The occurrence of both melanoma and glioma was first suggested by the observation of a familial association between these conditions, which was later confirmed by the description of the melanoma-astrocytoma syndrome, an extremely rare, inherited affliction in which people have an increased risk of developing melanoma and nervous system tumors. Taking into consideration the common embryologic precursor, the neuroectoderm, it was hypothesized that this syndrome is associated with a genetic disorder. While some families with germline CDKN2A mutations are prone to develop just melanomas, others develop both melanomas and astrocytomas or even other nervous-system neoplasms. Herein, we report the case of a 63-year-old male patient with no personal or family history of malignancy who had primary melanoma followed by glioblastoma. Our case report suggests that the occurrence of both melanoma and glioblastoma is most likely not coincidental but instead linked to genetic mutations of common embryologic precursors or signaling pathways.

OBJECTIVE: This study investigated the frequency of cancer-associated vasculitis, the types of associated cancers and vasculitides, and the temporal relationship in Korean patients who were diagnosed with both cancers and vasculitides.
METHODS: This study performed a digital search of the clinical data repository using selected diagnostic terms of vasculitides among patients diagnosed with cancers from May 2001 to May 2021. The time gap between the time of diagnosis of \'cancers\' and that of \'vasculitides\' was limited to 3 years. The types of cancers and vasculitides were reviewed.
RESULTS: The mean age of 73 patients with both cancers and vasculitides with a time gap of fewer than 3 years was 53.0 years and 42.5% were men. Of the 215,897 patients with cancers, 73 patients were also diagnosed with vasculitides (0.034%). The most common type of cancer was thyroid cancer (28.8%), followed by lymphoma (13.7%), whereas the most frequent type of vasculitis associated with cancer was Behcet disease (52.1%), followed by granulomatosis with polyangiitis (12.3%). The median time gap between cancer and vasculitis was - 17.0 days. Among vasculitides, Behcet disease was closely associated with various cancers compared to other types. Twenty-one patients exhibited both cancers and vasculitides between 0 and 90 days after the diagnosis of the corresponding cancer.
CONCLUSIONS: The frequency of cancer-associated vasculitis was 0.034% in Korean patients. The types of cancers and vasculitides in cancer-associated vasculitis and the distributions of sex and age may be dependent on ethnic and geographic differences. Key Points • The frequency of cancer-associated vasculitis was 0.034% in Korean patients. • The most common cancer and vasculitis in cancer-associated vasculitis were thyroid cancer and Behcet disease. • The types of cancers and vasculitides in cancer-associated vasculitis seemed to be dependent on ethnic and geographic differences.

Predictive patient stratification is greatly emerging, because it allows us to prospectively identify which patients will benefit from what interventions before their condition worsens. In the biomedical research, a number of stratification methods have been successfully applied and have assisted treatment process. Because of heterogeneity and complexity of medical data, it is very challenging to integrate them and make use of them in practical clinic. There are two major challenges of data integration. Firstly, since the biomedical data has a high number of dimensions, combining multiple data leads to the hard problem of vast dimensional space handling. The computation is enormously complex and time-consuming. Secondly, the disparity of different data types causes another critical problem in machine learning for biomedical data. It has a great need to develop an efficient machine learning framework to handle the challenges.
In this paper, we propose a fast-multiple kernel learning framework, referred to as fMKL-DR, that optimise equations to calculate matrix chain multiplication and reduce dimensions in data space. We applied our framework to two case studies, Alzheimer\'s disease (AD) patient stratification and cancer patient stratification. We performed several comparative evaluations on various biomedical datasets.
In the case study of AD patients, we enhanced significantly the multiple-ROIs approach based on MRI image data. The method could successfully classify not only AD patients and non-AD patients but also different phases of AD patients with AUC close to 1. In the case study of cancer patients, the framework was applied to six types of cancers, i.e., glioblastoma multiforme cancer, ovarian cancer, lung cancer, breast cancer, kidney cancer, and liver cancer. We efficiently integrated gene expression, miRNA expression, and DNA methylation. The results showed that the classification model basing on integrated datasets was much more accurate than classification model basing on the single data type.
The results demonstrated that the fMKL-DR remarkably improves computational cost and accuracy for both AD patient and cancer patient stratification. We optimised the data integration, dimension reduction, and kernel fusion. Our framework has great potential for mining large-scale cohort data and aiding personalised prevention.

