Comprehensive genomic variation profiling of cervical intraepithelial neoplasia and cervical cancer identifies potential targets for cervical cancer early warning

Genomic profiles and their relationships with clinical characteristics and immune features in cervical cancer

OBJECTIVE

This study aimed to investigate the genomic alteration profiles of cervical cancer patients, examine the correlation between mutation patterns and clinical and immune attributes, and discover novel targets for treatment of individuals with cervical cancer.

METHODS

We performed targeted next-generation sequencing of tumor tissues and blood samples obtained from 45 cervical cancer patients to analyze somatic alterations, mutation patterns, and HLA alleles comprehensively. Additionally, we used flow cytometry to assess expression levels of immune checkpoint genes.

RESULTS

Notably, genes such as AR (78%), KMT2D (76%), and NOTCH1 (62%) exhibited higher mutation frequencies. Moreover, the tumor mutation burden (TMB) was significantly greater in HPV-positive cervical cancer patients than in HPV-negative patients (P=0.029). BMI (P=0.047) and mutations in BARD1 (P=0.034), CEP290 (P=4E-04), and SLX4 (P=0.0128) were identified as predictors of shorter overall survival in cervical cancer patients. Furthermore, the present study revealed significant upregulation of PD-1 (P=0.027) and Tim-3 (P=0.048) in the high mutant-allele tumor heterogeneity (MATH) cohort. In the elderly cervical cancer patient population, HLA-A03:01 emerged as a high-risk allele (OR=3.2, P<0.0001); HLA-C07:02 (OR=0.073, P=0.02) and HLA-B*07:02 (OR=0.257, P=0.037) were associated with a reduced risk among patients with low TMB.

CONCLUSIONS

This study offers insights into the mutation characteristics of cervical cancer patients and identifies potential therapeutic.

Long-read sequencing reveals the structural complexity of genomic integration of HPV DNA in cervical cancer cell lines

BACKGROUND

Cervical cancer (CC) causes more than 311,000 deaths annually worldwide. The integration of human papillomavirus (HPV) is a crucial genetic event that contributes to cervical carcinogenesis. Despite HPV DNA integration is known to disrupt the genomic architecture of both the host and viral genomes in CC, the complexity of this process remains largely unexplored.

RESULTS

In this study, we conducted whole-genome sequencing (WGS) at 55-65X coverage utilizing the PacBio long-read sequencing platform in SiHa and HeLa cells, followed by comprehensive analyses of the sequence data to elucidate the complexity of HPV integration. Firstly, our results demonstrated that PacBio long-read sequencing effectively identifies HPV integration breakpoints with comparable accuracy to targeted-capture Next-generation sequencing (NGS) methods. Secondly, we constructed detailed models of complex integrated genome structures that included both the HPV genome and nearby regions of the human genome by utilizing PacBio long-read WGS. Thirdly, our sequencing results revealed the occurrence of a wide variety of genome-wide structural variations (SVs) in SiHa and HeLa cells. Additionally, our analysis further revealed a potential correlation between changes in gene expression levels and SVs on chromosome 13 in the genome of SiHa cells.

CONCLUSIONS

Using PacBio long-read sequencing, we have successfully constructed complex models illustrating HPV integrated genome structures in SiHa and HeLa cells. This accomplishment serves as a compelling demonstration of the valuable capabilities of long-read sequencing in detecting and characterizing HPV genomic integration structures within human cells. Furthermore, these findings offer critical insights into the complex process of HPV16 and HPV18 integration and their potential contribution to the development of cervical cancer.

Testing for viral DNA integration among HPV-positive women to detect cervical precancer: An observational cohort study

OBJECTIVE

Human papillomavirus (HPV) integration is a crucial genetic step in cervical carcinogenesis. This study aimed to evaluate the performance of an HPV integration test for the triage of HPV-positive women.

DESIGN

An observational cohort study.

SETTING

A cervical cancer screening programme in China.

POPULATION

1393 HPV-positive women aged 25-65 years undergoing routine cervical cancer screening and HPV integration testing with 1-year follow-up.

METHODS

The sensitivity, specificity, positive predictive value and negative predictive value between HPV integration and cytology were compared.

MAIN OUTCOME MEASURES

Cervical intraepithelial neoplasia grade 3 or more severe (CIN3+).

RESULTS

Among 1393 HPV-positive patients, 138 (9.9% [8.3-11.5%]) were HPV integration test positive compared with 537 who had abnormal cervical cytology (38.5% [36.0-41.1%]). Compared with cytology, HPV integration exhibited higher specificity (94.5% [93.3-95.8%] versus 63.8% [61.2-66.4%]) and equivalent sensitivity (70.5% [61.4-79.7%] versus 70.5% [61.4-79.7%]) for detection of CIN3+. HPV integration-negative women accounted for 90.1% (1255/1393) of the total population and had a low immediate CIN3+ risk (2.2%). At 1-year follow-up, the progression rate in the HPV integration-positive women was higher than in the HPV integration-negative women (12.0% versus 2.1%, odds ratio 5.6, 95% CI, 2.6-11.9). In 10 conservatively managed integration-negative CIN2 patients, all showed spontaneous regression and seven showed HPV clearance after 1-year follow-up.

CONCLUSION

The HPV integration test may be a precise risk stratification tool for HPV-positive women and could avoid excessive use of invasive biopsies.

Artificial intelligence and database for NGS-based diagnosis in rare disease

Rare diseases (RDs) are rare complex genetic diseases affecting a conservative estimate of 300 million people worldwide. Recent Next-Generation Sequencing (NGS) studies are unraveling the underlying genetic heterogeneity of this group of diseases. NGS-based methods used in RDs studies have improved the diagnosis and management of RDs. Concomitantly, a suite of bioinformatics tools has been developed to sort through big data generated by NGS to understand RDs better. However, there are concerns regarding the lack of consistency among different methods, primarily linked to factors such as the lack of uniformity in input and output formats, the absence of a standardized measure for predictive accuracy, and the regularity of updates to the annotation database. Today, artificial intelligence (AI), particularly deep learning, is widely used in a variety of biological contexts, changing the healthcare system. AI has demonstrated promising capabilities in boosting variant calling precision, refining variant prediction, and enhancing the user-friendliness of electronic health record (EHR) systems in NGS-based diagnostics. This paper reviews the state of the art of AI in NGS-based genetics, and its future directions and challenges. It also compare several rare disease databases.

