Agnostic drug development revisited.

The advent of molecular profiling and the generalization of next generation sequencing in oncology has enabled the identification of patients who could benefit from targeted agents. Since the tumor-agnostic approval of pembrolizumab for patients with MSI-High tumors in 2017, different molecularly-guided therapeutics have been awarded approvals and progressively incorporated in the treatment landscape across multiple tumor types. As the number of tumor-agnostic targets considered druggable expands in the clinic, novel challenges will reshape the drug development field involving all the stakeholders in oncology. In this review, we provide an overview of current tumor-agnostic approvals and discuss promising candidate therapeutics for tumor-agnostic designation and challenges for their broad implementation.

Intratumoral therapies in head and neck squamous cell carcinoma: A systematic review and future perspectives.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) presents an ideal scenario for intratumoral therapies (IT), due to its local recurrence pattern and frequent superficial extension. IT therapies aim to effect tumor regression by directly injecting antineoplastic agents into lesions. However, there is a lack of updated evidence regarding IT therapies in HNSCC. PATIENTS AND METHODS: A systematic literature search (CRD42023462291) was conducted using WebOfScience, ClinicalTrials.gov, and conference abstracts from ESMO and ASCO, identifying for IT clinical trials in patients with HNSCC, from database creation to September 12th, 2023. Efficacy as well as safety (grade ≥ 3 treatment-related adverse events[trAEs]) were reported. RESULTS: After evaluation of 1180 articles identified by the systematic search, 31 studies treating 948 patients were included. IT injectables were categorized as chemotherapies with or without electroporation (k = 4, N = 268), oncolytic viruses, plasmids, and bacteria-based (k = 16, N = 446), immunotherapies and EGFR-based therapies (k = 5, N = 160), radioenhancer particles (k = 2, N = 68), and calcium electroporation (k = 1, n = 6). EGFR-antisense plasmids, NBTXR3 radioenhancer and immune innate agonists show best overall response rates, at 83 %, 81 % and 44 % respectively. Eleven (35 %) studies added systemic therapy or radiotherapy to the IT injections. No study used predictive biomarkers to guide patient selection. 97 % studies were phase I-II. Safety-wise, electroporation and epinephrine-based injectable trials had significant local symptoms such as necrosis, fistula formation and post-injection dysphagia. Treatment-related tumor haemorrhages of various grades were described in several trials. Grade ≥ 3 trAEs attributable to the other therapies mainly comprised general symptoms such as fatigue. There were 3 injectable-related deaths across the systematic review. CONCLUSION: This is the first review to summarize all available evidence of IT in HNSCC. As of today, IT therapies lack sufficient evidence to recommend their use in clinical practice. Continuing research on potential molecules, patient selection, safe administration of injections and controlled randomized trials are needed to assess their added benefit.

Impact on costs and outcomes of multi-gene panel testing for advanced solid malignancies: a cost-consequence analysis using linked administrative data.

Background: To date, economic analyses of tissue-based next generation sequencing genomic profiling (NGS) for advanced solid tumors have typically required models with assumptions, with little real-world evidence on overall survival (OS), clinical trial enrollment or end-of-life quality of care. Methods: Cost consequence analysis of NGS testing (555 or 161-gene panels) for advanced solid tumors through the OCTANE clinical trial (NCT02906943). This is a longitudinal, propensity score-matched retrospective cohort study in Ontario, Canada using linked administrative data. Patients enrolled in OCTANE at Princess Margaret Cancer Centre from August 2016 until March 2019 were matched with contemporary patients without large gene panel testing from across Ontario not enrolled in OCTANE. Patients were matched according to 19 patient, disease and treatment variables. Full 2-year follow-up data was available. Sensitivity analyses considered alternative matched cohorts. Main Outcomes were mean per capita costs (2019 Canadian dollars) from a public payer's perspective, OS, clinical trial enrollment and end-of-life quality metrics. Findings: There were 782 OCTANE patients with 782 matched controls. Variables were balanced after matching (standardized difference <0.10). There were higher mean health-care costs with OCTANE ($79,702 vs. $59,550), mainly due to outpatient and specialist visits. Publicly funded drug costs were less with OCTANE ($20,015 vs. $24,465). OCTANE enrollment was not associated with improved OS (restricted mean survival time [standard error]: 1.50 (±0.03) vs. 1.44 (±0.03) years, log-rank p = 0.153), varying by tumor type. In five tumor types with ≥35 OCTANE patients, OS was similar in three (breast, colon, uterus, all p > 0.40), and greater in two (ovary, biliary, both p < 0.05). OCTANE was associated with greater clinical trial enrollment (25.4% vs. 9.5%, p < 0.001) and better end-of-life quality due to less death in hospital (10.2% vs. 16.4%, p = 0.003). Results were robust in sensitivity analysis. Interpretation: We found an increase in healthcare costs associated with multi-gene panel testing for advanced cancer treatment. The impact on OS was not significant, but varied across tumor types. OCTANE was associated with greater trial enrollment, lower publicly funded drug costs and fewer in-hospital deaths suggesting important considerations in determining the value of NGS panel testing for advanced cancers. Funding: T.P H holds a research grant provided by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario (#IA-035 and P.HSR.158) and through funding of the Canadian Network for Learning Healthcare Systems and Cost-Effective 'Omics Innovation (CLEO) via Genome Canada (G05CHS).

