Association between Average Vitamin D Levels and COVID-19 Mortality in 19 European Countries-A Population-Based Study.

Early epidemic reports have linked low average 25(OH) vitamin D levels with increased COVID-19 mortality. However, there has been limited updated research on 25(OH) vitamin D and its impact on COVID-19 mortality. This study aimed to update the initial report studying the link between vitamin D deficiency and COVID-19 mortality by using multi-country data in 19 European countries up to the middle of June 2023. COVID-19 data for 19 European countries included in this study were downloaded from Our World in Data from 1 March 2020, to 14 June 2023, and were included in the statistical analysis. The 25(OH) vitamin D average data were collected by conducting a literature review. A generalized estimation equation model was used to model the data. Compared to European countries with 25(OH) vitamin D levels of ≤50 nmol/L, European countries with 25(OH) vitamin D average levels greater than 50 nmol/L had lower COVID-19 mortality rates (RR = 0.794, 95% CI: 0.662-0.953). A statistically significant negative Spearman rank correlation was observed between 25(OH) vitamin D average levels and COVID-19 mortality. We also found significantly lower COVID-19 mortality rates in countries with high average 25(OH) vitamin D levels. Randomized trials on vitamin D supplementation are needed. In the meantime, the issue of vitamin D use should be debated in relation to the ongoing discussions of national post-COVID-19 resilience against future pandemics.

Years of life lost due to cancer in the United Kingdom from 1988 to 2017.

BACKGROUND: We investigated the application of years of life lost (YLL) in routine cancer statistics using cancer mortality data from 1988 to 2017. METHODS: Cancer mortality data for 17 cancers and all cancers in the UK from 1988 to 2017 were provided by the UK Association of Cancer Registries by sex, 5-year age group, and year. YLL, age-standardised YLL rate (ASYR) and age-standardised mortality rate (ASMR) were estimated. RESULTS: The annual average YLL due to cancer, in the time periods 1988-1992 and 2013-2017, were about 2.2 and 2.3 million years, corresponding to 4510 and 3823 ASYR per 100,000 years, respectively. During 2013-2017, the largest number of YLL occurred in lung, bowel and breast cancer. YLL by age groups for all cancers showed a peak between 60-64 and 75-79. The relative contributions to incidence, mortality, and YLL differ between cancers. For instance, pancreas (in women and men) made up a smaller proportion of incidence (3%) but bigger proportion of mortality (6 and 5%) and YLL (5 and 6%), whereas prostate cancer (26% of incidence) contributed 13% mortality and 9% YLL. CONCLUSION: YLL is a useful measure of the impact different cancers have on society and puts a higher weight on cancer deaths in younger individuals.

A method of correction for heaping error in the variables using validation data.

When self-reported data are used in statistical analysis to estimate the mean and variance, as well as the regression parameters, the estimates tend, in many cases, to be biased. This is because interviewees have a tendency to heap their answers to certain values. The aim of the paper is to examine the bias-inducing effect of the heaping error in self-reported data, and study the effect on the heaping error on the mean and variance of a distribution as well as the regression parameters. As a result a new method is introduced to correct the effects of bias due to the heaping error using validation data. Using publicly available data and simulation studies, it can be shown that the newly developed method is practical and can easily be applied to correct the bias in the estimated mean and variance, as well as in the estimated regression parameters computed from self-reported data. Hence, using the method of correction presented in this paper allows researchers to draw accurate conclusions leading to the right decisions, e.g. regarding health care planning and delivery.

The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis.

Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.

Histopathologic False-positive Diagnoses of Prostate Cancer in the Age of Immunohistochemistry.

