Lenvatinib plus pembrolizumab for patients with previously treated, advanced, triple-negative breast cancer: Results from the triple-negative breast cancer cohort of the phase 2 LEAP-005 Study.

BACKGROUND: Novel treatments are needed for patients with advanced, triple-negative breast cancer (TNBC) that progresses or recurs after first-line treatment with chemotherapy. The authors report results from the TNBC cohort of the multicohort, open-label, single-arm, phase 2 LEAP-005 study of lenvatinib plus pembrolizumab in patients with advanced solid tumors (ClinicalTrials.gov identifier NCT03797326). METHODS: Eligible patients had metastatic or unresectable TNBC with disease progression after one or two lines of therapy. Patients received lenvatinib (20 mg daily) plus pembrolizumab (200 mg every 3 weeks; up to 35 cycles). The primary end points were the objective response rate according to Response Evaluation Criteria in Solid Tumors, version 1.1, and safety (adverse events graded by the National Cancer Institute's Common Terminology Criteria for Adverse Events, version 4.0). Duration of response, progression-free survival, and overall survival were secondary end points. RESULTS: Thirty-one patients were enrolled. The objective response rate by investigator assessment was 23% (95% confidence interval [CI], 10%-41%). Overall, the objective response rate by blinded independent central review (BICR) was 32% (95% CI, 17%-51%); and, in patients who had programmed cell death ligand 1 combined positive scores ≥10 (n = 8) and <10 (n = 22), the objective response rate was 50% (95% CI, 16%-84%) and 27% (95% CI, 11%-50%), respectively. The median duration of response by BICR was 12.1 months (range, from 3.0+ to 37.9+ months). The median progression-free survival by BICR was 5.1 months (95% CI, 1.9-11.8 months) and the median overall survival was 11.4 months (95% CI, 4.1-21.7 months). Treatment-related adverse events occurred in 94% of patients (grade 3, 52%; grade 4, 0%). One patient died due to a treatment-related adverse event of subarachnoid hemorrhage. CONCLUSIONS: The combination of lenvatinib plus pembrolizumab demonstrated antitumor activity with a manageable safety profile in patients with previously treated, advanced TNBC.

Evaluating Debio 1347 in Patients with FGFR Fusion-Positive Advanced Solid Tumors from the FUZE Multicenter, Open-Label, Phase II Basket Trial.

PURPOSE: This multicenter phase II basket trial investigated the efficacy, safety and pharmacokinetics of Debio 1347, an investigational, oral, highly selective, ATP-competitive, small molecule inhibitor of FGFR1-3, in patients with solid tumors harboring a functional FGFR1-3 fusion. PATIENTS AND METHODS: Eligible adults had a previously treated locally advanced (unresectable) or metastatic biliary tract (cohort 1), urothelial (cohort 2) or other histologic cancer type (cohort 3). Debio 1347 was administered at 80 mg once daily, continuously, in 28-day cycles. The primary endpoint was the objective response rate (ORR). Secondary endpoints included duration of response, progression-free survival, overall survival, pharmacokinetics, and incidence of adverse events. RESULTS: Between March 22, 2019 and January 8, 2020, 63 patients were enrolled and treated, 30 in cohort 1, four in cohort 2, and 29 in cohort 3. An unplanned preliminary statistical review showed that the efficacy of Debio 1347 was lower than predicted and the trial was terminated. Three of 58 evaluable patients had partial responses, representing an ORR of 5%, with a further 26 (45%) having stable disease (≥6 weeks duration). Grade ≥3 treatment-related adverse events occurred in 22 (35%) of 63 patients, with the most common being hyperphosphatemia (13%) and stomatitis (5%). Two patients (3%) discontinued treatment due to adverse events. CONCLUSIONS: Debio 1347 had manageable toxicity; however, the efficacy in patients with tumors harboring FGFR fusions did not support further clinical evaluation in this setting. Our transcriptomic-based analysis characterized in detail the incidence and nature of FGFR fusions across solid tumors.

Bexmarilimab-induced macrophage activation leads to treatment benefit in solid tumors: The phase I/II first-in-human MATINS trial.

Macrophage Clever-1 contributes to impaired antigen presentation and suppression of anti-tumor immunity. This first-in-human trial investigates the safety and tolerability of Clever-1 blockade with bexmarilimab in patients with treatment-refractory solid tumors and assesses preliminary anti-tumor efficacy, pharmacodynamics, and immunologic correlates. Bexmarilimab shows no dose-limiting toxicities in part I (n = 30) and no additional safety signals in part II (n = 108). Disease control (DC) rates of 25%-40% are observed in cutaneous melanoma, gastric, hepatocellular, estrogen receptor-positive breast, and biliary tract cancers. DC associates with improved survival in a landmark analysis and correlates with high pre-treatment intratumoral Clever-1 positivity and increasing on-treatment serum interferon γ (IFNγ) levels. Spatial transcriptomics profiling of DC and non-DC tumors demonstrates bexmarilimab-induced macrophage activation and stimulation of IFNγ and T cell receptor signaling selectively in DC patients. These data suggest that bexmarilimab therapy is well tolerated and show that macrophage targeting can promote immune activation and tumor control in late-stage cancer.

Digital ECMT Cancer Trial Matching Tool: an Open Source Research Application to Support Oncologists in the Identification of Precision Medicine Clinical Trials.

