Wound Healing Complications Associated with Staged Reconstruction after Facial Lentigo Maligna Resection.

Background: The rates and risk factors for wound complications following staged reconstruction after facial lentigo maligna (LM) resection have not been well described. Objectives: (1) To identify the rate and types of wound complications, including infection, graft necrosis, distal flap necrosis, hematoma, superficial epidermolysis, and seroma among patients undergoing staged reconstruction after resection of LM as documented in the surgeon's clinical notes within 30 days of the procedure. (2) To determine a threshold defect size that may predict the development of wound complications. Design and Outcomes: Retrospective review at an academic medical center of patients who underwent staged reconstruction after facial LM resection over a 5-year period. Results: Ninety-eight patients were identified with a mean age of 69.2 ± 13.6 years; 37% of patients were female. The most common defect sites were the cheek (n = 41; 42%) and nose (n = 22; 22%). Twenty-five of 98 patients (26%) demonstrated complications, with the most common being wound infection (36%) and graft necrosis (24%). Those receiving perioperative antibiotics had lower rates of complication (odds ratio [OR]: 0.36; 95% confidence interval [CI]: 0.13,0.96; p = 0.041). Defects greater than 2.7 cm in maximal diameter had the highest sensitivity for predicting complications. Conclusions: Patients undergoing staged reconstruction after facial LM resection have a high rate of wound complication (26%) and defect size > 2.7 cm may be an important risk factor.

Supporting the decision to perform molecular profiling for cancer patients based on routinely collected data through the use of machine learning.

BACKGROUND: Personalized medicine offers targeted therapy options for cancer treatment. However, the decision whether to include a patient into next-generation sequencing (NGS) testing is not standardized. This may result in some patients receiving unnecessary testing while others who could benefit from it are not tested. Typically, patients who have exhausted conventional treatment options are of interest for consideration in molecularly targeted therapy. To assist clinicians in decision-making, we developed a decision support tool using routine data from a precision oncology program. METHODS: We trained a machine learning model on clinical data to determine whether molecular profiling should be performed for a patient. To validate the model, the model's predictions were compared with decisions made by a molecular tumor board (MTB) using multiple patient case vignettes with their characteristics. RESULTS: The prediction model included 440 patients with molecular profiling and 13,587 patients without testing. High area under the curve (AUC) scores indicated the importance of engineered features in deciding on molecular profiling. Patient age, physical condition, tumor type, metastases, and previous therapies were the most important features. During the validation MTB experts made the same decision of recommending a patient for molecular profiling only in 10 out of 15 of their previous cases but there was agreement between the experts and the model in 9 out of 15 cases. CONCLUSION: Based on a historical cohort, our predictive model has the potential to assist clinicians in deciding whether to perform molecular profiling.

Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically Relevant Subgroups of High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients.

INTRODUCTION: The validated 40-gene expression profile (40-GEP) test independently stratifies risk of regional or distant metastasis for cutaneous squamous cell carcinoma (cSCC) tumors with high-risk clinicopathologic features. This study evaluated the stratification of risk by the 40-GEP test in a large cohort of tumors with one or more high-risk factors and in clinically relevant subgroups, including tumors within National Comprehensive Cancer Network (NCCN) high- and very-high-risk groups, lower-stage BWH T1 and T2a tumors, and patients > 65 years old. METHODS: This multicenter (n = 58) performance study of the 40-GEP included 897 patients. Kaplan-Meier analyses were performed to assess risk stratification profiles for 40-GEP Class 1 (low), Class 2A (higher) and Class 2B (highest) risk groups, while nested Cox regression models were used to compare risk prediction of clinicopathologic risk classification systems versus risk classification systems in combination with 40-GEP. RESULTS: Patients classified as 40-GEP Class 1, Class 2A, or Class 2B had significantly different metastatic risk profiles (p < 0.0001). Integrating 40-GEP results into models with individual clinicopathologic risk factors or risk classification systems (Brigham and Women's Hospital, American Joint Committee on Cancer Staging Manual, 8th Edition) and NCCN demonstrated significant improvement in accuracy for prediction of metastatic events (ANOVA for model deviance, p < 0.0001 for all models). CONCLUSION: The 40-GEP test demonstrates accurate, independent, clinically actionable stratification of metastatic risk and improves predictive accuracy when integrated into risk classification systems. The improved accuracy of risk assessment when including tumor biology via the 40-GEP test ensures more risk-aligned, personalized patient management decisions.

Tumor-specific T cells in head and neck cancer have rescuable functionality and can be identified through single-cell co-culture.

BACKGROUND: Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) remains a treatment-resistance disease with limited response to immunotherapy. While T cells in HNSCC are known to display phenotypic dysfunction, whether they retain rescuable functional capacity and tumor-killing capability remains unclear. METHODS: To investigate the functionality and tumor-specificity of tumor-infiltrating lymphocytes (TILs) across HNSCCs, malignant cell lines and TILs were derived from 31 HPV-negative HNSCCs at the time of standard surgical resection. T cell functional capacity was evaluated through ex vivo expansion, immunophenotyping, and IsoLight single-cell proteomics. Tumor-specificity was investigated through both bulk and single-cell tumor-TIL co-culture. RESULTS: TILs could be successfully generated from 24 patients (77%), including both previously untreated and radiation recurrent HNSCCs. We demonstrate that across HNSCCs, TILs express multiple exhaustion markers but maintain a predominantly effector memory phenotype. After ex vivo expansion, TILs retain immunogenic functionality even from radiation-resistant, exhausted, and T cell-depleted disease. We further demonstrate tumor-specificity of T cells across HNSCC patients through patient-matched malignant cell-T cell co-culture. Finally, we use optofluidic technology to establish an autologous single tumor cell-single T cell co-culture platform for HNSCC. Cells derived from three HNSCC patients underwent single-cell co-culture which enabled identification and visualization of individual tumor-killing TILs in real-time in all patients. CONCLUSIONS: These studies show that cancer-specific T cells exist across HNSCC patients with rescuable immunogenicity and can be identified on a single-cell level. These data lay the foundation for development of patient-specific T cell immunotherapies in HNSCC.