Whole genome sequencing in high-grade cervical intraepithelial neoplasia patients from different ethnic groups in China

Cervical cancer (CC) is the fourth most common cancer in women worldwide. It develops through precancerous lesions (cervical intraepithelial neoplasia (CIN), graded from low-grade (CIN1) to high-grade (CIN2-3)). It is well established that precancerous and cancerous cervical lesions are caused by a persistent infection with high-risk types of the human papilloma virus (hrHPV). To have a deeper understanding of the pathogenesis of CIN and CC, we systematically analyzed the landscape of genomic alterations and HPV integration profiles in high-grade CIN2/3. We performed deep whole genome sequencing on exfoliated cervical cells and matched peripheral blood samples from a cohort of 51 Chinese patients (of whom 35 were HPV+) with high-grade CIN from 3 ethnic groups and constructed strict integrated workflow of genomic analysis. In addition, the HPV types and integration breakpoints in the exfoliated cervical cells from these patients were examined. Genomic analysis identified 6 significantly mutated genes (SMGs), including CDKN2A, PIK3CB, FAM20A, RABEP1, TMPRSS2 and SS18L1, in 51 CIN2/3 samples. As none of them had previously been identified as SMGs in the Cancer Genome Atlas cervical squamous cell carcinoma and endocervical adenocarcinoma (TCGA-CESC) cohort, future studies with larger sample size of CINs may be needed to validate our findings. Mutational signature analysis showed that mutational signatures of CINs were dramatically different from CCs, highlighting their different mutational processes and etiologies. Moreover, non-silent somatic mutations were detected in all of the CIN2/3 samples, and 88% of these mutations occurred in genes that also mutated in CCs of TCGA cohort. CIN2 samples had significantly less non-silent mutations than CIN3 samples (P = .0006). Gene ontology and pathway level analysis revealed that functions of mutated genes were significantly associated with tumorigenesis, thus these genes may be involved in the development and progression of CC. HPV integration breakpoints occurred in 28.6% of the CIN2/3 samples with HPV infection. Integrations of common high risk HPV types in CCs, including HPV16, 52, 58 and 68, also occurred in the CIN samples. Our results lay the groundwork for a deeper understanding of the molecular mechanisms underlying the pathogenesis of CC and pave the way for new tools for screening, diagnosis and treatment of cervical precancerous and cancerous lesions.

Landscape of somatic mutated genes and inherited susceptibility genes in gynecological cancer

Traditionally, gynecological cancers have been classified based on histology. Since remarkable advancements in next-generation sequencing technology have enabled the exploration of somatic mutations in various cancer types, comprehensive sequencing efforts have revealed the genomic landscapes of some common forms of human cancer. The genomic features of various gynecological malignancies have been reported by several studies of large-scale genomic cohorts, including The Cancer Genome Atlas. Although recent comprehensive genomic profiling tests, which can detect hundreds of genetic mutations at a time from cancer tissues or blood samples, have been increasingly used as diagnostic clinical biomarkers and in therapeutic management decisions, germline pathogenic variants associated with hereditary cancers can also be detected using this test. Gynecological cancers are closely related to genetic factors, with approximately 5% of endometrial cancer cases and 20% of ovarian cancer cases being caused by germline pathogenic variants. Hereditary breast and ovarian cancer syndrome and Lynch syndrome are the two major cancer susceptibility syndromes among gynecological cancers. In addition, several other hereditary syndromes have been reported to be associated with gynecological cancers. In this review, we highlight the genes for somatic mutation and germline pathogenic variants commonly seen in gynecological cancers. We first describe the relationship between clinicopathological attributes and somatic mutated genes. Subsequently, we discuss the characteristics and clinical management of inherited cancer syndromes resulting from pathogenic germline variants in gynecological malignancies.

Network modeling suggests HIV infection phenocopies PI3K-AKT pathway mutations to enhance HPV-associated cervical cancer

Women coinfected with human immunodeficiency virus type 1 (HIV-1) and human papillomavirus (HPV) are six times as likely to develop invasive cervical carcinoma compared to those without HIV. Unlike other HIV-associated cancers, the risk of cervical cancer development does not change when HPV/HIV coinfected women begin antiretroviral therapy, suggesting HIV-associated immune suppression is not a key driver of cervical cancer development in coinfected women. Here, we investigated whether the persistent secretion of inflammatory factors in HIV-positive patients on antiretroviral therapy could enhance cancer signaling in HPV-infected cervical cells via endocrine mechanisms. We integrated previously reported HIV-induced secreted inflammatory factors (Hi-SIFs), HIV and HPV virus-human protein interactions, and cervical cancer patient genomic data using network propagation to understand the pathways underlying disease development in HPV/HIV coinfection. Our results pinpointed the PI3K-AKT signaling pathway to be enriched at the interface between Hi-SIFs and HPV-host molecular networks, in alignment with PI3K pathway mutations being prominent drivers of HPV-associated, but HIV independent, cervical cancer development. Furthermore, we experimentally stimulated cervical cells with 14 Hi-SIFs to assess their ability to activate PI3K-AKT signaling. Strikingly, we found 8 factors (CD14, CXCL11, CXCL9, CXCL13, CXCL17, AHSG, CCL18, and MMP-1) to significantly upregulate AKT phosphorylation (pAKT-S473) relative to a phosphate buffered saline control. Our findings suggest that Hi-SIFs cooperate with HPV infection in cervical cells to over-activate PI3K-AKT signaling, effectively phenocopying PI3K-AKT pathway mutations, resulting in enhanced cervical cancer development in coinfected women. Our insights could support the design of therapeutic interventions targeting the PI3K-AKT pathway or neutralizing Hi-SIFs in HPV/HIV coinfected cervical cancer patients.

