A multi-variable predictive warning model for cervical cancer using clinical and SNPs data.

Introduction: Cervical cancer is the fourth most common cancer among female worldwide. Early detection and intervention are essential. This study aims to construct an early predictive warning model for cervical cancer and precancerous lesions utilizing clinical data and simple nucleotide polymorphisms (SNPs). Methods: Clinical data and germline SNPs were collected from 472 participants. Univariate logistic regression, least absolute shrinkage selection operator (LASSO), and stepwise regression were performed to screen variables. Logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), extreme gradient boosting(XGBoost) and neural network(NN) were applied to establish models. The receiver operating characteristic (ROC) curve was used to compare the models' efficiencies. The performance of models was validated using decision curve analysis (DCA). Results: The LR model, which included 6 SNPs and 2 clinical variables as independent risk factors for cervical carcinogenesis, was ultimately chosen as the most optimal model. The DCA showed that the LR model had a good clinical application. Discussion: The predictive model effectively foresees cervical cancer risk using clinical and SNP data, aiding in planning timely interventions. It provides a transparent tool for refining clinical decisions in cervical cancer management.

Sequential gene expression analysis of cervical malignant transformation identifies RFC4 as a novel diagnostic and prognostic biomarker.

BACKGROUND: Cervical squamous cell carcinoma (SCC) is known to arise through increasingly higher-grade squamous intraepithelial lesions (SILs) or cervical intraepithelial neoplasias (CINs). This study aimed to describe sequential molecular changes and identify biomarkers in cervical malignant transformation. METHODS: Multidimensional data from five publicly available microarray and TCGA-CESC datasets were analyzed. Immunohistochemistry was carried out on 354 cervical tissues (42 normal, 62 CIN1, 26 CIN2, 47 CIN3, and 177 SCC) to determine the potential diagnostic and prognostic value of identified biomarkers. RESULTS: We demonstrated that normal epithelium and SILs presented higher molecular homogeneity than SCC. Genes in the region (e.g., 3q, 12q13) with copy number alteration or HPV integration were more likely to lose or gain expression. The IL-17 signaling pathway was enriched throughout disease progression with downregulation of IL17C and decreased Th17 cells at late stage. Furthermore, we identified AURKA, TOP2A, RFC4, and CEP55 as potential causative genes gradually upregulated during the normal-SILs-SCC transition. For detecting high-grade SIL (HSIL), TOP2A and RFC4 showed balanced sensitivity (both 88.2%) and specificity (87.1 and 90.1%), with high AUC (0.88 and 0.89). They had equivalent diagnostic performance alone to the combination of p16INK4a and Ki-67. Meanwhile, increased expression of RFC4 significantly and independently predicted favorable outcomes in multi-institutional cohorts of SCC patients. CONCLUSIONS: Our comprehensive study of gene expression profiling has identified dysregulated genes and biological processes during cervical carcinogenesis. RFC4 is proposed as a novel surrogate biomarker for determining HSIL and HSIL+, and an independent prognostic biomarker for SCC.

Human papillomavirus integration perspective in small cell cervical carcinoma.

Small cell cervical carcinoma (SCCC) is a rare but aggressive malignancy. Here, we report human papillomavirus features and genomic landscape in SCCC via high-throughput HPV captured sequencing, whole-genome sequencing, whole-transcriptome sequencing, and OncoScan microarrays. HPV18 infections and integrations are commonly detected. Besides MYC family genes (37.9%), we identify SOX (8.4%), NR4A (6.3%), ANKRD (7.4%), and CEA (3.2%) family genes as HPV-integrated hotspots. We construct the genomic local haplotype around HPV-integrated sites, and find tandem duplications and amplified HPV long control regions (LCR). We propose three prominent HPV integration patterns: duplicating oncogenes (MYCN, MYC, and NR4A2), forming fusions (FGFR3-TACC3 and ANKRD12-NDUFV2), and activating genes (MYC) via the cis-regulations of viral LCRs. Moreover, focal CNA amplification peaks harbor canonical cancer genes including the HPV-integrated hotspots within MYC family, SOX2, and others. Our findings may provide potential molecular criteria for the accurate diagnosis and efficacious therapies for this lethal disease.