BACKGROUND: Urogenital cancers are not an uncommon occurrence in daily practice. Prostate cancer is the second most frequent cancer in men, kidney cancer accounts for 2.4% of all cancers and bladder cancers represent 3.1% of cancers in both men and women [1]. However, the cases of a simultaneous development of all three cancers, including one with a neuroendocrine component, are very few and far between.
METHODS: Our case report involves a case of a patient with prostate adenocarcinoma, clear-cell renal carcinoma, papillary renal carcinoma and small-cell bladder cancer. The patient was treated as if he had separate pathologies by a multidisciplinary team: surgical and oncological, performing radical cystoprostatectomy with left perifascial nephroureterectomy, right ureterostomy and adjuvant chemotherapy, with excellent outcome even four years after the initial diagnosis.
CONCLUSIONS: The distinct features of this case are the occurence of four different malignancies of the urogenital system, the family history of colon cancer, the development of small-cell carcinoma of the bladder, which is extremely rare and the good outcome, despite the quadruple malignancies and the aggresivity of the small-cell carcinoma.
CONCLUSIONS: Mutiple primary malignancies are a relatively rare pathology, but should be considered as a possibility in patients who already had a second malignancy. Cases of patients with MPMs should be supervised by a multidisciplinary team and should be followed closely.

Hepatitis C virus (HCV) infection causes hepatocellular carcinoma (HCC) and subtypes of non-Hodgkin lymphoma (NHL). Associations with other cancers are not established. The authors systematically assessed associations between HCV infection and cancers in the US elderly population.
This was a registry-based case-control study using Surveillance, Epidemiology, and End Results (SEER)-Medicare data in US adults aged ≥66 years. Cases (n = 1,623,538) were patients who had first cancers identified in SEER registries (1993-2011). Controls (n = 200,000) were randomly selected, cancer-free individuals who were frequency-matched to cases on age, sex, race, and calendar year. Associations with HCV (documented by Medicare claims) were determined using logistic regression.
HCV prevalence was higher in cases than in controls (0.7% vs 0.5%). HCV was positively associated with cancers of the liver (adjusted odds ratio [aOR] = 31.5; 95% confidence interval [CI], 29.0-34.3), intrahepatic bile duct (aOR, 3.40; 95% CI, 2.52-4.58), extrahepatic bile duct (aOR, 1.90; 95% CI, 1.41-2.57), pancreas (aOR, 1.23; 95% CI, 1.09-1.40), and anus (aOR, 1.97; 95% CI, 1.42-2.73); nonmelanoma nonepithelial skin cancer (aOR, 1.53; 95% CI, 1.15-2.04); myelodysplastic syndrome (aOR, 1.56; 95% CI, 1.33-1.83); and diffuse large B-cell lymphoma (aOR, 1.57; 95% CI, 1.34-1.84). Specific skin cancers associated with HCV were Merkel cell carcinoma (aOR, 1.92; 95% CI, 1.30-2.85) and appendageal skin cancers (aOR, 2.02; 95% CI, 1.29-3.16). Inverse associations were observed with uterine cancer (aOR, 0.64; 95% CI, 0.51-0.80) and prostate cancer (aOR, 0.73; 95% CI, 0.66-0.82). Associations were maintained in sensitivity analyses conducted among individuals without documented alcohol abuse, cirrhosis, or hepatitis B or human immunodeficiency virus infections and after adjustment for socioeconomic status. Associations of HCV with other cancers were not observed.
HCV is associated with increased risk of cancers other than HCC in the US elderly population, notably bile duct cancers and diffuse large B-cell lymphoma. These results support a possible etiologic role for HCV in an expanded group of cancers. Cancer 2017;123:1202-1211. © 2016 American Cancer Society.

BACKGROUND: Morphine is widely used for pain management in cancer patients. Use of heroin, a morphine derivative, is a risk factor for acute coronary syndrome (ACS).
OBJECTIVE: This study investigates the risk of ACS associated with morphine use by comparing the incidence of ACS in cancer patients treated with and without morphine.
METHODS: This is a population-based nested case-control study using the Longitudinal Health Insurance Database 2000 in Taiwan. In total, 31,384 patients on the database were diagnosed with cancer without prior history of ACS during 1998-2010. In this cohort, 499 patients subsequently developed ACS and 30,885 patients did not. The 499 patients were designated as the ACS group; controls were selected from the remaining 30,885 patients and matched 3:1 to each case for age, sex, year of cancer diagnosis, and index year. Logistic regression was used to estimate the odds ratios and 95% confidence intervals, and the multivariable model was applied to control for age, sex, and Charlson comorbidity score.
RESULTS: Cancer patients who received morphine had a 32% higher risk of developing ACS than non-morphine users. This increase in risk was significant when evaluating the overall cancer patients, but non-significant when evaluating any specific cancer type. The risk of ACS increased significantly with increasing morphine dosage (to ≥65 mg/y).
CONCLUSIONS: Morphine treatment is associated with a modest increase in risk of ACS in patients with malignancy, but this association displays low significance in specific cancer types.