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.

Oncologic and reproductive outcomes after fertility-sparing surgery for bilateral borderline ovarian tumors: A retrospective study.

OBJECTIVES: To investigate the oncological safety and fertility outcomes of different fertility-sparing surgery procedures for bilateral borderline ovarian tumors (BOTs) and to identify the safest and most effective approach to help patients conceive with minimal risk. STUDY DESIGN: A retrospective study of 144 patients (≤40 years) with pathologically confirmed bilateral BOTs were included in the study.The effects of surgery type on fertility outcome and recurrence were compared. Cox regression analysis was employed to determine potential prognostic factors. Survival analysis utilized the Kaplan-Meier method. RESULTS: Three therapeutic modalities were applied in our study, including bilateral ovarian cystectomy (BOC; n = 29), unilateral adnexectomy + contralateral cystectomy (UAC; n = 4) and radical surgery (n = 61). Totally 33 cases (22.9 %) relapsed during the follow-up period. In 37 % of cases administered conservative surgery, relapses were diagnosed in the first 2 years. Only conservative surgery and adjuvant chemotherapy were risk factors for recurrence. Meanwhile, a pregnancy rate of 55.4 % was obtained in patients with bilateral BOTs. The pregnancy rate was slightly higher but no significant (P = 0.539) difference in patients treated with BOC (n = 17, 63 %) compared with UAC (n = 29, 55.8 %) group. GnRHa treatment significantly improved the clinical pregnancy rate in this study(P = 0.029). CONCLUSIONS: Satisfactory pregnancy rate can be achieved after conservative surgery in patients with bilateral BOTs. BOC is worth recommending for bilateral borderline ovarian tumors and a critical factor in fertility is the preservation of maximum healthy ovarian tissue. Patients should make a pregnancy plan in 2 years after the first surgery. GnRHa increase the rate of successful clinical pregnancies.

Serum cell division cycle 42 reflects the treatment response and survival in patients with advanced cervical cancer who receive immune checkpoint inhibitor treatment.

Cell division cycle 42 (CDC42) regulates immune escape, which predicts immune checkpoint inhibitor (ICI) treatment response in several types of cancer. The present study aimed to evaluate the potential of serum CDC42 in predicting the ICI treatment outcome in patients with advanced cervical cancer. A total of 46 patients with advanced cervical cancer who received ICI treatment with or without antiangiogenic agents were enrolled. Serum CDC42 was detected in all patients before treatment (baseline) and following two treatment cycles by enzyme-linked immunosorbent assay. CDC42 at baseline was elevated in patients with target lesion size ≥5 cm (P=0.020), pelvis metastasis (P=0.031) and lung metastasis (P=0.043). Following treatment, the objective response rate (ORR) and disease control rate (DCR) were 30.4 and 78.3%, respectively. Meanwhile, the median progression-free survival (PFS) and overall survival (OS) were 5.8 and 13.1 months. CDC42 at baseline was decreased in patients achieving ORR (P=0.042) but not DCR (P=0.055). PFS (P=0.006) and OS (P=0.019) were decreased in patients with baseline CDC42 ≥600 pg/ml. After two treatment cycles, CDC42 was generally reduced (P<0.001). CDC42 following two treatment cycles was more significantly decreased in patients with ORR (P=0.032) and DCR (P=0.019). Multivariate Cox's regression analysis showed that CDC42 ≥600 pg/ml following two treatment cycles was associated with the shorter PFS (P=0.022, hazard ratio=2.469) and OS (P=0.013, hazard ratio=4.166). Serum CDC42 was reduced after treatment; high expression following treatment reflected a lower possibility of achieving treatment response and poorer survival in patients with advanced cervical cancer.

A novel hypoxia-stimulated lncRNA HIF1A-AS3 binds with YBX1 to promote ovarian cancer tumorigenesis by suppressing p21 and AJAP1 transcription.