Selinexor for the treatment of recurrent or metastatic salivary gland tumors: Results from the GEMS-001 clinical trial.

OBJECTIVES: We aimed to evaluate the activity of selinexor, an oral selective inhibitor of nuclear export, in patients with recurrent or metastatic salivary gland tumors (SGT). METHODS: GEMS-001 is an open-label Phase 2 study for patients with recurrent or metastatic SGT with two parts. In Part 1 of the protocol, patients had tumor samples profiled with targeted next generation sequencing as well as immunohistochemistry for androgen receptor, HER-2 and ALK. For Part 2, patients with no targeted therapies available were eligible to receive selinexor 60 mg given twice weekly every 28 days. The primary endpoint was objective response rate. Secondary endpoints included progression-free survival (PFS) and prevalence of druggable alterations across SGT. RESULTS: One hundred patients were enrolled in GEMS-001 and underwent genomic and immunohistochemistry profiling. A total of 21 patients who lacked available matched therapies were treated with selinexor. SGT subtypes (WHO classification) included adenoid cystic carcinoma (n = 10), salivary duct carcinoma (n = 3), acinic cell carcinoma (n = 2), myoepithelial carcinoma (n = 2), carcinoma ex pleomorphic adenoma (n = 2) and other (n = 2). Of 18 evaluable patients, stable disease (SD) was observed in 17 patients (94%) (SD ≥6 months in 7 patients (39%)). However, no objective responses were observed. The median PFS was 4.9 months (95% confidence interval, 3.4-10). The most common treatment-related Grade 1-2 adverse events were nausea [17 patients (81%)], fatigue [16 patients (76%)], and dysgeusia [12 patients (57%)]. Most common treatment-related Grade 3-4 adverse events were hyponatremia [3 patients (14%)], neutrophil count decrease [3 patients (14%)] and cataracts [2 patients (10%)]. No treatment-related deaths were observed. CONCLUSIONS: Although tumor reduction was observed across participants, single agent selinexor anti-tumor activity was limited.

Safety, Immunologic, and Clinical Activity of Durvalumab in Combination with Olaparib or Cediranib in Advanced Leiomyosarcoma: Results of the DAPPER Clinical Trial.

PURPOSE: Non-inflamed (cold) tumors such as leiomyosarcoma do not benefit from immune checkpoint blockade (ICB) monotherapy. Combining ICB with angiogenesis or PARP inhibitors may increase tumor immunogenicity by altering the immune cell composition of the tumor microenvironment (TME). The DAPPER phase II study evaluated the safety, immunologic, and clinical activity of ICB-based combinations in pretreated patients with leiomyosarcoma. PATIENTS AND METHODS: Patients were randomized to receive durvalumab 1,500 mg IV every 4 weeks with either olaparib 300 mg twice a day orally (Arm A) or cediranib 20 mg every day orally 5 days/week (Arm B) until unacceptable toxicity or disease progression. Paired tumor biopsies, serial radiologic assessments and stool collections were performed. Primary endpoints were safety and immune cell changes in the TME. Objective responses and survival were correlated with transcriptomic, radiomic, and microbiome parameters. RESULTS: Among 30 heavily pretreated patients (15 on each arm), grade ≥ 3 toxicity occurred in 3 (20%) and 2 (13%) on Arms A and B, respectively. On Arm A, 1 patient achieved partial response (PR) with increase in CD8 T cells and macrophages in the TME during treatment, while 4 had stable disease (SD) ≥ 6 months. No patients on Arm B achieved PR or SD ≥ 6 months. Transcriptome analysis showed that baseline M1-macrophage and B-cell activity were associated with overall survival. CONCLUSIONS: Durvalumab plus olaparib increased immune cell infiltration of TME with clinical benefit in some patients with leiomyosarcoma. Baseline M1-macrophage and B-cell activity may identify patients with leiomyosarcoma with favorable outcomes on immunotherapy and should be further evaluated.

A pan-cancer clinical platform to predict immunotherapy outcomes and prioritize immuno-oncology combinations in early-phase trials.