6 Circulating miRNAs can be used as Non-invasive Biomarkers for the Detection of Cervical Lesions.

Background: Cervical cancer is the most common malignant tumor in the female reproductive system, while the efficacy of routine screening strategy is unsatisfied. New molecular tests need to be developed. miRNAs participate in many pathologic processes, and circulating miRNAs are promising non-invasive biomarkers in tumors. Objectives: This study aimed to identify the circulating miRNAs associated with both cervical cancer and cervical intraepithelial neoplasia (CIN), and establish a non-invasive classifier for cervical lesions using circulating miRNAs. Methods: This study consisted of 5 steps: miRNAs screening, miRNAs validation, classifier establishment, independent validation and in silico analyses. Three cohorts were included in our study: In screening stage, 24 samples including 14 cases and 10 controls were retrieved; In validation stage, 380 samples including 200 cases and 180 controls were recruited; In independent validation stage, 47 samples comprising 26 cases and 21 controls were included. miRNAs were quantified by RT-qPCR. A classifier was built with random forest algorithm using validation samples and selected miRNAs, which were then validated in an independent cohort. To explore the function of selected miRNAs, in silico analyses were performed. Target genes of selected miRNAs were predicted by the overlap of three online tools. Enrichment analyses were executed with predicted target genes. Differential analysis of target genes was carried out with open access expression assay datasets of cervical tissues. Results: 6 miRNAs (hsa-miR-26b-5p, hsa-miR-146b-5p, hsa-miR-191-5p, hsa-miR-484, hsa-miR-574-3p, hsa-miR-625-3p) were screened out from 754 miRNAs. They were associated with cervical lesions and were selected to establish a classifier. The accuracy of the classifier were 0.7218 (0.7117, 0.7319) in validation samples, which was 0.7021 in the independent cohort. 958 target genes were predicted and enriched in 23 pathways (MAPK, human papillomavirus infection and Wnt signaling pathway, etc.). 55 genes were identified as the most likely target genes by differential analysis. Conclusion: The 6 circulating miRNAs were related to cervical lesions and could serve as non-invasive biomarkers.

A case of SLE with COVID-19 and multiple infections.

The coronavirus disease 2019 (COVID-19) has become a global pandemic, which is induced by infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Patients with systemic lupus erythematosus (SLE) are susceptible to infections due to the chronic use of immunosuppressive drugs and the autoimmune disorders. Now we report a case of SLE infected with SARS-CoV-2, influenza A virus and Mycoplasma pneumoniae concurrently. The patient used hydroxychloroquine and prednisone chronically to control the SLE. After infection of SARS-CoV-2, she was given higher dose of prednisone than before and the same dosage of hydroxychloroquine. Besides, some empirical treatments such as antiviral, antibiotic and immunity regulating therapies were also given. The patient finally recovered from COVID-19. This case indicated that hydroxychloroquine may not be able to fully protect SLE patient form SARS-CoV-2. Intravenous immunoglobulin therapies and increased dose of corticosteroids might be adoptable for patient with both COVID-19 and SLE. Physicians should consider SARS-CoV-2 virus test when SLE patient presented with suspected infection or SLE flare under the epidemic of COVID-19.

Comparison of clinical and microbiological diagnoses for older adults with COVID-19 in Wuhan: a retrospective study.