There are few studies into the rate and causes of histopathologic false-positive diagnosis of prostate cancer. Only 2 of these, including a previous one from our group, incorporate survival data. In addition, in none of the previous studies had immunohistochemistry (IHC) been originally requested on any of the misdiagnosed cases. Diagnostic biopsies (n=1080) and transurethral resection of prostate specimens (n=314) from 1394 men with clinically localized prostate cancer diagnosed in the United Kingdom but treated conservatively between 1990 and 2003 were reviewed by a panel of 3 genitourinary pathologists. Thirty-five cases were excluded for being potentially incomplete. Of the remaining 1359, 30 (2.2%) were reassigned to a nonmalignant category (26 benign and 4 suspicious for malignancy). IHC had been originally performed on 7 of these. The reasons for the errors were recorded on each case: adenosis (19), partial atrophy (3), prostatic intraepithelial neoplasia (2), seminal vesicle epithelium (1), and hyperplasia (1). Follow-up of these men revealed only one prostate cancer-related death, possibly due to unsampled tumor. In conclusion, a relatively small number of prostate cancer mimics were responsible for a large proportion of the false-positive prostate cancer diagnoses and the use of IHC did not prevent the overcall of benign entities as cancer in approximately a quarter of these cases. Targeting these mimics at educational events and raising awareness of the pitfalls in the interpretation of IHC in prostate cancer diagnosis, emphasizing that glands within a suspicious focus should be treated as a whole rather than individually, may be beneficial in lowering the rate of false-positive diagnosis.

Should reporting of peri-neural invasion and extra prostatic extension be mandatory in prostate cancer biopsies? correlation with outcome in biopsy cases treated conservatively.

The identification of perineural invasion (PNI) and extraprostatic extension (ECE) in prostate cancer (PC) biopsies is time consuming and can be difficult. Although this is required information in many datasets, there is little evidence on their effect on outcome in patients treated conservatively. Cases of PC were identified from three cancer registries in the UK from men with clinically localized prostate cancer diagnosed by needle biopsy from 1990-2003. The endpoint was prostate cancer death (DOD). Patients treated radically within 6 months, those with objective evidence of metastases or who had prior hormone therapy were excluded. Follow-up was through cancer registries up until 2012. Deaths were divided into those from PC and those from other causes, according to WHO criteria. 988 biopsy cases (6522 biopsy cores) were centrally reviewed by three uropathologists and assigned a Gleason score and Grade Group (GG). The presence of both PNI and ECE was recorded. Of 988 patients, PNI was present in 288 (DOD = 75) and ECE in 23 (DOD = 5). On univariable analysis PNI was highly significantly associated with DOD (hazard ratio [HR] 2.28, 95% CI: 1.68, 3.1, log-rank test p-value = 4.8 × 10-8), but ECE was not (log-rank test p-value = 0.334). On multivariable analysis with GG, serum PSA (per 10%), clinical stage and extent of disease (per 10%), PNI lost significance (HR 1.16, 95% CI: 0.83, 1.63, likelihood ratio test p-value = 0.371). The utility of routinely examining prostate biopsies for ECE and PNI is doubtful as it is not independently associated with higher grade, stage or prognosis.

Performance and Diagnostic Accuracy of a Urine-Based Human Papillomavirus Assay in a Referral Population.

Background: Human papillomavirus (HPV) testing from clinician-collected cervical and self-collected cervico-vaginal samples is more sensitive for detecting CIN2+/CIN3+ than cytology-based screening, stimulating interest in HPV testing from urine. The objective was to determine the performance of the Trovagene HPV test for the detection of CIN2+ from urine and PreservCyt cervical samples.Methods: Women referred for colposcopy at St Mary's Hospital (London, United Kingdom), following abnormal cytology, were recruited to this diagnostic accuracy study by convenience sampling (September 2011 to April 2013). A total of 501 paired urine and cervical samples were collected. Primary outcomes were sensitivity for CIN2+/CIN3+ and specificity for

A novel DNA methylation score accurately predicts death from prostate cancer in men with low to intermediate clinical risk factors.

Clinically aggressive disease behavior is difficult to predict in men with low to intermediate clinical risk prostate cancer and methylation biomarkers may be a valuable adjunct for assessing the management of these patients. We set to evaluate the utility of DNA methylation to identify high risk disease in men currently considered as low or intermediate risk. DNA was extracted from formalin-fixed paraffin-embedded transurethral prostate resection tissues collected during the years 1990-96 in a watchful-waiting cohort of men in the UK. The primary end point was death of prostate cancer, assessed by reviewing cancer registry records from 2009. Methylation was quantified by pyrosequencing assays for six genes (HSPB1, CCND2, TIG1, DPYS, PITX2, and MAL) with established biomarker value in prostate cancer. A novel prognostic methylation score was developed by multivariate Cox modelling using the six methylation biomarkers in 385 men with low-and-intermediate clinical risk variables and its prognostic value compared to two previously defined clinically-derived risk scores. Methylation score was the most significant variable in univariate and bivariate analysis in men with low-to-intermediate CAPRA risk score. When combined with CAPRA score the hazard ratio was 2.02; 95% confidence interval, 1.40-2.92. For a methylation score sensitivity of 83% the specificity was 44%, while the maximum achieved sensitivity by CAPRA was 68% at a specificity of 44%. The derived methylation score is a strong predictor of aggressive prostate cancer that could have an important role in directing the management of patients with low-to-intermediate risk disease. The estimated areas under the curve (AUC) at 10 years of follow-up were 0.62 (95% CI: 0.51, 0.70) and 0.74 (95% CI: 0.65, 0.82) for CAPRA, and combined (CAPRA + methylation) risk score (CRS) respectively.