BACKGROUND: Immunotherapy is effective, but current biomarkers for patient selection have proven modest sensitivity. Here, we developed VIGex, an optimized gene signature based on the expression level of 12 genes involved in immune response with RNA sequencing. METHODS: We implemented VIGex using the nCounter platform (Nanostring) on a large clinical cohort encompassing 909 tumor samples across 45 tumor types. VIGex was developed as a continuous variable, with cutoffs selected to detect three main categories (hot, intermediate-cold and cold) based on the different inflammatory status of the tumor microenvironment. FINDINGS: Hot tumors had the highest VIGex scores and exhibited an increased abundance of tumor-infiltrating lymphocytes as compared with the intermediate-cold and cold. VIGex scores varied depending on tumor origin and anatomic site of metastases, with liver metastases showing an immunosuppressive tumor microenvironment. The predictive power of VIGex-Hot was observed in a cohort of 98 refractory solid tumor from patients treated in early-phase immunotherapy trials and its clinical performance was confirmed through an extensive metanalysis across 13 clinically annotated gene expression datasets from 877 patients treated with immunotherapy agents. Last, we generated a pan-cancer biomarker platform that integrates VIGex categories with the expression levels of immunotherapy targets under development in early-phase clinical trials. CONCLUSIONS: Our results support the clinical utility of VIGex as a tool to aid clinicians for patient selection and personalized immunotherapy interventions. FUNDING: BBVA Foundation; 202-2021 Division of Medical Oncology and Hematology Fellowship award; Princess Margaret Cancer Center.

Patient-Centric Approaches for Phase I Combination Trials Come on Stage.

SUMMARY: A disruptive clinical trial design allowed Drilon and colleagues to demonstrate proof of concept of the potential of PF-07284892 to overcome resistance mechanisms to targeted therapies in the clinic. See related article by Drilon et al., p. 1789 (7).

Nutritional status associates with immunotherapy clinical outcomes in recurrent or metastatic head and neck squamous cell carcinoma patients.

BACKGROUND: Beyond programmed death-ligand 1 (PD-L1) assessed by the combined positive score (CPS) and tumor mutational burden (TMB), no other biomarkers are approved for immunotherapy interventions. Here, we investigated whether additional clinical and pathological variables may impact on immunotherapy outcomes in recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) patients. METHODS: R/M HNSCC patients treated with immunotherapy were reviewed. Analyzed variables at baseline included: clinicopathological, laboratory, and variables reflecting the host nutritional status such as the prognostic nutritional index (PNI) and albumin. The primary endpoint was progression free survival (PFS). The secondary endpoints were overall survival (OS) and objective response rate (ORR). Univariable and multivariable Cox models were fitted and random forest algorithm was used to estimate the importance of each prognostic variable. RESULTS: A total of 100 patients were treated with immunotherapy; 50% with single agent and 50% with experimental immunotherapy combinations. In the multivariable analysis, both ECOG performance status (HR: 1.73; 95%CI 1.07-2.82; p = 0.03) and PNI levels (10-point increments, HR: 0.66; 0.46-0.95; p = 0.03) were significantly associated with PFS. However, the derived neutrophil to lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) were not significantly associated with PFS (p-values > 0.15). In the OS analysis, albumin and PNI were the only statistically significant factors in the multivariable model (p < 0.001). CONCLUSIONS: In our cohort, PNI and ECOG performance status were most strongly associated with PFS in R/M HNSCC patients treated with immunotherapy. These results suggest that parameters informative of nutritional status should be considered before immunotherapy.

A risk stratification model for toxicities in phase 1 immunotherapy trials.

INTRODUCTION: Despite the increased number of novel immunotherapy (IO) agents under current development, their toxicity profile remains to be fully elucidated. METHODS: An IO risk stratification model was developed based on 5 different variables: treatment-related deaths; rate of grade ≥3 treatment-related adverse events or treatment-emergent adverse events; grade ≥2 encephalopathy or central nervous system toxicity; grade ≥2 cytokine release syndrome; and the number and type of dose-limiting toxicity. Phase 1 IO trials published from January 2014 to December 2020 were reviewed and categorised based on our risk stratification model into three categories: low-, intermediate- and high-risk. Clinical trial variables were associated with the high-risk category. To review the quality of reporting across phase 1 IO trials, a subset of studies was further examined by the use of the ASCO/SITC Trial Reporting in Immuno-Oncology (TRIO) standards. RESULTS: Different IO compounds demonstrated diverse risk profiles. In multivariable analysis, combination versus IO single agent treatment, and testing IO agents different from anti-programmed death-1/programmed death ligand-1 (anti-PD1/L1), anti-cytotoxic t-lymphocyte antigen-4 (anti-CTLA4) antibodies and anti-cancer vaccines were associated with a higher toxicity risk. None of the studies examined in our dataset reported all the items included in the TRIO standards. CONCLUSIONS: Our results have important implications for future clinical trial design. Additionally, standards for reporting are urgently needed.