BACKGROUND: The potential differences between a clinical diagnosis of coronavirus disease 2019 (COVID-19) (i.e., symptoms without positive virus test) and a microbiological diagnosis (i.e., positive virus test results) of COVID-19 are not known. AIMS: This study explored the differences between the two types of COVID-19 diagnosis among older patients in terms of clinical characteristics and outcomes. METHODS: A total of 244 inpatients aged ≥ 60 years with COVID-19 were included in this study, of whom 52 were clinically diagnosed and 192 were microbiologically diagnosed. Clinical and laboratory data on hospital admission and outcomes (discharged or died in hospital) of all patients were retrieved from medical records retrospectively. Patients who met the criteria for clinical diagnosis with negative virus test results were assigned to the clinical diagnosis group, whereas those with positive virus test results were assigned to the microbiological diagnosis group. After univariate analyses, two propensity score analyses [i.e., covariate adjustment using propensity score (CAPS) and propensity score matching (PSM)] were conducted to control bias. RESULTS: The clinical and microbiological diagnosis groups demonstrated significant differences in outcomes and in the majority of laboratory findings. After propensity score analyses, many differences between the two groups disappeared and the rate of mortality had no statistically significant difference (P = 0.318 and 0.828 for CAPS and PSM, respectively). CONCLUSIONS: Patients with similar signs, symptoms, and laboratory and imaging findings as confirmed COVID-19 cases may have a similar mortality risk, regardless of the virus test results, and require timely intervention to reduce their mortality.

Risk Factors for Mortality in 244 Older Adults With COVID-19 in Wuhan, China: A Retrospective Study.

BACKGROUND/OBJECTIVES: Previous studies have reported that older patients may experience worse outcome(s) after infection with severe acute respiratory syndrome coronavirus-2 than younger individuals. This study aimed to identify potential risk factors for mortality in older patients with coronavirus disease 2019 (COVID-19) on admission, which may help identify those with poor prognosis at an early stage. DESIGN: Retrospective case-control. SETTING: Fever ward of Sino-French New City Branch of Tongji Hospital, Wuhan, China. PARTICIPANTS: Patients aged 60 years or older with COVID-19 (n = 244) were included, of whom 123 were discharged and 121 died in hospital. MEASUREMENTS: Data retrieved from electronic medical records regarding symptoms, signs, and laboratory findings on admission, and final outcomes of all older patients with COVID-19, were retrospectively reviewed. Univariate and multivariate logistic regression analyses were used to explore risk factors for death. RESULTS: Univariate analysis revealed that several clinical characteristics and laboratory variables were significantly different (ie, P < .05) between discharged and deceased patients. Multivariable logistic regression analysis revealed that lymphocyte (LYM) count (odds ratio [OR] = 0.009; 95% confidence interval [CI] = 0.001-0.138; P = .001) and older age (OR = 1.122; 95% CI = 1.007-1.249; P = .037) were independently associated with hospital mortality. White blood cell count was also an important risk factor (P = .052). The area under the receiver operating characteristic curve in the logistic regression model was 0.913. Risk factors for in-hospital death were similar between older men and women. CONCLUSION: Older age and lower LYM count on admission were associated with death in hospitalized COVID-19 patients. Stringent monitoring and early intervention are needed to reduce mortality in these patients. J Am Geriatr Soc 68:E19-E23, 2020.

Adjuvant chemotherapy after surgery can improve clinical outcomes for patients with IB2-IIB cervical cancer with neoadjuvant chemotherapy followed by radical surgery.

The aim of the study is to evaluate the efficacy of postoperative treatments based on pathological response for cervical cancer patients who received neoadjuvant chemotherapy (NACT) followed by radical surgery. Firstly, a total of 756 cervical squamous cell cancer (SCC) patients with FIGO IB2-IIB were included in this retrospective study. Then data from a prospective cohort of 393 patients was employed for further validation. Overall survival (OS) and disease-free survival (DFS) were assessed. In the retrospective study, SCC patients who accepted adjuvant chemotherapy after radical surgery had a relatively better OS than those who received no therapy (P = 0.08, HR = 0.57). The result was more noticeable in the prospective cohort study (P = 0.006, HR = 0.28). In the combined analysis, adjuvant chemotherapy improved clinical outcomes compared with no therapy (P = 0.002 and 0.04 for OS and DFS). Particularly for patients with extra-cervical residual disease, adjuvant chemotherapy improved OS (log-rank P = 0.008, 0.004 and 0.001 in the retrospective, prospective and combined studies). Optimal response patients had good outcomes even without therapy. Our study indicates that adjuvant chemotherapy can benefit clinical outcomes for SCC patients with NACT followed by radical surgery, especially those with extra-cervical residual disease. For optimal response patients, there may be no need for further treatment. This finding needs to be validated in more future studies.