PURPOSE: Matching patients with cancer to precision medicine clinical trials on the basis of their tumor genotype has the potential to improve outcomes for patients who have exhausted standard-of-care treatment options. However, the matching process presents a substantial challenge because of the number of clinical trials available. We describe a free, open source research tool designed to extract relevant trial information to support oncologists in the matching process, and we illustrate its utility with recent case studies of patients who were matched to trials using this tool. METHODS: Trial records are sourced from ClinicalTrials.gov and indexed using natural language processing techniques, including named entity recognition, term normalization, and relationship extraction. Relationships between trials and genetic alterations are assigned scores on the basis of a rule-based system. All data are updated daily. A user interface is provided via R Shiny app. RESULTS: An instance of the trial match tool, configured for UK clinical trials, is hosted by the digital Experimental Cancer Medicine Team (see link in Data Sharing Statement). Users select the relevant cancer type and genetic alteration(s). Matching studies are ranked according to the score assigned for the selected genetic alterations. Results may be downloaded and attached to the patient's health record if desired. The tool is currently being used to support the ongoing TARGET National study, which aims to match up to 6,000 patients to early phase clinical trials. We present three case studies that exemplify relationships between genetic alterations and studies. CONCLUSION: With increasing numbers of precision medicine treatments and as comprehensive molecular profiling of tumor samples becomes more common, decision support tools are likely to become increasingly important. This work represents an important step toward the development and wider implementation of such systems.

Real-world outcomes with ipilimumab and nivolumab in advanced melanoma: a multicentre retrospective study.

PURPOSE: To assess efficacy and toxicity of combination immunotherapy with ipilimumab plus nivolumab in routine practice in a retrospective multicentre cohort of patients with advanced melanoma. PATIENTS AND METHODS: This retrospective analysis included patients with advanced melanoma treated with ipilimumab and nivolumab between October 2015 and January 2020 at six centres in Australia, Europe and the United States of America. We describe efficacy outcomes (overall survival [OS], progression-free survival [PFS] and objective response rate [ORR]) in treatment-naïve and pre-treated patients, with and without brain metastases, plus treatment-related adverse events (trAEs) in all patients treated. RESULTS: A total of 697 patients were identified; 472 were treatment-naïve of which 138 (29.2%) had brain metastases, and 225 were previously treated of which 102 (45.3%) had brain metastases. At baseline, 32.3% had stage M1c and 34.4% stage M1d disease. Lactate dehydrogenase was high in 280 patients (40.2%). With a median follow-up of 25.9 months, median OS in the 334 treatment-naïve patients without brain metastases was 53.7 months (95% confidence interval [CI] 40.8-NR) and 38.7 months (95% CI 18.6-NR) for the 138 treatment-naïve patients with brain metastases. For the entire cohort the ORR was 48%, for treatment-naïve patients without brain metastases ORR was 56.6% with a median PFS of was 13.7 months (95% CI 9.6-26.5). Median PFS was 7.9 months (95% CI 5.8-10.4) and OS 38 months (95% CI 31-NR) for the entire cohort. Grade 3-4 trAE were reported in 44% of patients, and 4 (0.7%) treatment-related deaths (1 pneumonitis, 2 myocarditis and 1 colitis) were recorded. CONCLUSION: The outcome and toxicity of combination immunotherapy with ipilimumab and nivolumab in a real-world patient population are similar to those reported in pivotal trials.

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves.

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

Patient attrition in Molecular Tumour Boards: a systematic review.

BACKGROUND: Molecular Tumour Boards (MTBs) were created with the purpose of supporting clinical decision-making within precision medicine. Though in use globally, reporting on these meetings often focuses on the small percentages of patients that receive treatment via this process and are less likely to report on, and assess, patients who do not receive treatment. METHODS: A literature review was performed to understand patient attrition within MTBs and barriers to patients receiving treatment. A total of 51 papers were reviewed spanning a 6-year period from 11 different countries. RESULTS: In total, 20% of patients received treatment through the MTB process. Of those that did not receive treatment, the main reasons were no mutations identified (27%), no actionable mutations (22%) and clinical deterioration (15%). However, data were often incomplete due to inconsistent reporting of MTBs with only 55% reporting on patients having no mutations, 55% reporting on the presence of actionable mutations with no treatment options and 59% reporting on clinical deterioration. DISCUSSION: As patient attrition in MTBs is an issue which is very rarely alluded to in reporting, more transparent reporting is needed to understand barriers to treatment and integration of new technologies is required to process increasing omic and treatment data.

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.

Latency and interval therapy affect the evolution in metastatic colorectal cancer.

While comparison of primary tumor and metastases has highlighted genomic heterogeneity in colorectal cancer (CRC), previous studies have focused on a single metastatic site or limited genomic testing. Combining data from whole exome and ultra-deep targeted sequencing, we explored possible evolutionary trajectories beyond the status of these mutations, particularly among patient-matched metastatic tumors. Our findings confirm the persistence of known clinically-relevant mutations (e.g., those of RAS family of oncogenes) in CRC primary and metastases, yet reveal that latency and interval systemic therapy affect the course of evolutionary events within metastatic lesions. Specifically, our analysis of patient-matched primary and multiple metastatic lesions, developed over time, showed a similar genetic composition for liver metastatic tumors, which were 21-months apart. This genetic makeup was different from those identified in lung metastases developed before manifestation of the second liver metastasis. These results underscore the role of latency in the evolutionary path of metastatic CRC and may have implications for future treatment options.