Advances in Mapping Tumor Progression from Precancer Atlases

Tissue profiling technologies present opportunities for understanding transition from precancerous lesions to malignancy, which may impact risk stratification, prevention, and even cancer treatment. A human precancer atlas building effort is ongoing to tackle the significant challenge of decoding the heterogeneity among cells, specimens, and patients. Here, we discuss the findings resulting from atlases built across precancer types, including those found in colon, breast, lung, stomach, cervix, and skin, using bulk, single-cell, and spatial profiling strategies. We highlight two main themes that emerge across precancer types: the ordering of molecular events that occur during tumor progression and the fluctuation of microenvironmental response during precancer progression. We further highlight the key challenges of data integration across large cohorts of patients, and the need for computational tools to reliably annotate and quality control high-volume, high-dimensional data.

Analysis of somatic mutations and key driving factors of cervical cancer progression

We investigated the somatic mutations and key driving factors of cervical cancer by whole exome sequencing . We found 22,183 somatic single nucleotide variations (SNVs) in 52 paired samples. Somatic SNVs in cervical cancer were significantly higher than those in high-grade intraepithelial lesion and low-grade squamous intraepithelial lesion groups (P < 0.05). C → T/G accounted for 44.12% of base substitution. Copy number variation (false discovery rate < 0.05) was found in 57 chromosome regions. The three regions with significant differences between cervical cancer and non-cervical cancer groups were 1q21.1, 3q26.33, and 13q33.1, covering genes related to tumor proliferation, differentiation, and apoptosis. The frequency of human papillomavirus (HPV) insertion/integration and the number of "tCw" mutations in the cervical cancer group were significantly higher than those in the non-cervical cancer group (P < 0.05). The total number of mutations was positively correlated with the number of "tCw" mutations (R 2 = 0.7967). HPV insertion/integration (OR = 2.302, CI = 1.523-3.589, P = 0.0005), APOBEC enrichment (OR = 17.875, CI = 2.117-150.937, P = 0.001), and HLA-B*39 in HLA-I (OR = 6.435, CI = 0.823-48.919, P = 0.0042) were risk factors for cervical cancer, while HLA-DQB1*05 in HLA-II was a protective factor (OR = 0.426, CI = 0.197-0.910, P = 0.032). Conclusively, HPV insertion/integration, APOBEC mutagenesis, and HLA polymorphisms are high-risk factors for cervical cancer and may be causes of genome instability and somatic mutations. This study provides experimental data for revealing the molecular mechanism of cervical cancer.

NOVAprep-miR-Cervix: New Method for Evaluation of Cervical Dysplasia Severity Based on Analysis of Six miRNAs

Cervical cancer is one of the most common gynecological malignancies and it is preventable through the yearly diagnosis and management of pre-cancerous cervical disease. The profile of miRNA expression in cervical epithelium cells is altered with cervical dysplasia development and further progression. The NOVAprep-miR-CERVIX is a new approach for the assessment of cervical dysplasia through the analysis of six marker miRNAs. This study aims to evaluate theperformance and diagnostic potency of the new method. Cytological smears from 226 women (NILM, n.114; HSIL, n.112) were included in the study. A VPH test was performed with RealBest DNAHPV HR screen Kit, six marker miRNAs (miR-21, -29b, -145, -451a, -1246, -1290) were assayed using NOVAprep-miR-CERVIX kit. Obtained data were analyzed using the Delta Ct method and random forest machine learning algorithm. The results of the quantitative analysis of six microRNAs were expressed as a miR-CERVIX parameter, which ranged from 0 to 1, where "0" corresponded to the healthy cervical epithelium, while "1" corresponded to high-grade squamous intraepithelial dysplasia. The average value of miR-CERVIX differed in groups of NILM and HSIL samples (0.34 vs. 0.72; p < 0.000005). An estimation of miR-CERVIX allowed for the differentiation between healthy and pre-cancerous samples with sensitivity of 0.79 and specificity of 0.79, as well as to confirm HSIL with specificity of 0.98. Interestingly, the HSIL group included HPV(+) and HPV(-) samples, which were statistically significantly different in terms of miR-CERVIX value. Analysis of CC-associated miRNAs in material of cervical smear might serve as an additional method for the evaluation of cervical dysplasia severity.

Candidate Genes and Pathways in Cervical Cancer: A Systematic Review and Integrated Bioinformatic Analysis

Cervical cancer is the leading cause of cancer-related death among women in developing countries. However, no comprehensive molecular mechanism for cervical cancer has been established, as many studies were small-cohort studies conducted with small sample sizes. A thorough literature search was performed using the PubMed, Scopus, EBSCOhost, and Science Direct databases. Medical Subject Heading (MeSH) terms such as "Uterine Cervical Neoplasms" and "gene expression" were used as the keywords in all fields. A total of 4027 studies were retrieved, and only clinical studies, which used the microarray method to identify differentially expressed genes (DEGs) in the cervical tissue of cervical cancer patients, were selected. Following the screening, 6 studies were selected and 1128 DEGs were extracted from the data. Sixty-two differentially expressed genes from at least two studies were selected for further analysis by DAVID, STRING, and Cytoscape software. In cervical cancer pathogenesis, three significant clusters with high intermolecular interactions from the Protein-Protein Interaction (PPI) network complex revealed three major molecular mechanisms, including cell signaling, cell cycle, and cell differentiation. Subsequently, eight genes were chosen as the candidate genes based on their involvement in the relevant gene ontology (GO) and their interaction with other genes in the PPI network through undirected first neighbor nodes. The present systematic review improves our understanding of the molecular mechanism of cervical cancer and the proposed genes that can be used to expand the biomarker panel in the screening for cervical cancer. The targeted genes may be beneficial for the development of better treatment strategies.