Hypoxia is characteristic of the ovarian tumor (OC) microenvironment and profoundly affects tumorigenesis and therapeutic response. Long noncoding RNAs (lncRNAs) play various roles in tumor progression; however, the characteristics of lncRNAs in pathological responses of the OC microenvironment are not entirely understood. Through high-throughput sequencing, lncRNA expression in hypoxia (1% O2 ) and normoxia (21% O2 ) SKOV3 cells was explored and analyzed. The 5'- and 3'-rapid amplification of complementary DNA ends was used to detect the full length of the novel HIF1A-AS3 transcript. Real-time quantitative polymerase chain reaction was used to assess HIF1A-AS3 expression in OC cells and tissues. In vitro and in vivo evaluations of the biological functions of hypoxic HIF1A-AS3 were conducted. To clarify the underlying mechanisms of HIF1A-AS3 in hypoxic OC, a dual-luciferase assay, chromatin immunoprecipitation, RNA pull-down, RNA immunoprecipitation, and RNA-sequencing were used. We used high-throughput sequencing to investigate a novel lncRNA, HIF1A-AS3, as a hypoxic candidate significantly elevated in OC cells/tissues. HIF1A-AS3 was predominantly localized in the nucleus and promoted in vitro and in vivo OC growth and tumorigenesis. Hypoxia-inducible factor 1α bound to hypoxia response elements in the HIF1A-AS3 promoter region and stimulated its expression in hypoxia. Under hypoxia, HIF1A-AS3 directly integrated with Y-Box binding protein 1 and inhibited its ability to bind to the promoters of p21 and AJAP1 to repress their transcriptional activity, thereby promoting hypoxic OC progression. Our results revealed the crucial role and mechanism of the novel hypoxic HIF1A-AS3 in the oncogenesis of OC. The novel HIF1A-AS3 could be a crucial biomarker and therapeutic target for future OC treatments.

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.

Small Nucleolar RNAs and Their Comprehensive Biological Functions in Hepatocellular Carcinoma.

Small nucleolar RNAs (snoRNAs) are a class of highly conserved, stable non-coding RNAs involved in both post-transcriptional modification of RNA and in ribosome biogenesis. Recent research shows that the dysfunction of snoRNAs plays a pivotal role in hepatocellular carcinoma (HCC) and related etiologies, such as hepatitis B virus (HBV), hepatitis C virus (HCV), and non-alcoholic fatty liver disease (NAFLD). Growing evidence suggests that snoRNAs act as oncogenes or tumor suppressors in hepatocellular carcinoma (HCC) through multiple mechanisms. Furthermore, snoRNAs are characterized by their stability in body fluids and their clinical relevance and represent promising tools as diagnostic and prognostic biomarkers. SnoRNAs represent an emerging area of cancer research. In this review, we summarize the classification, biogenesis, activity, and functions of snoRNAs, as well as highlight the mechanism and roles of snoRNAs in HCC and related diseases. Our findings will aid in the understanding of complex processes of tumor occurrence and development, as well as suggest potential diagnostic markers and treatment targets. Furthermore, we discuss several limitations and suggest future research and application directions.

Infiltration Patterns of Cervical Epithelial Microenvironment Cells During Carcinogenesis.

Background: Local cellular microenvironment plays a crucial role in the HPV-induced cervical malignant transformation. Characterization of the dynamic infiltration changes of microenvironment cells during cervical carcinogenesis would contribute to a better understanding of involved mechanisms. Methods: Three public gene expression datasets of cervical squamous epithelium samples were collected and combined. We applied seven up-to-date computational methods for infiltrating estimation and compared their results (CD4+ and CD8+ T cells) to the known fraction. After benchmarking the applied methods, the cell filtration patterns were determined and clustered through fuzzy c-means algorithm. Results: Most methods displayed better performance in predicting the abundance of CD4+ T cell than that of CD8+ T cell. The infiltration patterns of 33 microenvironment cell types (including 31 immune cells and 2 non-immune cells) were determined, and five immune cell clusters with distinct features were then derived. Meanwhile, opposite changes in abundance were observed between the activated and resting state of some immune cells from the progression perspective. Conclusions: Based on characteristics and evaluation performance of different methods, as well as previous findings, for the first time we provide a comprehensive overview of the infiltration patterns of microenvironment cells throughout cervical cancer progression.

The prognostic value and biological significance of gap junction beta protein 2 (GJB2 or Cx26) in cervical cancer.

Objective: To evaluate the prognostic value and explore the biological significance of gap junction protein beta 2 (GJB2 or Cx26) in cervical cancer (CC). Methods: We first compared GJB2 expression between CC and normal tissues using public databases and immunohistochemistry (IHC). Based on The Cancer Genome Atlas data (TCGA cohort, n = 304) and tissue microarray samples (OBC cohort, n = 111), we explored the prognostic value of GJB2 for CC patients using bioinformatics analysis and IHC scoring. To explore the biological significance of GJB2, Gene set enrichment analysis (GSEA) and Gene Ontology (GO) were performed. The impact of GJB2 on the immune microenvironment was analyzed by CIBERSORTx and ESTIMATE algorithms. We finally investigated the relationship between GJB2 and drug sensitivity based on the Genomics of Drug Sensitivity in Cancer (GDSC). Results: The expression of GJB2 was significantly increased in CC over normal tissues. Both the TCGA and OBC cohort found that patients with high GJB2 expression had shorter overall survival (OS) time, and high GJB2 expression was the independent risk factor for prognosis (TCGA: HR, 2.566; 95% CI, 1.066-6.180; p = 0.036; OBC: HR, 2.198; 95% CI, 1.019-4.741; p = 0.045). GJB2 was correlated with patient clinical factors such as tumor size and differentiation grade. The p53 signaling pathway and toll-like receptor pathway may be regulated by GJB2. The abundance of various immune cells was significantly different between the low and high GJB2 expression groups. The ImmuneScore was significantly increased in the high GJB2 expression group. In addition, the expression level of GJB2 was positively correlated with the natural log of the half-maximal inhibitory concentration (LN_IC50) value of cisplatin/paclitaxel (Spearman r = 0.238/0.153, p < 0.001). Conclusion: GJB2 can serve as a potential prognostic marker of poor survival and a therapeutic target in CC. Moreover, GJB2 may affect the immune microenvironment and is correlated with chemoresistance.

