Differential expression and prognostic value of long nonâ coding RNA in HPVâ negative head and neck squamous cell carcinoma

BackgroundLong nonâ coding RNA (lncRNA) has emerged as a new avenue of interest due to its various biological functions in cancer. Abnormal expression of lncRNA has been reported in other malignancies but has been understudied in head and neck squamous cell carcinoma (HNSCC).MethodsThe lncRNA expression was interrogated via quantitative realâ time polymerase chain reaction (qRTâ PCR) array for 19 human papillomavirus (HPV)â negative HNSCC tumorâ normal pairs. The Cancer Genome Atlas (TCGA) was used to validate these results. The association between differentially expressed lncRNA and survival outcomes was analyzed.ResultsDifferential expression was validated for 5 lncRNA (SPRY4â IT1, HEIH, LUCAT1, LINC00152, and HAND2â AS1). There was also an inverse association between MEG3 expression (not significantly differentially expressed in TCGA tumors but highly variable expression) and 3â year recurrenceâ free survival (RFS).ConclusionWe identified and validated differential expression of 5 lncRNA in HPVâ negative HNSCC. Low MEG3 expression was associated with favorable 3â year RFS, although the significance of this finding remains unclear.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144638/1/hed25136_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144638/2/hed25136.pd

Working in disadvantaged communities: What additional competencies do we need?

Background: Residents of socioeconomically disadvantaged locations are more likely to have poor health than residents of socioeconomically advantaged locations and this has been comprehensively mapped in Australian cities. These inequalities present a challenge for the public health workers based in or responsible for improving the health of people living in disadvantaged localities. The purpose of this study was to develop a generic workforce needs assessment tool and to use it to identify the competencies needed by the public health workforce to work effectively in disadvantaged communities. Methods: A two-step mixed method process was used to identify the workforce needs. In step 1 a generic workforce needs assessment tool was developed and applied in three NSW Area Health Services using focus groups, key stakeholder interviews and a staff survey. In step 2 the findings of this needs assessment process were mapped against the existing National Health Training Package (HLT07) competencies, gaps were identified, additional competencies described and modules of training developed to fill identified gaps. Results: There was a high level of agreement among the AHS staff on the nature of the problems to be addressed but less confidence indentifying the work to be done. Processes for needs assessments, community consultations and adapting mainstream programs to local needs were frequently mentioned as points of intervention. Recruiting and retaining experienced staff to work in these communities and ensuring their safety were major concerns. Workforce skill development needs were seen in two ways: higher order planning/epidemiological skills and more effective working relationships with communities and other sectors. Organisational barriers to effective practice were high levels of annual compulsory training, balancing state and national priorities with local needs and giving equal attention to the population groups that are easy to reach and to those that are difficult to engage. A number of additional competency areas were identified and three training modules developed. Conclusion: The generic workforce needs assessment tool was easy to use and interpret. It appears that the public health workforce involved in this study has a high level of understanding of the relationship between the social determinants and health. However there is a skill gap in identifying and undertaking effective intervention

Association of immunotherapy and immunosuppression with severe COVID-19 disease in patients with cancer

Background: Cytokine storm due to COVID-19 can cause high morbidity and mortality. Patients with cancer treated with immunotherapy (IO) and those with immunosuppression may have higher rates of cytokine storm due to immune dysregulation. We sought to evaluate the association of IO and immunosuppression with COVID-19 outcomes and cytokine storm occurrence among patients with cancer and COVID-19, based on data from the COVID-19 and Cancer Consortium (CCC19). Methods: A registry-based retrospective cohort study was conducted on patients reported to the CCC19 registry from March 2020 to September 2021. The primary outcome was defined as an ordinal scale of COVID-19 severity. The secondary outcome was the occurrence of a cytokine storm using CCC19 variables, defined as biological and clinical evidence of severe inflammation, with end-organ dysfunction (Fajgenbaum D.C. et al., N Engl J Med., 2020). The association of IO or immunosuppression with the outcomes of interest were evaluated using a multivariable logistic regression balanced for covariate distributions through inverse probability of treatment weighting (IPTW). Results: A total of 10,214 patients were included, among which 482 (4.7%) received IO, 3,715 (36.4%) received non-IO systemic therapies, and 6,017 (58.9%) were untreated in the 3 months prior to COVID-19 diagnosis. No difference in COVID-19 severity or the development of a cytokine storm was found in the IO group compared to the untreated group (aOR: 0.77; 95%CI:0.45-1.32, and aOR: 1.06; 95%CI:0.42-2.67, respectively). On multivariable analysis, baseline immunosuppression was associated with worse outcomes both in relation to COVID-19 severity (aOR: 1.89; 95%CI:1.51-2.35) and the presence of a cytokine storm (aOR: 1.75; 95%CI:1.30-2.35). Conclusions: Administration of IO was not associated with severe outcomes in patients with cancer and COVID-19, whereas pre-existing baseline immunosuppression appears to be independently associated with worse clinical outcomes including cytokine storm