Cervical cancer heterogeneity: a constant battle against viruses and drugs

Cervical cancer is the first identified human papillomavirus (HPV) associated cancer and the most promising malignancy to be eliminated. However, the ever-changing virus subtypes and acquired multiple drug resistance continue to induce failure of tumor prevention and treatment. The exploration of cervical cancer heterogeneity is the crucial way to achieve effective prevention and precise treatment. Tumor heterogeneity exists in various aspects including the immune clearance of viruses, tumorigenesis, neoplasm recurrence, metastasis and drug resistance. Tumor development and drug resistance are often driven by potential gene amplification and deletion, not only somatic genomic alterations, but also copy number amplifications, histone modification and DNA methylation. Genomic rearrangements may occur by selection effects from chemotherapy or radiotherapy which exhibits genetic intra-tumor heterogeneity in advanced cervical cancers. The combined application of cervical cancer therapeutic vaccine and immune checkpoint inhibitors has become an effective strategy to address the heterogeneity of treatment. In this review, we will integrate classic and recently updated epidemiological data on vaccination rates, screening rates, incidence and mortality of cervical cancer patients worldwide aiming to understand the current situation of disease prevention and control and identify the direction of urgent efforts. Additionally, we will focus on the tumor environment to summarize the conditions of immune clearance and gene integration after different HPV infections and to explore the genomic factors of tumor heterogeneity. Finally, we will make a thorough inquiry into completed and ongoing phase III clinical trials in cervical cancer and summarize molecular mechanisms of drug resistance among chemotherapy, radiotherapy, biotherapy, and immunotherapy.

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 p16^INK4a 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.

Integrated analysis of cervical squamous cell carcinoma cohorts from three continents reveals conserved subtypes of prognostic significance

Human papillomavirus (HPV)-associated cervical cancer is a leading cause of cancer deaths in women. Here we present an integrated multi-omic analysis of 643 cervical squamous cell carcinomas (CSCC, the most common histological variant of cervical cancer), representing patient populations from the USA, Europe and Sub-Saharan Africa and identify two CSCC subtypes (C1 and C2) with differing prognosis. C1 and C2 tumours can be driven by either of the two most common HPV types in cervical cancer (16 and 18) and while HPV16 and HPV18 are overrepresented among C1 and C2 tumours respectively, the prognostic difference between groups is not due to HPV type. C2 tumours, which comprise approximately 20% of CSCCs across these cohorts, display distinct genomic alterations, including loss or mutation of the STK11 tumour suppressor gene, increased expression of several immune checkpoint genes and differences in the tumour immune microenvironment that may explain the shorter survival associated with this group. In conclusion, we identify two therapy-relevant CSCC subtypes that share the same defining characteristics across three geographically diverse cohorts.

Human papillomavirus (HPV) is a known cause of cervical cancer. Here, the authors perform a multi-omic analysis using published cervical squamous cell carcinoma cohorts from the USA, Europe, and SubSaharan Africa and identify two cervical squamous cell carcinoma subtypes that display prognostic differences.

Expression of GMFB in High-Grade Cervical Intraepithelial Neoplasia and Its Role in Cervical Cancer

Cervical intraepithelial neoplasia (CIN) is a collective term for specific precancerous lesions associated with cervical cancer (CC). Although it has been affirmed with slow development of several levels of cellular changes, the existing poor prognosis calls for an urgent need to diagnose CIN at early stage and be aware of markers related to its pathogenesis and prognosis. We explored the expression level of a newly marker GMFB and its regulatory effect on CIN and CC. Patient samples and cell models were included. Bioinformatic studies were taken to predict its binding to miR-143-3p, miR-26b-5p, miR-191-5p, and miR-223-3p. Luciferase reporter and RNA pull-down assays were used to validate the prediction. Edu assay and flow cytometry were used to measure the regulation of GMFB on proliferation and apoptosis of CC cells. qRT-PCR was used for mRNA expression level detection. The results showed that GMFB was targeted by miR-143-3p, miR-26b-5p, miR-191-5p, and miR-223-3p. It had elevated expression in both CIN and CC samples. GMFB had highly prognostic value for CIN, and lymph node metastasis of CC was much associated with high GMFB expression level. Besides, silencing of GMFB inhibited CC cell proliferation and elevated cell apoptosis. In conclusion, we determined that GMFB has regulatory effect on high grade CIN and CC, which could lighten a novel way in exploring their pathogenesis and improving accuracy of prognosis.

Establishment and genetically characterization of patient-derived xenograft models of cervical cancer

Purpose

Patient-derived xenograft (PDX) models were established to reproduce the clinical situation of original cancers and have increasingly been applied to preclinical cancer research. Our study was designed to establish and genetically characterize cervical cancer PDX models.

Methods

A total of 91 fresh fragments obtained from 22 surgically resected cervical cancer tissues were subcutaneously engrafted into female NOD-SCID mice. Hematoxylin and eosin (H&E) staining was performed to assess whether the established PDX models conserved the histological features of original patient cervical cancer tissues. Moreover, a Venn diagram was applied to display the overlap of all mutations detected in whole-genome sequencing (WGS) data from patient original cervical cancer (F0) and F2-, F3-PDX models. The whole exome sequencing (WES) and the “maftools” package were applied to determine the somatic mutations among primary cervical cancers and the established PDX models.

Results

Our study successfully developed a panel of cervical cancer PDX models and the latency time of cervical cancer PDX model establishment was variable with a progressive decrease as the passage number increased, with a mean time to initial growth of 94.71 days in F1 engraftment to 40.65 days in F3 engraftment. Moreover, the cervical cancer PDX models preserved the histological features of their original cervical cancer. WGS revealed that the genome of original cervical cancer was preserved with high fidelity in cervical cancer PDX models throughout the xenografting and passaging process. Furthermore, WES demonstrated that the cervical cancer PDX models maintained the majority somatic mutations of original cervical cancer, of which the KMT2D, LRP1B, NAV3, TP53, FAT1, MKI67 and PKHD1L1 genes were identified as the most frequently mutated genes.

Conclusions

The cervical cancer PDX models preserved the histologic and genetic characteristics of their original cervical cancer, which helped to gain a deeper insight into the genetic alterations and lay a foundation for further investigation of the molecular targeted therapy of cervical cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01342-5.