Impact of pharmacodynamic biomarkers in immuno-oncology phase 1 clinical trials.

BACKGROUND: Phase 1 immuno-oncology (IO) trials frequently involve pharmacodynamic (PD) biomarker assessments involving tumour biopsies and/or blood collection, with increasing use of molecular imaging. PD biomarkers are set to play a fundamental role in early drug development of immuno-oncology (IO) agents. In the IO era, the impact of PD biomarkers for confirmation of biologic activity and their role in subsequent drug development have not been investigated. METHODS: Phase 1 studies published between January 2014 and December 2020 were reviewed. Studies that reported on-treatment PD biomarkers [tissue-derived (tissue-PD), blood-based (blood-PD) and imaging-based (imaging-PD)] were analysed. PD biomarker results and their correlation with clinical activity endpoints were evaluated. Authors' statements on the influence of PD biomarkers on further drug development decisions, and subsequent citations of PD biomarker study results were recorded. RESULTS: Among 386 trials, the most frequent IO agent classes evaluated were vaccines (32%) and PD-(L)1 inhibitors (25%). No PD biomarker assessments were reported in 100 trials (26%). Of the remaining 286, blood-PD, tissue-PD, and imaging-PD data were reported in 270 (94%), 94 (33%), and 12 (4%) trials, respectively. Assessments of more than one PD biomarker type were reported in 82 studies (29%). Similar proportions of blood-PD (9%), tissue-PD (7%), and imaging-PD studies (8%) had positive results that correlated with clinical activity. Results of 22 PD biomarker studies (8%) were referenced in subsequent clinical trials. CONCLUSIONS: Most phase 1 IO studies performed PD biomarker assessments. Overall, positive PD biomarker results were infrequently correlated with clinical activity or cited in subsequent trials, suggesting a limited impact on subsequent drug development. With emerging health regulatory emphasis on optimal dose selection based on PD activity, more informative and integrative multiplexed assays that capture the complexity of tumour-host immunity interactions are warranted to improve phase 1 IO trial methodology.

Novel classes of immunotherapy for breast cancer.

Immune-checkpoint inhibitors have profoundly changed the treatment landscape for many tumor types. Despite marked improvements in disease control for highly immunogenic cancers, the clinical impact of checkpoint inhibitors in breast cancers to date is limited. Breast cancer is a heterogeneous disease with different levels of PD-L1 expression and variable tumor microenvironment (TME) composition according to molecular subtype. With emerging evidence of the role of different factors involved in immune evasion, there are promising new immunotherapy targets that will reshape early drug development for metastatic breast cancer. This review examines the available evidence for existing and emerging immuno-oncology (IO) approaches including small molecules targeting different regulators of the cancer-immunity cycle.

Phase I prognostic online (PIPO): A web tool to improve patient selection for oncology early phase clinical trials.

PURPOSE: Patient selection in phase 1 clinical trials (Ph1t) continues to be a challenge. The aim of this study was to develop a user-friendly prognostic calculator for predicting overall survival (OS) outcomes in patients to be included in Ph1t with immune checkpoint inhibitors (ICIs) or targeted agents (TAs) based on clinical parameters assessed at baseline. METHODS: Using a training cohort with consecutive patients from the VHIO phase 1 unit, we constructed a prognostic model to predict median OS (mOS) as a primary endpoint and 3-month (3m) OS rate as a secondary endpoint. The model was validated in an internal cohort after temporal data splitting and represented as a web application. RESULTS: We recruited 799 patients (training and validation sets, 558 and 241, respectively). Median follow-up was 21.2 months (m), mOS was 10.2 m (95% CI, 9.3-12.7) for ICIs cohort and 7.7 m (95% CI, 6.6-8.6) for TAs cohort. In the multivariable analysis, six prognostic variables were independently associated with OS - ECOG, number of metastatic sites, presence of liver metastases, derived neutrophils/(leukocytes minus neutrophils) ratio [dNLR], albumin and lactate dehydrogenase (LDH) levels. The phase 1 prognostic online (PIPO) calculator showed adequate discrimination and calibration performance for OS, with C-statistics of 0.71 (95% CI 0.64-0.78) in the validation set. The overall accuracy of the model for 3m OS prediction was 87.2% (95% CI 85%-90%). CONCLUSIONS: PIPO is a user-friendly objective and interactive tool to calculate specific survival probabilities for each patient before enrolment in a Ph1t. The tool is available at https://pipo.vhio.net/.