Identification of stemness-related glycosylation changes in head and neck squamous cell carcinoma.

BACKGROUND: Altered glycosylation is a hallmark of cancer associated with therapy resistance and tumor behavior. In this study, we investigated the glycosylation profile of stemness-related proteins OCT4, CIP2A, MET, and LIMA1 in HNSCC tumors. METHODS: Tumor, adjacent normal tissue, and blood samples of 25 patients were collected together with clinical details. After tissue processing, lectin-based glycovariant screens were performed. RESULTS: Strong correlation between glycosylation profiles of all four stemness-related proteins was observed in tumor tissue, whereas glycosylation in tumor tissue, adjacent normal tissue, and serum was differential. CONCLUSIONS: A mannose- and galactose-rich glycosylation niche associated with stemness-related proteins was identified.

Impact of deep learning-determined smoking status on mortality of cancer patients: never too late to quit.

BACKGROUND: Persistent smoking after cancer diagnosis is associated with increased overall mortality (OM) and cancer mortality (CM). According to the 2020 Surgeon General's report, smoking cessation may reduce CM but supporting evidence is not wide. Use of deep learning-based modeling that enables universal natural language processing of medical narratives to acquire population-based real-life smoking data may help overcome the challenge. We assessed the effect of smoking status and within-1-year smoking cessation on CM by an in-house adapted freely available language processing algorithm. MATERIALS AND METHODS: This cross-sectional real-world study included 29 823 patients diagnosed with cancer in 2009-2018 in Southwest Finland. The medical narrative, International Classification of Diseases-10th edition codes, histology, cancer treatment records, and death certificates were combined. Over 162 000 sentences describing tobacco smoking behavior were analyzed with ULMFiT and BERT algorithms. RESULTS: The language model classified the smoking status of 23 031 patients. Recent quitters had reduced CM [hazard ratio (HR) 0.80 (0.74-0.87)] and OM [HR 0.78 (0.72-0.84)] compared to persistent smokers. Compared to never smokers, persistent smokers had increased CM in head and neck, gastro-esophageal, pancreatic, lung, prostate, and breast cancer and Hodgkin's lymphoma, irrespective of age, comorbidities, performance status, or presence of metastatic disease. Increased CM was also observed in smokers with colorectal cancer, men with melanoma or bladder cancer, and lymphoid and myeloid leukemia, but no longer independently of the abovementioned covariates. Specificity and sensitivity were 96%/96%, 98%/68%, and 88%/99% for never, former, and current smokers, respectively, being essentially the same with both models. CONCLUSIONS: Deep learning can be used to classify large amounts of smoking data from the medical narrative with good accuracy. The results highlight the detrimental effects of persistent smoking in oncologic patients and emphasize that smoking cessation should always be an essential element of patient counseling.

Effect of coronavirus disease 2019 on recurrences and follow up of head and neck squamous cell carcinoma.

OBJECTIVE: This prospective study aimed to evaluate possible diagnostic delays in head and neck squamous cell carcinoma recurrences due to the changed follow-up protocol during the coronavirus disease 2019 pandemic. METHODS: The follow-up appointments of head and neck squamous cell carcinoma patients treated more than one year prior to the pandemic were changed to telephone appointments in order to reduce physical visits to the hospital. All contacts, reasons for contact and recurrent cancers were recorded. RESULTS: There were 17 recurrences during a seven-month study period among 178 patients treated in the previous year (10 per cent); 14 of these recurrences occurred in patients whose treatment had ended less than one year previously and 3 occurred more than one year after treatment had ended. There was no delay in diagnoses of recurrent tumours or treatment despite reduced visits because of the coronavirus disease 2019 pandemic. CONCLUSION: According to our analyses, no delay was caused in the diagnoses of recurrent diseases. Follow up by telephone or telemedicine can be considered as part of the follow-up protocol one year after the treatment of head and neck squamous cell carcinoma when necessary.

Critical review of the follow-up protocol for head and neck cancer patients.

OBJECTIVE: Head and neck cancer follow-up length, interval and content are controversial. Therefore, this study aimed to evaluate the efficacy of the follow-up protocol after curative treatment in head and neck cancer patients. METHOD: Clinical data of 456 patients with new malignancy of the head and neck from a tertiary care centre district from 1999 to 2008 were analysed. Time from treatment, symptoms and second-line treatment outcomes of patients with recurrent disease were evaluated. RESULTS: A total of 94 (22 per cent) patients relapsed during the 5-year follow-up period; 90 per cent of recurrences were found within 3 years. Fifty-six per cent of the patients had subjective symptoms indicating a recurrence of the tumour. All recurrent tumours found during routine follow-up visits without symptoms were found within 34 months after completion of treatment. CONCLUSION: Routine follow up after three years is questionable; recurrent disease beyond this point was detected in only 2 per cent of patients. In this study, all late tumour recurrences had symptoms of the disease. Easy access to extra follow-up visits when symptoms occur could cover the need for late follow up.