A comparison of different human papillomavirus tests in PreservCyt versus SurePath in a referral population-PREDICTORS 4.

BACKGROUND: Two transport media, PreservCyt and SurePath, are widely used for cervical cytology screening. There are concerns that they may perform differently for HPV testing. OBJECTIVES: A comparison of the performance of six different HPV tests in SurePath and PreservCyt in a referral population using two samples from each woman. The primary goal was to compare the performance of each test in the two media. Comparisons between assays and viral load comparisons between media were secondary aims. STUDY DESIGN: Two cervical samples were collected in random order at the same visit in women with abnormal cytology. One sample was placed in 20ml of PreservCyt and the other in 10ml of SurePath. Aliquots were taken for 4 DNA based tests: digene HC2 High-Risk HPV DNA Test, Abbott Realtime, BD Onclarity and Genera PapType, an RNA based test-: Hologic Aptima and a protein test: OncoHealth. RESULTS: 630 sample pairs were included in the analyses. For all tests except the protein test sensitivities were in excess of 90% for CIN2+ and 95% for CIN3+ for both media and with no significant differences except for a lower sensitivity for CIN2+ of Aptima in SurePath (93% vs 98%, P=0.005). Specificity for

DNA methylation of PITX2 predicts poor survival in men with prostate cancer.

AIM: We investigated if methylation of candidate genes can be useful for predicting prostate cancer (PCa) specific death. PATIENTS & METHODS: Methylation of PITX2, WNT5a, SPARC, EPB41L3 and TPM4 was investigated in a 1:2 case-control cohort comprising 45 men with cancer of Gleason score ≤ 7 who died (cases), and 90 men who were alive or died of other causes with survival time longer than the cases (controls). A univariate conditional logistic regression model was fitted by maximizing the likelihood of DNA methylation of each gene versus the primary end point. RESULTS: A 10% increase in methylation of PITX2 was associated with PCa related death with OR 1.56 (95% CI: 1.17-2.08; p = 0.005). CONCLUSION: Our study strengthens prior findings that PITX2 methylation is useful as a biomarker of poor outcome of PCa and in addition we also suggest that it may be particularly useful in men with low Gleason score.

DNA methylation gene-based models indicating independent poor outcome in prostate cancer.

BACKGROUND: Prostate cancer has a variable clinical behaviour with frequently unpredictable outcome. DNA methylation plays an important role in determining the biology of cancer but prognostic information is scanty. We assessed the potential of gene-specific DNA methylation changes to predict death from prostate cancer in a cohort of untreated men in the UK. METHODS: This was a population-based study in which cases were identified from six cancer registries in Great Britain. DNA was extracted from formalin-fixed paraffin wax-embedded transurethral prostate resection tissues collected during 1990-96 from men with clinically-localised cancer who chose not to be treated for at least 6 months following diagnosis. The primary end point was death from prostate cancer. Outcomes were determined through medical records and cancer registry records. Pyrosequencing was used to quantify methylation in 13 candidate genes with established or suggested roles in cancer. Univariate and multivariate Cox models were used to identify possible predictors for prostate cancer-related death. RESULTS: Of 367 men, 99 died from prostate cancer during a median of 9.5 years follow-up (max = 20). Univariately, 12 genes were significantly associated with prostate cancer mortality, hazard ratios ranged between 1.09 and 1.28 per decile increase in methylation. Stepwise Cox regression modelling suggested that the methylation of genes HSPB1, CCND2 and DPYS contributed objective prognostic information to Gleason score and PSA with respect to cancer-related death during follow-up (p = 0.006). CONCLUSION: Methylation of 13 genes was analysed in 367 men with localised prostate cancer who were conservatively treated and stratified with respect to death from prostate cancer and those who survived or died of other causes. Of the 13 genes analysed, differential methylation of HSPB1, CCND2 and DPYS provided independent prognostic information. Assessment of gene-methylation may provide independent objective information that can be used to segregate prostate cancers at diagnosis into predicted behavioural groups.

