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Parathyroid carcinoma (PC) is one of the rarest malignant neoplasms of the human endocrine system, with a prevalence of approximately 0.005% of all oncological diseases. Despite its indolent course, PC generally relapses in about 40%-60% of cases.

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Advances in the detection and treatment of cancer have translated into improved cancer survival rates and a growing population of cancer survivors. These include those living with cancer and individuals free of the disease following treatment. Epidemiological studies demonstrate that cancer survivors are at an increased risk of cardiovascular disease (CVD), with cardiovascular (CV) mortality overtaking cancer mortality in some tumour types.

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Objectives: Assessment of age, sex and smoking-specific risk of cancer diagnosis and non-cancer mortality following primary care consultation for 15 new-onset symptoms.

Methods And Analysis: Data on patients aged 30-99 in 2007-2017 were extracted from a UK primary care database (CPRD Gold), comprising a randomly selected reference group and a symptomatic cohort of patients presenting with one of 15 new onset symptoms (abdominal pain, abdominal bloating, rectal bleed, change in bowel habit, dyspepsia, dysphagia, dyspnoea, haemoptysis, haematuria, fatigue, night sweats, weight loss, jaundice, breast lump and post-menopausal bleed).Time-to-event models were used to estimate outcome-specific hazards for site-specific cancer diagnosis and non-cancer mortality and to estimate cumulative incidence up to 12 months following index consultation.

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Objective: To evaluate signal transducer and activator of transcription 3 (STAT3) inhibition we conducted a co-clinical trial testing danvatirsen, a STAT3 antisense oligonucleotide (ASO) and checkpoint inhibition in conjunction with preclinical experiments.

Methods And Analysis: Orthotopically implanted pancreatic cancer (pancreatic adenocarcinoma (PDAC)) was treated with STAT3 ASO with immune checkpoint inhibition. Tumour infiltrating immune cell populations were characterised via flow cytometry.

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Advanced in vitro models are crucial for studying human airway biology. Our objective was the development and optimization of 3D in vitro models representing diverse airway regions, including deep lung alveolar region. This initiative was aimed at assessing the influence of selective scaffold materials on distinct airway co-culture models.

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