Comprehensive characterization of viral integrations and genomic aberrations in HBV-infected intrahepatic cholangiocarcinomas

BACKGROUND AND AIMS

Despite the epidemiological association between intrahepatic cholangiocarcinoma (iCCA) and HBV infection, little is known about the relevant oncogenic effects. We sought to identify the landscape and mechanism of HBV integration, along with the genomic architecture of HBV-infected iCCA (HBV-iCCA) tumors.

APPROACH AND RESULTS

We profiled a cohort of 108 HBV-iCCAs using whole-genome sequencing, deep sequencing, and RNA sequencing, together with preconstructed data sets of HBV-infected HCC (HBV-HCC; n = 167) and combined hepatocellular cholangiocarcinoma (HBV-cHCC/CCA; n = 59), and conventional (n = 154) and fluke-related iCCAs (n = 16). Platforms based on primary iCCA cell lines to evaluate the functional effects of chimeric transcripts were also used. We found that HBV had inserted at multiple sites in the iCCA genomes in 45 (41.7%) of the tumors. Recurrent viral integration breakpoints were found at nine different sites. The most common insertional hotspot (7 tumors) was in the TERT (telomerase reverse transcriptase) promoter, where insertions and mutations (11 tumors) were mutually exclusive, and were accompanied by promoter hyperactivity. Recurrent HBV integration events (5 tumors) were also detected in FAT2 (FAT atypical cadherin 2), and were associated with enrichment of epithelial-mesenchymal transition-related genes. A distinctive intergenic insertion (chr9p21.3), between DMRTA1 (DMRT like family A1) and LINC01239 (long intergenic non-protein coding RNA 1239), had oncogenic effects through activation of the mammalian target of rapamycin (mTOR)/4EBP/S6K pathway. Regarding the mutational profiles of primary liver cancers, the overall landscape of HBV-iCCA was closer to that of nonviral conventional iCCA, than to HBV-HCC and HBV-cHCC/CCA.

CONCLUSIONS

Our findings provide insight into the behavior of iCCAs driven by various pathogenic mechanisms involving HBV integration events and associated genomic aberrations. This knowledge should be of use in managing HBV carriers.

Optimization of Cervical Cancer Screening: A Stacking-Integrated Machine Learning Algorithm Based on Demographic, Behavioral, and Clinical Factors

PURPOSE

The purpose is to accurately identify women at high risk of developing cervical cancer so as to optimize cervical screening strategies and make better use of medical resources. However, the predictive models currently in use require clinical physiological and biochemical indicators, resulting in a smaller scope of application. Stacking-integrated machine learning (SIML) is an advanced machine learning technique that combined multiple learning algorithms to improve predictive performance. This study aimed to develop a stacking-integrated model that can be used to identify women at high risk of developing cervical cancer based on their demographic, behavioral, and historical clinical factors.

METHODS

The data of 858 women screened for cervical cancer at a Venezuelan Hospital were used to develop the SIML algorithm. The screening data were randomly split into training data (80%) that were used to develop the algorithm and testing data (20%) that were used to validate the accuracy of the algorithms. The random forest (RF) model and univariate logistic regression were used to identify predictive features for developing cervical cancer. Twelve well-known ML algorithms were selected, and their performances in predicting cervical cancer were compared. A correlation coefficient matrix was used to cluster the models based on their performance. The SIML was then developed using the best-performing techniques. The sensitivity, specificity, and area under the curve (AUC) of all models were calculated.

RESULTS

The RF model identified 18 features predictive of developing cervical cancer. The use of hormonal contraceptives was considered as the most important risk factor, followed by the number of pregnancies, years of smoking, and the number of sexual partners. The SIML algorithm had the best overall performance when compared with other methods and reached an AUC, sensitivity, and specificity of 0.877, 81.8%, and 81.9%, respectively.

CONCLUSION

This study shows that SIML can be used to accurately identify women at high risk of developing cervical cancer. This model could be used to personalize the screening program by optimizing the screening interval and care plan in high- and low-risk patients based on their demographics, behavioral patterns, and clinical data.

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 $\left(p<0.0001\right)$ . 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.

Molecular Pathology of Human Papilloma Virus-Negative Cervical Cancers

Cervical cancer is the fourth most common cancer in women worldwide and is predominantly caused by infection with human papillomavirus (HPV). However, a small subset of cervical cancers tests negative for HPV, including true HPV-independent cancers and false-negative cases. True HPV-negative cancers appear to be more prevalent in certain pathological adenocarcinoma subtypes, such as gastric- and clear-cell-type adenocarcinomas. Moreover, HPV-negative cervical cancers have proven to be a biologically distinct tumor subset that follows a different pathogenetic pathway to HPV-associated cervical cancers. HPV-negative cervical cancers are often diagnosed at an advanced stage with a poor prognosis and are expected to persist in the post-HPV vaccination era; therefore, it is important to understand HPV-negative cancers. In this review, we provide a concise overview of the molecular pathology of HPV-negative cervical cancers, with a focus on their definitions, the potential causes of false-negative HPV tests, and the histology, genetic profiles, and pathogenesis of HPV-negative cancers.

HPV16 and HPV18 type-specific APOBEC3 and integration profiles in different diagnostic categories of cervical samples

Human papillomavirus (HPV) 16 and 18 are the most predominant types in cervical cancer. Only a small fraction of HPV infections progress to cancer, indicating that additional factors and genomic events contribute to the carcinogenesis, such as minor nucleotide variation caused by APOBEC3 and chromosomal integration. We analysed intra-host minor nucleotide variants (MNVs) and integration in HPV16 and HPV18 positive cervical samples with different morphology. Samples were sequenced using an HPV whole genome sequencing protocol TaME-seq. A total of 80 HPV16 and 51 HPV18 positive samples passed the sequencing depth criteria of 300× reads, showing the following distribution: non-progressive disease (HPV16 n = 21, HPV18 n = 12); cervical intraepithelial neoplasia (CIN) grade 2 (HPV16 n = 27, HPV18 n = 9); CIN3/adenocarcinoma in situ (AIS) (HPV16 n = 27, HPV18 n = 30); cervical cancer (HPV16 n = 5). Similar numbers of MNVs in HPV16 and HPV18 samples were observed for most viral genes, with the exception of HPV18 E4 with higher numbers across clinical categories. APOBEC3 signatures were observed in HPV16 lesions, while similar mutation patterns were not detected for HPV18. The proportion of samples with integration was 13% for HPV16 and 59% for HPV18 positive samples, with a noticeable portion located within or close to cancer-related genes.