Identification of Key Pathways and Establishment of a Seven-Gene Prognostic Signature in Cervical Cancer.

Cervical cancer (CC) remains high morbidity and mortality. We aimed to identify critical pathways underlying cervical carcinogenesis and establish a prognostic signature. Six datasets from the gene expression omnibus (GEO) database were used to screen the differentially expressed genes (DEGs) between CC and normal tissues. We used the unions of the DEGs to perform functional analysis. The 108 overlapped DEGs were analyzed to determine a prognostic signature by Cox regression and Lasso analysis based on The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Immune Cell Abundance Identifier (ImmuCellAI) were used to determine the relationships between the signature and biological functions. The PI3K-Akt signaling pathway, the Ras signaling pathway, and the viral carcinogenesis pathway may be critical for CC development. We identified seven genes (PLOD2, DSG2, SPP1, CXCL8, MCM5, HLTF, and KLF4) to construct a risk score formula. Survival analysis showed that the high-risk group indicated a worse prognosis than the low-risk group (p < 0.0001). The AUC of the prognostic signature was 0.7449, 0.7641, and 0.8146 at 1, 3, and 5 years. We also identified that the signature is an independent prognostic factor. GSEA showed five pathways were relevant to the signature, such as the adherens junction pathway. The signature also affected the abundances of various types of immune cells, such as B cell, CD4+ T cell, and CD8+ T cell. Further, we found that SPP1 was co-expressed with HK3, CD163, CCL3, CLEC5A, MMP8, TREM1, OLR1, and TREM2. The results of Gene Ontology analysis showed that SPP1 and its co-expressed related proteins mainly affected metabolic process, multicellular organismal process, cell communication, cell proliferation, protein binding, and transporter activity. In conclusion, the present study explored the key pathways for CC development and the seven-gene signature can effectively make the prognosis evaluation of CC patients.

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.

GJA1 Expression and Its Prognostic Value in Cervical Cancer.

Gap Junction Protein Alpha 1 (GJA1) belongs to the gap junction family and has been widely studied in cancers. We evaluated the role of GJA1 in cervical cancer (CC) using public data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. The difference of GJA1 expression level between CC and normal tissues was analyzed by the Gene Expression Profiling Interactive Analysis (GEPIA), six GEO datasets, and the Human Protein Atlas (HPA). The relationship between clinicopathological features and GJA1 expression was analyzed by the chi-squared test and the logistic regression. Kaplan-Meier survival analysis and Cox proportional hazard regression analysis were used to assessing the effect of GJA1 expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways regulated by GJA1. Immune Cell Abundance Identifier (ImmuCellAI) was chosen to analyze the immune cells affected by GJA1. The expression of GJA1 in CC was significantly lower than that in normal tissues based on the GEPIA, GEO datasets, and HPA. Both the chi-squared test and the logistic regression showed that high-GJA1 expression was significantly correlated with keratinization, hormone use, tumor size, and FIGO stage. The Kaplan-Meier curves suggested that high-GJA1 expression could indicate poor prognosis (p = 0.0058). Multivariate analysis showed that high-GJA1 expression was an independent predictor of poor overall survival (HR, 4.084; 95% CI, 1.354-12.320; p = 0.013). GSEA showed many cancer-related pathways, such as the p53 signaling pathway and the Wnt signaling pathway, were enriched in the high-GJA1-expression group. Immune cell abundance analysis revealed that the abundance of CD8 naive, DC, and neutrophil was significantly increased in the high-GJA1-expression group. In conclusion, GJA1 can be regarded as a potential prognostic marker of poor survival and therapeutic target in CC. Moreover, many cancer-related pathways may be the critical pathways regulated by GJA1. Furthermore, GJA1 can affect the abundance of immune cells.

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.