The accuracy of HPV genotyping in isolation and in combination with CD4 and HIV viral load for the identification of HIV-infected women at risk for developing cervical cancer

Plasmacytoid Dendritic Cells, the Expression of the Stimulator of Interferon Genes Protein (STING) and a Possible Role of Th17 Immune Response in Cervical Lesions Mediated by Human Papillomavirus

Human papillomavirus (HPV) is a virus with a DNA structure that specifically targets squamous epithelial cells. In individuals with a healthy immune system, HPV infection is typically resolved naturally, leading to spontaneous regression. However, when the viral genetic material integrates into the host DNA, it can disrupt the immune response and eventually give rise to neoplastic manifestations. Remarkably, HPV infection appears to activate a protein called Stimulator of Interferon genes (STING), which contributes to the infiltration of Treg Foxp3 + cells. This cellular response acts as a predisposing factor in patients with HPV, potentially exacerbating the progression of the infection. The STING is versatile in different circumstances and can play a role in the immune response as an anti-tumour therapeutic target in HPV-related carcinogenesis. The function of Th17 cells is ambiguous, depending on the microenvironment in the tumour. In this study, 46 biopsies of the uterine cervix of human immunodeficiency virus (HIV) positive patients were divided into three groups: I-cervicitis (10); II-low-grade intraepithelial neoplasia (26); III-moderate or severe intraepithelial neoplasia (10) and it was performed an immunohistochemical technique with the specific antibodies to HPV, CD123, STING and IL17. Immunostained cells were quantified and statistically analysed. Antigens of HPV were detected in the cervical intraepithelial neoplasia (CIN) groups and were absent in cervicitis group. The expression of CD123 was positive in 10.87% of the casuistic, with no statistical difference among groups. STING was present in the three groups. Group 1 presented an area fraction that varied from 3 to 20%, group 2 presented a variation of 3-23% and group 3 presented an area fraction between 4 and 12%. Cells expressing IL17 were present in three groups, more frequent in cervicitis. Considering that the casuistic is composed of women carrying HIV, this infectious agent could influence the numerical similarities of the cells studied among three groups, even in the absence of HPV.

Cervical Cancer Among Women With HIV in South Carolina During the Era of Effective Antiretroviral Therapy

OBJECTIVES

We aimed to determine whether women with HIV (WWH) and cervical cancer were more likely to experience cancer-related death and to be diagnosed with cervical cancer at a younger age and in more advanced stages.

MATERIALS AND METHODS

This is a retrospective cohort study of all women diagnosed with cervical cancer in South Carolina from 1998 to 2018. Deidentified data were obtained from 2 statewide databases. A survival analysis was performed to evaluate differences in cancer survival between women with and without HIV. Wilcoxon rank sum test was used to determine differences in the median age at cancer diagnosis. χ2 test was used to assess differences in cancer stage according to HIV status.

RESULTS

Four thousand three hundred fourteen women were diagnosed with cervical cancer, and 53 (1.2%) had HIV infection. Survival time in months was similar between WWH and HIV-negative women (86 months [interquartile range {IQR} = 32-146] and 62 months [IQR = 18-153], p = .37; log-rank p = .26). Compared with HIV-negative women, WWH were less likely to experience cervical cancer-related death (36% vs. 19%, p = .005). Women with HIV were diagnosed with cervical cancer at a younger age (44 [IQR = 37-54] vs. 49 [IQR = 39-61], p = .02). Cervical cancer stage was similar at diagnosis between groups (tumor node metastasis stage, p = .97, and Surveillance, Epidemiology, and End Results summary stage, p = .41).

CONCLUSIONS

Women with HIV were younger at diagnosis than HIV-negative women, but they were no more likely to die from or have more advanced cervical cancer. Women with HIV were not more likely to develop cervical cancer before the age of 21 years and earlier screening is likely unnecessary.

Predicting the severity of disease progression in COVID-19 at the individual and population level: A mathematical model

The impact of COVID-19 disease on health and economy has been global, and the magnitude of devastation is unparalleled in modern history. Any potential course of action to manage this complex disease requires the systematic and efficient analysis of data that can delineate the underlying pathogenesis. We have developed a mathematical model of disease progression to predict the clinical outcome, utilizing a set of causal factors known to contribute to COVID-19 pathology such as age, comorbidities, and certain viral and immunological parameters. Viral load and selected indicators of a dysfunctional immune response, such as cytokines IL-6 and IFNα, which contribute to the cytokine storm and fever, parameters of inflammation d-dimer and ferritin, aberrations in lymphocyte number, lymphopenia, and neutralizing antibodies were included for the analysis. The model provides a framework to unravel the multi-factorial complexities of the immune response manifested in SARS-CoV-2 infected individuals. Further, this model can be valuable to predict clinical outcome at an individual level, and to develop strategies for allocating appropriate resources to mitigate severe cases at a population level.

Predicting the Severity of Disease Progression in COVID-19 at the Individual and Population Level: A Mathematical Model

The impact of COVID-19 disease on health and economy has been global, and the magnitude of devastation is unparalleled in modern history. Any potential course of action to manage this complex disease requires the systematic and efficient analysis of data that can delineate the underlying pathogenesis. We have developed a mathematical model of disease progression to predict the clinical outcome, utilizing a set of causal factors known to contribute to COVID-19 pathology such as age, comorbidities, and certain viral and immunological parameters. Viral load and selected indicators of a dysfunctional immune response, such as cytokines IL-6 and IFNα which contribute to the cytokine storm and fever, parameters of inflammation D-Dimer and Ferritin, aberrations in lymphocyte number, lymphopenia, and neutralizing antibodies were included for the analysis. The model provides a framework to unravel the multi-factorial complexities of the immune response manifested in SARS-CoV-2 infected individuals. Further, this model can be valuable to predict clinical outcome at an individual level, and to develop strategies for allocating appropriate resources to manage severe cases at a population level.