The Help of HPV Integration Testing to Avoid the Misdiagnosis of a Patient with Stage Ia1 Cervical Cancer: A Case Report and Literature Review

Screening and prevention in the early stage of cervical cancer could improve the 5-year survival rate of cervical cancer by up to 90%. The occurrence rate of human papillomavirus (HPV) integration has gradually increased with the development of cervical lesions. Here, we report the case of a 43-year-old woman diagnosed with chronic cervicitis based on cervical biopsy results. After medical consultation, surgery was recommended to the patient considering her 64 HPV integration sites and other biochemical and clinical test results. The pathology result of the conical biopsy obtained during operation confirmed that both her cervix and the glands had high-grade squamous intraepithelial lesion or cervical intraepithelial neoplasia III (HSIL/CIN III). The patient underwent uterectomy and bilateral salpingectomy and was discharged thereafter. The diagnosis of the patient was revised to stage Ia1 cervical cancer. The number of HPV integration sites is suggested to be an auxiliary indicator in the early screening of cervical cancer for predicting high-grade CIN and invasive cervical cancer.

Genomic alterations associated with mutational signatures, DNA damage repair and chromatin remodeling pathways in cervical carcinoma

Despite recent advances in the prevention of cervical cancer, the disease remains a leading cause of cancer-related deaths in women worldwide. By applying the GISTIC2.0 and/or the MutSig2CV algorithms on 430 whole-exome-sequenced cervical carcinomas, we identified previously unreported significantly mutated genes (SMGs) (including MSN, GPX1, SPRED3, FAS, and KRT8), amplifications (including NFIA, GNL1, TGIF1, and WDR87) and deletions (including MIR562, PVRL1, and NTM). Subset analyses of 327 squamous cell carcinomas and 86 non-squamous cell carcinomas revealed previously unreported SMGs in BAP1 and IL28A, respectively. Distinctive copy number alterations related to tumors predominantly enriched for *CpG- and Tp*C mutations were observed. CD274, GRB2, KRAS, and EGFR were uniquely significantly amplified within the Tp*C-enriched tumors. A high frequency of aberrations within DNA damage repair and chromatin remodeling genes were detected. Facilitated by the large sample size derived from combining multiple datasets, this study reveals potential targets and prognostic markers for cervical cancer.

Protein tyrosine phosphatase, receptor type B is a potential biomarker and facilitates cervical cancer metastasis via epithelial-mesenchymal transition

Cervical cancer (CC) is one of the most common malignant tumors. This study analyzed the impact of protein tyrosine phosphatase, receptor type B (PTPRB) on malignant behavior of CC and explored its possible molecular mechanism. RT-PCR, western blot and Immunohistochemistry were applied to examine the expression of PTPRB in CC specimens and cells. Aberrant PTPRB expression in CC and survival outcomes were constructed using The Cancer Genome Atlas (TCGA) database and tissue microarray cervical squamous cell carcinoma cohort. Cultured human CC cells were assayed for viability, apoptosis, migration, and invasion in vitro and in vivo. Kyoto Encyclopedia of Genes and Genomes (KEGG) assays and gene set enrichment analysis (GSEA) assays were used to delve into PTPRB-related pathways using TCGA datasets. The levels of proteins associated with the epithelial-mesenchymal transition (EMT) pathway and modulated by PTPRB were examined through Western blot. We found that the levels of PTPRB in CC tissues and cells were distinctly up-regulated. PTPRB was also an unfavorable prognostic factor for CC patients. Functionally, PTPRB knockdown exhibits tumor-suppressive function via reducing cell proliferation and metastasis and inducing cell apoptosis. KEGG assays and GSEA assays suggested PTPRB overexpression was associated with several tumor-related pathways. The results of Western blot assays suggested that N-cadherin was decreased in the PTPRB-knockdown CC cells, while E-cadherin was increased. Overall, PTPRB is highly expressed in CC and can effectively enhance the proliferation, metastasis and EMT process of tumor cells. PTPRB is expected to be a therapeutic target for CC.

Reduced MAGI3 level by HPV18E6 contributes to Wnt/β-catenin signaling activation and cervical cancer progression

Human papillomavirus type 18 (HPV18) has high carcinogenic power in invasive cervical cancer (ICC) development. However, the underlying mechanism remains elusive. The carcinogenic properties of HPV18 require the PDZ‐binding motif of its E6 oncoprotein (HPV18 E6) to degrade its target PSD95/Dlg/ZO‐1 (PDZ) proteins. In this study, we demonstrated that the PDZ protein membrane‐associated guanylate kinase, WW and PDZ domain containing 3 (MAGI3) inhibited the Wnt/β‐catenin pathway, and subsequently cervical cancer (CC) cell migration and invasion, via decreasing β‐catenin levels. By reducing MAGI3 protein levels, HPV18 E6 promoted CC cell migration and invasion through activation of Wnt/β‐catenin signaling. Furthermore, HPV18 rather than HPV16 was preferentially associated with the downregulation of MAGI3 and activation of the Wnt/β‐catenin pathway in CC. These findings shed light on the mechanism that gives HPV18 its high carcinogenic potential in CC progression.

An epigenomic landscape of cervical intraepithelial neoplasia and cervical cancer using single-base resolution methylome and hydroxymethylome

BACKGROUND

Cervical cancer (CC) is the second leading cause of cancer death among women worldwide. Epigenetic regulation of gene expression through DNA methylation and hydroxymethylation plays a pivotal role during tumorigenesis. In this study, to analyze the epigenomic landscape and identify potential biomarkers for CCs, we selected a series of samples from normal to cervical intra-epithelial neoplasia (CINs) to CCs and performed an integrative analysis of whole-genome bisulfite sequencing (WGBS-seq), oxidative WGBS, RNA-seq, and external histone modifications profiling data.

