs of patient cohorts who took sotorasib at lower doses in the dose-escalation portion of CodeBreaK 100, a dose comparison study is being conducted as a post-marketing requirement.

FDA Approval Summary: Nivolumab in Combination with Ipilimumab for the Treatment of Unresectable Malignant Pleural Mesothelioma.

On October 2, 2020, FDA approved nivolumab with ipilimumab as first-line treatment for adult patients with unresectable malignant pleural mesothelioma (MPM). The approval was based on results from Study CA209743 (CHECKMATE-743), an open-label trial of patients with MPM randomized to receive nivolumab and ipilimumab for up to 2 years (n = 303) or six cycles of chemotherapy with cisplatin or carboplatin plus pemetrexed (n = 302). Overall survival (OS) was improved for patients who received nivolumab and ipilimumab, with a median OS of 18.1 months [95% confidence interval (CI), 16.8-21.5] compared with 14.1 months (95% CI: 12.5-16.2; HR, 0.74; 95% CI, 0.61-0.89; P = 0.002), for patients who received chemotherapy. The magnitude of benefit was larger for patients with non-epithelioid versus epithelioid histology. Additional clinical pharmacology data support an alternative dosing regimen of nivolumab than evaluated in the trial, which will reduce the number of required treatment visits. This application was reviewed under FDA's Project Orbis, in collaboration with Australia's Therapeutic Goods Administration, Switzerland's Swissmedic, Health Canada, and Brazil's National Health Surveillance Agency or ANVISA (Agência Nacional de Vigilância Sanitária). Nivolumab and ipilimumab is the first drug regimen approved by FDA for MPM since 2004.

Challenge of Rechallenge: When to Resume Immunotherapy Following an Immune-Related Adverse Event.

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.

Assessing the inter-observer variability of Computer-Aided Nodule Assessment and Risk Yield (CANARY) to characterize lung adenocarcinomas.

Lung adenocarcinoma (ADC), the most common lung cancer type, is recognized increasingly as a disease spectrum. To guide individualized patient care, a non-invasive means of distinguishing indolent from aggressive ADC subtypes is needed urgently. Computer-Aided Nodule Assessment and Risk Yield (CANARY) is a novel computed tomography (CT) tool that characterizes early ADCs by detecting nine distinct CT voxel classes, representing a spectrum of lepidic to invasive growth, within an ADC. CANARY characterization has been shown to correlate with ADC histology and patient outcomes. This study evaluated the inter-observer variability of CANARY analysis. Three novice observers segmented and analyzed independently 95 biopsy-confirmed lung ADCs from Vanderbilt University Medical Center/Nashville Veterans Administration Tennessee Valley Healthcare system (VUMC/TVHS) and the Mayo Clinic (Mayo). Inter-observer variability was measured using intra-class correlation coefficient (ICC). The average ICC for all CANARY classes was 0.828 (95% CI 0.76, 0.895) for the VUMC/TVHS cohort, and 0.852 (95% CI 0.804, 0.901) for the Mayo cohort. The most invasive voxel classes had the highest ICC values. To determine whether nodule size influenced inter-observer variability, an additional cohort of 49 sub-centimeter nodules from Mayo were also segmented by three observers, with similar ICC results. Our study demonstrates that CANARY ADC classification between novice CANARY users has an acceptably low degree of variability, and supports the further development of CANARY for clinical application.

Quantifying metabolic heterogeneity in head and neck tumors in real time: 2-DG uptake is highest in hypoxic tumor regions.

PURPOSE: Intratumoral metabolic heterogeneity may increase the likelihood of treatment failure due to the presence of a subset of resistant tumor cells. Using a head and neck squamous cell carcinoma (HNSCC) xenograft model and a real-time fluorescence imaging approach, we tested the hypothesis that tumors are metabolically heterogeneous, and that tumor hypoxia alters patterns of glucose uptake within the tumor. EXPERIMENTAL DESIGN: Cal33 cells were grown as xenograft tumors (n = 16) in nude mice after identification of this cell line's metabolic response to hypoxia. Tumor uptake of fluorescent markers identifying hypoxia, glucose import, or vascularity was imaged simultaneously using fluorescent molecular tomography. The variability of intratumoral 2-deoxyglucose (IR800-2-DG) concentration was used to assess tumor metabolic heterogeneity, which was further investigated using immunohistochemistry for expression of key metabolic enzymes. HNSCC tumors in patients were assessed for intratumoral variability of (18)F-fluorodeoxyglucose ((18)F-FDG) uptake in clinical PET scans. RESULTS: IR800-2-DG uptake in hypoxic regions of Cal33 tumors was 2.04 times higher compared to the whole tumor (p = 0.0001). IR800-2-DG uptake in tumors containing hypoxic regions was more heterogeneous as compared to tumors lacking a hypoxic signal. Immunohistochemistry staining for HIF-1α, carbonic anhydrase 9, and ATP synthase subunit 5ß confirmed xenograft metabolic heterogeneity. We detected heterogeneous (18)F-FDG uptake within patient HNSCC tumors, and the degree of heterogeneity varied amongst tumors. CONCLUSION: Hypoxia is associated with increased intratumoral metabolic heterogeneity. (18)F-FDG PET scans may be used to stratify patients according to the metabolic heterogeneity within their tumors, which could be an indicator of prognosis.

Metabolic symbiosis in cancer: refocusing the Warburg lens.

Using relatively primitive tools in the 1920s, Otto Warburg demonstrated that tumor cells show an increased dependence on glycolysis to meet their energy needs, regardless of whether they were well-oxygenated or not. High rates of glucose uptake, fueling glycolysis, are now used clinically to identify cancer cells. However, the Warburg effect does not account for the metabolic diversity that has been observed amongst cancer cells nor the influences that might direct such diversity. Modern tools have shown that the oncogenes, variable hypoxia levels, and the utilization of different carbon sources affect tumor evolution. These influences may produce metabolic symbiosis, in which lactate from a hypoxic, glycolytic tumor cell population fuels ATP production in the oxygenated region of a tumor. Lactate, once considered a waste product of glycolysis, is an important metabolite for oxidative phosphorylation in many tissues. While much is known about how muscle and the brain use lactate in oxidative phosphorylation, the contribution of lactate in tumor bioenergetics is less defined. A refocused perspective of cancer metabolism that recognizes metabolic diversity within a tumor offers novel therapeutic targets by which cancer cells may be starved from their fuel sources, and thereby become more sensitive to traditional cancer treatments.