CD8 infiltration is associated with disease control and tobacco exposure in intermediate-risk oropharyngeal cancer.

Oropharyngeal squamous cell carcinoma (OPSCC) incidence is increasing at a nearly epidemic rate, largely driven by the human papillomavirus (HPV). Despite the generally favorable clinical outcomes of patients with HPV driven (HPV+) OPSCC, a significant subset of HPV tumors associated with tobacco exposure have diminished treatment response and worse survival. The tumor immune microenvironment (TIME) has been shown to be a critical driver of treatment response and oncologic outcomes in OPSCC generally and HPV+ OPSCC more specifically. However, the impact of tobacco exposure on the TIME in OPSCC patients remains unclear. We analyzed the relationship between TIME, tobacco exposure and clinical outcomes in OPSCC patients (n = 143) with extensive tobacco exposure (median pack-years = 40). P16 overexpression, a surrogate marker of HPV association, was a strong predictor of relapse-free (RFS) and overall survival (OS) (p < 0.001, p < 0.001 respectively) regardless of tobacco exposure and associated strongly with differential infiltration of the tumor by both CD3 and CD8 lymphocytes measured via immunohistochemistry (p < 001, p < 0.001 respectively). CD3 and CD8 infiltration was a strong predictor of RFS and OS and associated strongly with disease stage (AJCC 8th Edition Staging Manual). Tobacco exposure correlated significantly (p < 0.001) with decreased CD8 infiltration in p16+ OPSCC tumors. Our findings demonstrate that the HPV+ OPSCC clinical outcomes are strongly correlated with the TIME, which is potentially modulated by tobacco exposure. Immunomodulatory strategies targeting this disease in smokers must take into consideration the potential modifying effects of tobacco exposure on treatment effectiveness and clinical outcomes.

A spatial neighborhood methodology for computing and analyzing lymph node carcinoma similarity in precision medicine.

Precision medicine seeks to tailor therapy to the individual patient, based on statistical correlates from patients who are similar to the one under consideration. These correlates can and should go beyond genetics, and in general, beyond tabular or array data that can be easily represented computationally and compared. For example, in many types of cancer, cancer treatment and toxicity depend in large measure on the spatial disease spread-e.g., metastasizes to regional lymph nodes in head and neck cancer. However, there is currently a lack of methodology for integrating spatial information when considering patient similarity. We present a novel modeling methodology for the comparison of cancer patients within a cohort, based on the spatial spread of the lymph nodes affected in each patient. The method uses a topological map, bigrams, and hierarchical clustering to group patients based on their similarity. We compare this approach against a nonspatial (categorical) similarity approach where patients are binned solely by their affected nodes. We present similarity results on a 582 head and neck cancer patient cohort, along with two visual abstractions for analysis of the results, and we present clinician feedback. Our novel methodology partitions a patient cohort into clinically meaningful groups more susceptible to treatment side-effects. Such spatially-aware similarity approaches can help maximize the effectiveness of each patient's treatment.

Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration.

We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.

Doublet BRAF/MEK inhibition versus single-agent BRAF inhibition in the management of BRAF-mutant advanced melanoma, biological rationale and meta-analysis of published data

BACKGROUND: We executed a comparative systematic review and meta-analysis of the efficacy and toxicity of doublet BRAF/MEK inhibition versus single-agent BRAF inhibitor in the management of BRAF-mutant advanced melanoma. METHODS: Eligible studies included prospective studies evaluating doublet regimens versus BRAF-inhibitor monotherapy for the management of BRAF-mutant advanced melanoma. RESULTS: Our search strategy yielded 200 potentially relevant citations from searched databases. After preclusion of ineligible studies, four studies were included in the final analysis. Efficacy analyses demonstrate that BRAF/MEK inhibition strategy is associated with a significant improvement in ORR [OR 1.35; 95 % CI (1.16, 1.58); P = 0.0002], PFS [HR 0.56; 95 % CI (0.49, 0.64); P < 0.00001] and OS [HR 0.70; 95 % CI (0.58, 0.84); P = 0.0001]. Moreover, this combination is associated with a higher RR for diarrhea [1.30; 95 % CI (1.30, 1.49); P = 0.0002], decreased ejection fraction [4.63; 95 % CI (2.56, 8.37); P = <0.00001], acneiform dermatitis [1.61; 95 % CI (1.03, 2.53); P = 0.04] and pyrexia [1.98; 95 % CI (1.72, 2.27); P < 0.00001]. CONCLUSIONS: Our meta-analysis has demonstrated that combination of MEK/BRAF inhibitors is associated with higher ORR, PFS and OS. However, this comes at the expense of a higher risk of selected toxicities

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Doublet BRAF/MEK inhibition versus single-agent BRAF inhibition in the management of BRAF-mutant advanced melanoma, biological rationale and meta-analysis of published data.

BACK GROUND: We executed a comparative systematic review and meta-analysis of the efficacy and toxicity of doublet BRAF/MEK inhibition versus single-agent BRAF inhibitor in the management of BRAF-mutant advanced melanoma. METHODS: Eligible studies included prospective studies evaluating doublet regimens versus BRAF-inhibitor monotherapy for the management of BRAF-mutant advanced melanoma. RESULTS: Our search strategy yielded 200 potentially relevant citations from searched databases. After preclusion of ineligible studies, four studies were included in the final analysis. Efficacy analyses demonstrate that BRAF/MEK inhibition strategy is associated with a significant improvement in ORR [OR 1.35; 95 % CI (1.16, 1.58); P = 0.0002], PFS [HR 0.56; 95 % CI (0.49, 0.64); P < 0.00001] and OS [HR 0.70; 95 % CI (0.58, 0.84); P = 0.0001]. Moreover, this combination is associated with a higher RR for diarrhea [1.30; 95 % CI (1.30, 1.49); P = 0.0002], decreased ejection fraction [4.63; 95 % CI (2.56, 8.37); P = <0.00001], acneiform dermatitis [1.61; 95 % CI (1.03, 2.53); P = 0.04] and pyrexia [1.98; 95 % CI (1.72, 2.27); P < 0.00001]. CONCLUSIONS: Our meta-analysis has demonstrated that combination of MEK/BRAF inhibitors is associated with higher ORR, PFS and OS. However, this comes at the expense of a higher risk of selected toxicities.