A prognostic model of all-cause mortality at 30 days in patients with cancer and COVID-19

Background: Patients with cancer are at higher risk of dying of COVID-19. Known risk factors for 30-day all-cause mortality (ACM-30) in patients with cancer are older age, sex, smoking status, performance status, obesity, and co-morbidities. We hypothesized that common clinical and laboratory parameters would be predictive of a higher risk of 30-day ACM, and that a machine learning approach (random forest) could produce high accuracy. Methods: In this multi-institutional COVID-19 and Cancer Consortium (CCC19) registry study, 12,661 patients enrolled between March 17, 2020 and December 31, 2021 were utilized to develop and validate a model of ACM-30. ACM-30 was defined as death from any cause within 30 days of COVID-19 diagnosis. Pre-specified variables were: age, sex, race, smoking status, ECOG performance status (PS), timing of cancer treatment relative to COVID19 diagnosis, severity of COVID19, type of cancer, and other laboratory measurements. Missing variables were imputed using random forest proximity. Random forest was utilized to model ACM-30. The area under the curve (AUC) was computed as a measure of predictive accuracy with out-of-bag prediction. One hundred bootstrapped samples were used to obtain the standard error of the AUC. Results: The median age at COVID-19 diagnosis was 65 years, 53% were female, 18% were Hispanic, and 16.7% were Black. Over half were never smokers and the median body mass index was 28.2. Random forest with under sampling selected 20 factors prognostic of ACM-30. The AUC was 88.9 (95% CI 88.5-89.2). Highly informative parameters included: COVID-19 severity at presentation, cancer status, age, troponin level, ECOG PS and body mass index. Conclusions: This prognostic model based on readily available clinical and laboratory values can be used to estimate individual survival probability within 30-days for COVID-19. In addition, this model can be used to select or classify patients with cancer and COVID-19 into risk groups based on validated cut points, for treatment selection, prophylaxis prioritization, and/or enrollment in clinical trials. Future work includes external validation using other large datasets of patients with COVID-19 and cancer

Properties of B-Mesons in Lattice QCD

The results of an extensive study of B-meson properties in quenched lattice QCD are presented. The studies are carried out in the static quark limit where the b-quark is taken to be infinitely massive. Our computations rely on a multistate smearing method introduced previously, with smearing functions generated from a relativistic lattice quark model. Systematic errors arising from excited state contamination, finite volume effects, and the chiral extrapolation for the light quarks are estimated. We obtain continuum results for the mass splitting M_{B_s}- M_{B_u} = 86 (+/-)12(stat) {+7/-9}(syst) MeV, the ratio of decay constants f_{B_s}/f_{B_u} = 1.22 (+/-)0.04(stat) (+/-)0.02 (syst). For the B-meson decay constant we separately exhibit the sizable uncertainties in the extrapolation to the continuum limit a -> 0 and higher order perturbative matching. We obtain f_{B} = 188 (+/-)23(stat) (+/-)15(syst) {+26/-0}(extrap) (+/-)14 (pert) MeV. ----- [Postscript version of paper available by anonymous ftp at fncrd6.fnal.gov. The file is fb.ps in subdirectory theory.]Comment: 75 pages, FERMILAB-PUB-94/164-

Human Papillomavirus (HPV) 16 E6 Variants in Tonsillar Cancer in Comparison to Those in Cervical Cancer in Stockholm, Sweden