RESULTS

In the development and progression of CC, there were genome-wide hypo-methylation and hypo-hydroxymethylation, accompanied by local hyper-methylation and hyper-hydroxymethylation. Hydroxymethylation prefers to distribute in the CpG islands and CpG shores, as displayed a trend of gradual decline from health to CIN2, while a trend of increase from CIN3 to CC. The differentially methylated and hydroxymethylated region-associated genes both enriched in Hippo and other cancer-related signaling pathways that drive cervical carcinogenesis. Furthermore, we identified eight novel differentially methylated/hydroxymethylated-associated genes (DES, MAL, MTIF2, PIP5K1A, RPS6KA6, ANGEL2, MPP, and PAPSS2) significantly correlated with the overall survival of CC. In addition, no any correlation was observed between methylation or hydroxymethylation levels and somatic copy number variations in CINs and CCs.

CONCLUSION

Our current study systematically delineates the map of methylome and hydroxymethylome from CINs to CC, and some differentially methylated/hydroxymethylated-associated genes can be used as the potential epigenetic biomarkers in CC prognosis.

The Role of Human Papilloma Virus in Dictating Outcomes in Head and Neck Squamous Cell Carcinoma

The Human Papilloma Virus (HPV) is an oncogenic virus which is associated with the development of head and neck squamous cell carcinoma (HNSCC), predominantly within the oropharynx. Approximately 25% of oropharyngeal squamous cell carcinoma (OPSCC) cases worldwide are attributable to HPV infection, with an estimated 65% in the United States. Transmission is via exposure during sexual contact, with distinctive anatomical features of the tonsils providing this organ with a predilection for infection by HPV. No premalignant lesion is identifiable on clinical examination, thus no comparative histological features to denote the stages of carcinogenesis for HPV driven HNSCC are identifiable. This is in contrast to HPV-driven cervical carcinoma, making screening a challenge for the head and neck region. However, HPV proffers a favorable prognosis in the head and neck region, with better overall survival rates in contrast to its HPV negative counterparts. This has resulted in extensive research into de-intensifying therapies aiming to minimize the morbidity induced by standard concurrent chemo-radiotherapy without compromising efficacy. Despite the favorable prognosis, cases of recurrence and/or metastasis of HPV positive HNSCC do occur, and are linked with poor outcomes. HPV 16 is the most frequent genotype identified in HNSCC, yet there is limited research to date studying the impact of other HPV genotype with respect to overall survival. A similar situation pertains to genetic aberrations associated in those with HPV positive HNSCC who recur, with only four published studies to date. Somatic mutations in TSC2, BRIP1, NBN, TACC3, NFE2l2, STK11, HRAS, PIK3R1, TP63, and FAT1 have been identified in recurrent HPV positive OPSCC. Finding alternative therapeutic strategies for this young cohort may depend on upfront identification of HPV genotypes and mutations which are linked with worse outcomes, thus ensuring appropriate stratification of treatment regimens.

Identifying Potential Neoantigens for Cervical Cancer Immunotherapy Using Comprehensive Genomic Variation Profiling of Cervical Intraepithelial Neoplasia and Cervical Cancer

Cervical cancer (CC) is one of the most common gynecological malignant tumors. The 5-year survival rate remains poor for the advanced and metastatic cervical cancer for the lack of effective treatments. Immunotherapy plays an important role in clinical tumor therapy. Neoantigens derived from tumor-specific somatic mutations are prospective targets for immunotherapy. Hence, the identification of new targets is of great significance for the treatment of advanced and metastatic cervical cancer. In this study, we performed whole-exome sequencing in 70 samples, including 25 cervical intraepithelial neoplasia (CINs) with corresponding blood samples and 10 CCs along with paired adjacent tissues to identify genomic variations and to find the potential neoantigens for CC immunotherapy. Using systematic bioinformatics pipeline, we found that C>T transitions were in both CINs and CCs. In contrast, the number of somatic mutations in CCs was significantly higher than those in CINs (t-test, P = 6.60E-04). Meanwhile, mutational signatures analysis revealed that signature 6 was detected in CIN2, CIN3, and CC, but not in CIN1, while signature 2 was only observed in CCs. Furthermore, PIK3CA, ARHGAP5 and ADGRB1 were identified as potential driver genes in this report, of which ADGRB1 was firstly reported in CC. Based on the genomic variation profiling of CINs and CCs, we identified 2586 potential neoantigens in these patients, of which 45 neoantigens were found in three neoantigen-related databases (TSNAdb, IEDB, and CTDatabase). Our current findings lay a solid foundation for the study of the pathogenesis of CC and the development of neoantigen-targeted immunotherapeutic measures.

Genomic alterations in gynecological malignancies: histotype-associated driver mutations, molecular subtyping schemes, and tumorigenic mechanisms

There are numerous histological subtypes (histotypes) of gynecological malignancies, with each histotype considered to largely reflect a feature of the "cell of origin," and to be tightly linked with the clinical behavior and biological phenotype of the tumor. The recent advances in massive parallel sequencing technologies have provided a more complete picture of the range of the genomic alterations that can persist within individual tumors, and have highlighted the types and frequencies of driver-gene mutations and molecular subtypes often associated with these histotypes. Several large-scale genomic cohorts, including the Cancer Genome Atlas (TCGA), have been used to characterize the genomic features of a range of gynecological malignancies, including high-grade serous ovarian carcinoma, uterine corpus endometrial carcinoma, uterine cervical carcinoma, and uterine carcinosarcoma. These datasets have also been pivotal in identifying clinically relevant molecular targets and biomarkers, and in the construction of molecular subtyping schemes. In addition, the recent widespread use of clinical sequencing for the more ubiquitous types of gynecological cancer has manifested in a series of large genomic datasets that have allowed the characterization of the genomes, driver mutations, and histotypes of even rare cancer types, with sufficient statistical power. Here, we review the field of gynecological cancer, and seek to describe the genomic features by histotype. We also will demonstrate how these are linked with clinicopathological attributes and highlight the potential tumorigenic mechanisms.