Standardization of Gleason grading among 337 European pathologists.

AIMS: The 2005 International Society of Urological Pathology (ISUP) modification of Gleason grading recommended that the highest grade should always be included in the Gleason score (GS) in prostate biopsies. We analysed the impact of this recommendation on reporting of GS 6 versus 7. METHODS AND RESULTS: Fifteen expert uropathologists reached two-thirds consensus on 15 prostate biopsies with GS 6-7 cancer. Eighty-five microphotographs were graded by 337 of 617 members of the European Network of Uropathology (ENUP), representing 19 countries. There was agreement between expert and majority member GS in 12 of 15 cases, while members upgraded in three cases. Among members and the expert consensus, a GS >6 was assigned by 64.5% and 60%, respectively. Mean member GS was higher than consensus GS in nine of 15 cases. A Gleason pattern (GP) 5 was reported by 0.3-5.6% in 10 cases. Agreement between consensus and member GS was 58.2-89.3% (mean 71.4%) in GS 6 cases and 46.3-63.8% (mean 56.4%) in GS 7 cases (P = 0.009). CONCLUSIONS: While undergrading of prostate cancer used to be prevalent, some now tend to overgrade. Minimum diagnostic criteria for GP 4 and 5 in biopsies need to be better defined. Image libraries reviewed by experts may be useful for standardization.

Quantitative DNA methylation and recurrence of breast cancer: a study of 30 candidate genes.

BACKGROUND: The need for new prognostic factors in breast cancer is ever increasing as breast cancer management evolves. Aberrant DNA methylation plays a pivotal role in cancer development and progression; DNA methylation-based biomarkers may provide independent prognostic information. We used pyrosequencing to investigate the prognostic potential of quantitative DNA methylation of a large set of candidate genes in a Korean single-institution series of operable breast cancer. METHODS: Absolute DNA methylation in 20 candidate genes from an initial set of 30 genes was measured by pyrosequencing of bisulfite converted DNA in 121 fresh frozen breast cancer cases. Survival analyses used continuous and categorized (quintile-based) gene methylation data with time to recurrence (TTR) as an endpoint. Prognostic abilities of gene-only and risk-score models were explored. RESULTS: Median follow-up was 5.1 years; 25 recurrences (21%) were observed. Nodal status, methylation of TWIST1, SLIT2 (both as continuous and categorized variables) and APC, HLA-A, NKX2-5, SERPINB5, SFN (as categorized variables) were significantly prognostic; grade showed a prognostic trend. A multivariate model containing nodal status, grade and TWIST1 was a best fit (p< 0.001) in stepwise regression; risk-score based on this model separated patients into 3 distinct risk-groups (p< 0.001). A gene-only model based on TWIST1 and SFN also classified patients into distinct risk-groups (p=0.009). CONCLUSIONS: This study shows that accurate quantitative measurement of DNA methylation by pyrosequencing identifies a small set of genes with independent prognostic potential in breast cancer. These genes complement the current clinico-pathological prognostic factors and appear to be potential biomarkers that warrant further validation.

Functional viability profiles of breast cancer.

UNLABELLED: The design of targeted therapeutic strategies for cancer has largely been driven by the identification of tumor-specific genetic changes. However, the large number of genetic alterations present in tumor cells means that it is difficult to discriminate between genes that are critical for maintaining the disease state and those that are merely coincidental. Even when critical genes can be identified, directly targeting these is often challenging, meaning that alternative strategies such as exploiting synthetic lethality may be beneficial. To address these issues, we have carried out a functional genetic screen in >30 commonly used models of breast cancer to identify genes critical to the growth of specific breast cancer subtypes. In particular, we describe potential new therapeutic targets for PTEN-mutated cancers and for estrogen receptor-positive breast cancers. We also show that large-scale functional profiling allows the classification of breast cancers into subgroups distinct from established subtypes. SIGNIFICANCE: Despite the wealth of molecular profiling data that describe breast tumors and breast tumor cell models, our understanding of the fundamental genetic dependencies in this disease is relatively poor. Using high-throughput RNA interference screening of a series of pharmacologically tractable genes, we have generated comprehensive functional viability profiles for a wide panel of commonly used breast tumor cell models. Analysis of these profiles identifies a series of novel genetic dependencies, including that of PTEN-null breast tumor cells upon mitotic checkpoint kinases, and provides a framework upon which additional dependencies and candidate therapeutic targets may be identified.