Background: Human papillomavirus (HPV), especially HPV16, is associated with the development of both cervical and tonsillar cancer and intratype variants in the amino acid sequence of the HPV16 E6 oncoprotein have been demonstrated to be associated with viral persistence and cancer lesions. For this reason the presence of HPV16 E6 variants in tonsillar squamous cell carcinoma (TSCC) in cervical cancer (CC), as well as in cervical samples (CS), were explored. Methods: HPV16 E6 was sequenced in 108 TSCC and 52 CC samples from patients diagnosed 2000–2008 in the County of Stockholm, and in 51 CS from young women attending a youth health center in Stockholm. Results: The rare E6 variant R10G was relatively frequent (19%) in TSCC, absent in CC and infrequent (4%) in CS, while the well-known L83V variant was common in TSCC (40%), CC (31%), and CS (29%). The difference for R10G was significant between TSCC and CC (p = 0.0003), as well as between TSCC and CS (p = 0.009). The HPV16 European phylogenetic lineage and its derivatives dominated in all samples (.90%). Conclusion: The relatively high frequency of the R10G variant in TSCC, as compared to what has been found in CC both in the present study as well as in several other studies in different countries, may indicate a difference between TSCC and CC with regard to tumor induction and development. Alternatively, there could be differences with regard to the oral an

Systemic Anticancer Therapy and Thromboembolic Outcomes in Hospitalized Patients With Cancer and COVID-19

IMPORTANCE: Systematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking. OBJECTIVE: To assess the association between anticancer therapy exposure within 3 months prior to COVID-19 and TEEs following COVID-19 diagnosis in patients with cancer. DESIGN, SETTING, AND PARTICIPANTS: This registry-based retrospective cohort study included patients who were hospitalized and had active cancer and laboratory-confirmed SARS-CoV-2 infection. Data were accrued from March 2020 to December 2021 and analyzed from December 2021 to October 2022. EXPOSURE: Treatments of interest (TOIs) (endocrine therapy, vascular endothelial growth factor inhibitors/tyrosine kinase inhibitors [VEGFis/TKIs], immunomodulators [IMiDs], immune checkpoint inhibitors [ICIs], chemotherapy) vs reference (no systemic therapy) in 3 months prior to COVID-19. MAIN OUTCOMES AND MEASURES: Main outcomes were (1) venous thromboembolism (VTE) and (2) arterial thromboembolism (ATE). Secondary outcome was severity of COVID-19 (rates of intensive care unit admission, mechanical ventilation, 30-day all-cause mortality following TEEs in TOI vs reference group) at 30-day follow-up. RESULTS: Of 4988 hospitalized patients with cancer (median [IQR] age, 69 [59-78] years; 2608 [52%] male), 1869 had received 1 or more TOIs. Incidence of VTE was higher in all TOI groups: endocrine therapy, 7%; VEGFis/TKIs, 10%; IMiDs, 8%; ICIs, 12%; and chemotherapy, 10%, compared with patients not receiving systemic therapies (6%). In multivariable log-binomial regression analyses, relative risk of VTE (adjusted risk ratio [aRR], 1.33; 95% CI, 1.04-1.69) but not ATE (aRR, 0.81; 95% CI, 0.56-1.16) was significantly higher in those exposed to all TOIs pooled together vs those with no exposure. Among individual drugs, ICIs were significantly associated with VTE (aRR, 1.45; 95% CI, 1.01-2.07). Also noted were significant associations between VTE and active and progressing cancer (aRR, 1.43; 95% CI, 1.01-2.03), history of VTE (aRR, 3.10; 95% CI, 2.38-4.04), and high-risk site of cancer (aRR, 1.42; 95% CI, 1.14-1.75). Black patients had a higher risk of TEEs (aRR, 1.24; 95% CI, 1.03-1.50) than White patients. Patients with TEEs had high intensive care unit admission (46%) and mechanical ventilation (31%) rates. Relative risk of death in patients with TEEs was higher in those exposed to TOIs vs not (aRR, 1.12; 95% CI, 0.91-1.38) and was significantly associated with poor performance status (aRR, 1.77; 95% CI, 1.30-2.40) and active/progressing cancer (aRR, 1.55; 95% CI, 1.13-2.13). CONCLUSIONS AND RELEVANCE: In this cohort study, relative risk of developing VTE was high among patients receiving TOIs and varied by the type of therapy, underlying risk factors, and demographics, such as race and ethnicity. These findings highlight the need for close monitoring and perhaps personalized thromboprophylaxis to prevent morbidity and mortality associated with COVID-19-related thromboembolism in patients with cancer