From Base Pairs to City Squares: Comprehensive Precision Oncology for the Future.

SUMMARY: An increased understanding of the role of the social determinants of health in cancer prevention, cancer care, and outcomes can lead to their integration into genetics and genomics as well as informing interventions and clinical trials, creating a comprehensive precision oncology framework.

Molecular Profiling and the Impact of Treatment on Outcomes in Adenoid Cystic Carcinoma Type I and II.

PURPOSE: Adenoid cystic carcinoma (ACC) is an uncommon salivary gland cancer with no approved therapies available to treat advanced, incurable disease. Recent molecular profiling efforts have identified two important subtypes: the more aggressive ACC-I is characterized by Notch pathway alterations and MYC amplification whereas ACC-II demonstrates a more indolent phenotype and TP63 overexpression. EXPERIMENTAL DESIGN: This retrospective observational cohort study involved de-identified samples from 438 patients with ACC with tumor samples sent for commercially-available molecular profiling (Caris Life Sciences). Next-generation whole-exome and whole-transcriptomic sequencing was performed on primary and metastatic samples. Immunostaining for PD-L1 and RNA deconvolution (quanTIseq) was used to explore the tumor immune microenvironment (TME). Real-world clinical and survival outcome metrics were extracted from insurance claims data. RESULTS: MYC expression was 1.61-fold higher (39.8 vs. 24.7; P < 0.0001) among NOTCH1-mutant ACC-I tumors, whereas MYB/L1 fusion rates were similar among ACC-I/II. The median B-cell fraction in the TME was higher among ACC-II (7.1% vs. 5.8%; P < 0.01), although infiltrating T cells subsets were low among either ACC subgroup (both <1%). When pooling systemic treatment categories, ACC-I patients had worse outcomes with available therapies (HR, 3.06; 95% confidence interval, 1.65-5.68; P < 0.01), with no significant difference in overall survival between ACC-I/II based on chemotherapy or VEGFR tyrosine kinase inhibitor exposure in smaller subsets. CONCLUSIONS: We confirmed the previously reported associations with MYC and TP63 in the prognostically relevant subgroups of ACC-I and -II, respectively, and report immunologic differences among these subtypes. Survival outcomes are comparatively worse in ACC-I regardless of treatment type.

A new prognostic model in chemotherapy-treated patients with recurrent or metastatic head and neck cancer: An analysis of ECOG-ACRIN E1305.

INTRODUCTION: For patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) periodic reassessment of prognostic factors provides valuable information that can aid in patient stratification. PATIENTS AND METHODS: This post hoc analysis included all patients with R/M HNSCC enrolled in the ECOG-ACRIN E1305 phase III clinical trial who received first-line treatment with platinum-containing chemotherapy doublet with or without bevacizumab. Overall survival (OS) was estimated using the Kaplan-Meier method. Prognostic factors for OS were identified using univariate and multivariable analyses. A new prognostic model for OS was built retaining the prognostic factors which were significant in the final multivariable analysis (P < 0.05). RESULTS: All 403 study participants were included in the analysis. The median OS in the whole study cohort was 11.8 months (90% confidence intervals [CI], 10.6-13.2). The new prognostic model for OS comprised four risk factors (ECOG performance status [1 versus 0], primary tumor location [other versus oropharynx], presence of bone or liver metastasis, and prior radiation to the head and neck); patients with ≤ 2 (n = 249) and > 2 risk factors (n = 154) had a median OS of 15.2 and 7.6 months, respectively (Hazard ratio, 2.14; 95% CI, 1.73-2.66; P < 0.0001). CONCLUSIONS: The new proposed model includes 4 clinical prognostic factors that can be readily assessed at baseline. Similar models have the potential to improve trial design and optimize stratification of patients with R/M HNSCC.

Predictive capacity of immune-related adverse events and cytokine profiling in neoadjuvant immune checkpoint inhibitor trials for head and neck squamous cell carcinoma.

OBJECTIVES: Certain low-level immune-related adverse events (irAEs) have been associated with survival benefits in patients with various solid tumors on immune checkpoint inhibitors (ICIs). We aimed to investigate the association between irAEs and response to neoadjuvant ICIs in patients with head and neck squamous cell carcinoma (HNSCC) and to identify differences in circulating cytokine levels based on irAE status. METHODS: This was a retrospective cohort study including three neoadjuvant clinical trials from July 2017 to January 2022: NCT03238365 (nivolumab ± tadalafil), NCT03854032 (nivolumab ± BMS986205), NCT03618654 (durvalumab ± metformin). The presence and type of irAEs, pathologic treatment response, and survival were compared. Canonical linear discriminant analysis (LDA) was performed to identify combinations of circulating cytokines predictive of irAEs using plasma sample multiplex assay. RESULTS: Of 113 participants meeting inclusion criteria, 32 (28.3%) developed irAEs during treatment or follow-up. Positive p16 status was associated with irAEs (odds ratio [OR] 2.489; 95% CI 1.069-6.119; p = 0.043). irAEs were associated with pathologic treatment response (OR 3.73; 95% CI 1.34-10.35; p = 0.011) and with higher OS in the combined cohort (HR 0.319; 95% CI 0.113-0.906; p = 0.032). Patients with irAEs within the nivolumab cohort had significant elevations of select cytokines pre-treatment. Canonical LDA identified key drivers of irAEs among all trials, which were highly predictive of future irAE status. CONCLUSIONS: irAEs are associated with response to neoadjuvant ICI therapy in HNSCC and can serve as clinical indicators for improved clinical outcomes. irAEs can be predicted by concentrations of several circulating cytokines prior to treatment.

Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in patients with cancer.

The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.