Genomic distance entrained clustering and regression modelling highlights interacting genomic regions contributing to proliferation in breast cancer.

BACKGROUND: Genomic copy number changes and regional alterations in epigenetic states have been linked to grade in breast cancer. However, the relative contribution of specific alterations to the pathology of different breast cancer subtypes remains unclear. The heterogeneity and interplay of genomic and epigenetic variations means that large datasets and statistical data mining methods are required to uncover recurrent patterns that are likely to be important in cancer progression. RESULTS: We employed ridge regression to model the relationship between regional changes in gene expression and proliferation. Regional features were extracted from tumour gene expression data using a novel clustering method, called genomic distance entrained agglomerative (GDEC) clustering. Using gene expression data in this way provides a simple means of integrating the phenotypic effects of both copy number aberrations and alterations in chromatin state. We show that regional metagenes derived from GDEC clustering are representative of recurrent regions of epigenetic regulation or copy number aberrations in breast cancer. Furthermore, detected patterns of genomic alterations are conserved across independent oestrogen receptor positive breast cancer datasets. Sequential competitive metagene selection was used to reveal the relative importance of genomic regions in predicting proliferation rate. The predictive model suggested additive interactions between the most informative regions such as 8p22-12 and 8q13-22. CONCLUSIONS: Data-mining of large-scale microarray gene expression datasets can reveal regional clusters of co-ordinate gene expression, independent of cause. By correlating these clusters with tumour proliferation we have identified a number of genomic regions that act together to promote proliferation in ER+ breast cancer. Identification of such regions should enable prioritisation of genomic regions for combinatorial functional studies to pinpoint the key genes and interactions contributing to tumourigenicity.

The molecular underpinning of lobular histological growth pattern: a genome-wide transcriptomic analysis of invasive lobular carcinomas and grade- and molecular subtype-matched invasive ductal carcinomas of no special type.

Invasive lobular carcinoma (ILC) is the most frequent special type of breast cancer. The majority of these tumours are of low histological grade, express hormone receptors, and lack HER2 expression. The pleomorphic variant of ILCs (PLCs) is characterized by atypical cells with pleomorphic nuclei and is reported to have an aggressive clinical behaviour. Expression profiling studies have demonstrated that classic ILCs preferentially display a luminal phenotype, whereas PLCs may be of luminal, HER2 or molecular apocrine subtypes. The aims of this study were two-fold: to determine the transcriptomic characteristics of lobular carcinomas and to define the genome-wide transcriptomic differences between classic ILCs and PLCs. To define the transcriptomic characteristics of ILCs, minimizing the impact of histological grade and molecular subtype on the analysis, we subjected a series of grade- and molecular subtype-matched ILCs and invasive ductal carcinomas (IDCs) to genome-wide gene expression profiling using oligonucleotide microarrays. Hierarchical clustering analysis demonstrated that ILCs formed a separate cluster and a supervised analysis revealed that 5.8% of the transcriptionally regulated genes were significantly differentially expressed in ILCs compared to grade- and molecular subtype-matched IDCs. ILCs displayed down-regulation of E-cadherin and of genes related to actin cytoskeleton remodelling, protein ubiquitin, DNA repair, cell adhesion, TGF-beta signalling; and up-regulation of transcription factors/immediate early genes, lipid/prostaglandin biosynthesis genes, and cell migration-associated genes. Supervised analysis of classic ILCs and PLCs demonstrated that less than 0.1% of genes were significantly differentially expressed between these tumour subtypes. Our results demonstrate that ILCs differ from grade- and molecular subtype-matched IDCs in the expression of genes related to cell adhesion, cell-to-cell signalling, and actin cytoskeleton signalling. However, classic ILCs and PLCs are remarkably similar at the molecular level and should be considered as part of a spectrum of lesions.