Inherited alterations of TGF beta signaling components in Appalachian cervical cancers

Elucidation of Increased Cervical Cancer Risk Due to Polymorphisms in XRCC1 (R399Q and R194W), ERCC5 (D1104H), and NQO1 (P187S)

Genetic variations like single nucleotide polymorphisms (SNPs) are associated with cervical carcinogenesis. In this study, SNPs have been identified that contribute toward changes in the function and stability of the proteins and show association with cervical cancer. Initially, literature mining identified 114 protein-coding polymorphisms with population-based evidence in cervical cancer. Subsequently, the functional assessment was performed using sequence-dependent tools, and thereafter, protein stability was analyzed using sequence and structural data. Twenty-three non-synonymous SNPs (nsSNPs) found to be damaging and destabilizing were then analyzed to check their risk association at the population level. The meta-analysis indicated that polymorphisms in DNA damage repair genes XRCC1 (rs25487 and rs1799782), ERCC5 (rs17655), and oxidative stress-related gene NQO1 (rs1800566) are significantly associated with increased cervical cancer risk. The XRCC1 rs25487 and rs1799782 polymorphisms showed the highest risk of cervical cancer in the homozygous model having odds ratio (OR) = 1.85, 95% confidence interval (CI) = 1.17-2.92, p = 0.01, and recessive model with OR = 1.81, 95% CI = 1.01-3.24, and p = 0.04 respectively. Similarly, rs17655 polymorphism of ERCC5 and rs1800566 polymorphism of NQO1 showed the highest pooled OR in the homozygous (OR = 1.70, 95% CI = 1.32-2.19, p = 0.00004) and heterozygous model (OR = 1.3, 95% CI = 1.06-1.58, p = 0.01) respectively. Thus, in this study, a comprehensive collection of nsSNPs was collated and assessed, leading to the identification of polymorphisms in DNA damage repair and oxidative stress-related genes, that destabilize the protein and shows increased risk associated with cervical cancer.

A novel cervix carcinoma biomarker: Pathological-epigenomics, integrated analysis of MethylMix algorithm and pathology for predicting response to cancer immunotherapy

Herein, A non-invasive pathomics approach was developed to reveal the methylation status in patients with cervical squamous cell carcinoma and predict clinical outcomes and treatment response. Using the MethylMix algorithm, 14 methylation-driven genes were selected for further analysis. We confirmed that methylation-driven genes were differentially expressed in immune, stromal, and tumor cells. In addition, we constructed a methylation-driven model and explored the alterations in immunocyte infiltration between the different models. The methylation-driven subtypes identified in our investigation could effectively predict the clinical outcomes of cervical cancer. To further evaluate the level of methylation-driven patterns, we constructed a risk model with four genes. Significant correlations were observed between the score and immune response markers, including PD1 and CTLA4. Multiple immune infiltration algorithms evaluated the level of immunocyte infiltration between the high- and low-risk groups, while the components of anti-tumor immunocytes in the low-risk group were significantly increased. Subsequently, a total of 205 acquired whole-slide imaging (WSI) images were processed to capture image signatures, and the pathological algorithm was employed to construct an image prediction model based on the risk score classification. The model achieved an area under the curve (AUC) of 0.737 and 0.582 for the training and test datasets, respectively. Moreover, we conducted vitro assays for validation of hub risk gene. The proposed prediction model is a non-invasive method that combines pathomics features and genomic profiles and shows satisfactory performance in predicting patient survival and treatment response. More interdisciplinary fields combining medicine and electronics should be explored in the future.

Species-specific sensitivity to TGFβ signaling and changes to the Mmp13 promoter underlie avian jaw development and evolution

Precise developmental control of jaw length is critical for survival, but underlying molecular mechanisms remain poorly understood. The jaw skeleton arises from neural crest mesenchyme (NCM), and we previously demonstrated that these progenitor cells express more bone-resorbing enzymes including Matrix metalloproteinase 13 (Mmp13) when they generate shorter jaws in quail embryos versus longer jaws in duck. Moreover, if we inhibit bone resorption or Mmp13, we can increase jaw length. In the current study, we uncover mechanisms establishing species-specific levels of Mmp13 and bone resorption. Quail show greater activation of and sensitivity to transforming growth factor beta (TGFβ) signaling than duck; where intracellular mediators like SMADs and targets like Runt-related transcription factor 2 (Runx2), which bind Mmp13, become elevated. Inhibiting TGFβ signaling decreases bone resorption, and overexpressing Mmp13 in NCM shortens the duck lower jaw. To elucidate the basis for this differential regulation, we examine the Mmp13 promoter. We discover a SMAD-binding element and single nucleotide polymorphisms (SNPs) near a RUNX2-binding element that distinguish quail from duck. Altering the SMAD site and switching the SNPs abolish TGFβ sensitivity in the quail Mmp13 promoter but make the duck promoter responsive. Thus, differential regulation of TGFβ signaling and Mmp13 promoter structure underlie avian jaw development and evolution.

A Multi-level Model to Understand Cervical Cancer Disparities in Appalachia

The Appalachian region experiences higher incidence and mortality due to cervical cancer compared with other regions of the United States. The goal of the Ohio State University Center for Population Health and Health Disparities (CPHHD), called the Community Awareness Resources and Education (CARE) project, was to understand reasons for this disparity. The first wave (2003-2008) of funding included three projects focusing on the known risk factors for cervical cancer, lack of screening, smoking, and infection with human papillomavirus (HPV). On the basis of the results of these projects, the second wave (2011-2017) included four projects, designed to address a multi-level model of factors contributing to cervical disparities in Appalachia. The results of these projects were then used to refine a multi-level model that explains cervical cancer disparities in Appalachia. Future funded projects will take these multi-level explanations for cervical disparities and focus on implementation science strategies to reduce the burden of cervical cancer morbidity and mortality in Appalachia.See all articles in this Special Collection Honoring Paul F. Engstrom, MD, Champion of Cancer Prevention.