A Drosophila platform identifies a novel, personalized therapy for a patient with adenoid cystic carcinoma

Adenoid cystic carcinoma (ACC) is a rare cancer type that originates in the salivary glands. Tumors commonly invade along nerve tracks in the head and neck, making surgery challenging. Follow-up treatments for recurrence or metastasis including chemotherapy and targeted therapies have shown limited efficacy, emphasizing the need for new therapies. Here, we report a Drosophila-based therapeutic approach for a patient with advanced ACC disease. A patient-specific Drosophila transgenic line was developed to model the five major variants associated with the patient's disease. Robotics-based screening identified a three-drug cocktail—vorinostat, pindolol, tofacitinib—that rescued transgene-mediated lethality in the Drosophila patient-specific line. Patient treatment led to a sustained stabilization and a partial metabolic response of 12 months. Subsequent resistance was associated with new genomic amplifications and deletions. Given the lack of options for patients with ACC, our data suggest that this approach may prove useful for identifying novel therapeutic candidates.

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Personalized therapy was developed for patient with Adenoid Cystic Carcinoma

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Genomics analysis was leveraged to establish a Drosophila ‘personalized patient avatar’

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A robotics-based screen identified a novel three drug therapeutic cocktail

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12 months response was followed by relapse and significant tumor genomic re-wiring

Association between oncogenic human papillomavirus type 16 and Killian polyp

BACKGROUND

Killian polyp (KP) is a benign lesion that arises from the maxillary sinus. The etiology of KP is unknown. The aim of this study was to investigate the potential involvement of human papilloma- (HPV) and polyoma-viruses (HPyV) infections in the onset of KP.

METHODS

DNA from antral (n = 14) and nasal (n = 14) KP fractions were analyzed for HPV and HPyV sequences, genotypes, viral DNA load and physical status along with expression of viral proteins and p16 cellular protein.

RESULTS

The oncogenic HPV16 was detected in 3/14 (21.4%) antral KPs, whilst nasal KPs tested HPV-negative (0/14). The mean HPV16 DNA load was 4.65 ± 2.64 copy/104 cell. The whole HPV16 episomal genome was detected in one KP sample, whereas HPV16 DNA integration in two KPs. P16 mRNA level was lower in the KP sample carrying HPV16 episome than in KPs carrying integrated HPV16 and HPV- negative KPs (p< 0.001). None of the antral and nasal KP samples tested positive for HPyV DNA (0/28).

CONCLUSIONS

A fraction of KP tested positive for the oncogenic HPV16. HPV16 detection in the KP antral portion may be consistent with HPV16 infection derived from the maxillary sinus. HPV16 DNA integration represents a novel finding. Altogether, these data improve our knowledge on the association between KP and HPV infection, whereas it indicates that the KP onset is heterogeneous.

Mutation profiling of uterine cervical cancer patients treated with definitive radiotherapy

OBJECTIVE

To elucidate tumor mutation profiles associated with outcomes of uterine cervical cancer (UCC) patients treated with definitive radiotherapy.

METHODS

Ninety-eight patients with newly diagnosed and pathologically confirmed UCC (82 squamous cell carcinomas, 12 adenocarcinomas, and four adenosquamous carcinomas) who were treated with definitive radiotherapy were analyzed. DNA was extracted from pre-treatment tumor biopsy specimens. The exons of 409 cancer-related genes were sequenced using a next-generation sequencer. Genetic mutations were identified and analyzed for correlations with clinical outcome.

RESULTS

Recurrent mutations were observed in PIK3CA (35.7%), ARID1A (25.5%), NOTCH1 (19.4%), FGFR3 (16.3%), FBXW7 (19.4%), TP53 (13.3%), EP300 (12.2%), and FGFR4 (10.2%). The prevalence of mutations in FGFR family genes (i.e., FGFR1-4) was almost as high (24.5%) as that in PIK3CA and ARID1A, both of which are well-studied drivers of UCC. Fifty-five percent (21 of 38) of the identified FGFR mutations were located in the FGFR protein tyrosine kinase domain. Five-year progression-free survival (PFS) rates for FGFR mutation-positive patients (n = 24) were significantly worse than those for FGFR mutation-negative patients (n = 74) (43.9% vs. 68.5%, respectively; P = 0.010). Multivariate analysis identified FGFR mutations as significant predictors of worse 5 year PFS (P = 0.005), independent of clinicopathological variables.

CONCLUSIONS

FGFR mutations are associated with worse PFS in UCC patients treated with definitive radiotherapy. These results warrant further validation in prospective studies.

Artificial intelligence (AI) and big data in cancer and precision oncology

Artificial intelligence (AI) and machine learning have significantly influenced many facets of the healthcare sector. Advancement in technology has paved the way for analysis of big datasets in a cost- and time-effective manner. Clinical oncology and research are reaping the benefits of AI. The burden of cancer is a global phenomenon. Efforts to reduce mortality rates requires early diagnosis for effective therapeutic interventions. However, metastatic and recurrent cancers evolve and acquire drug resistance. It is imperative to detect novel biomarkers that induce drug resistance and identify therapeutic targets to enhance treatment regimes. The introduction of the next generation sequencing (NGS) platforms address these demands, has revolutionised the future of precision oncology. NGS offers several clinical applications that are important for risk predictor, early detection of disease, diagnosis by sequencing and medical imaging, accurate prognosis, biomarker identification and identification of therapeutic targets for novel drug discovery. NGS generates large datasets that demand specialised bioinformatics resources to analyse the data that is relevant and clinically significant. Through these applications of AI, cancer diagnostics and prognostic prediction are enhanced with NGS and medical imaging that delivers high resolution images. Regardless of the improvements in technology, AI has some challenges and limitations, and the clinical application of NGS remains to be validated. By continuing to enhance the progression of innovation and technology, the future of AI and precision oncology show great promise.

Genes Regulated by HPV 16 E6 and High Expression of NFX1-123 in Cervical Cancers

Purpose

High-risk human papillomaviruses (HR HPV) cause cervical cancer, and in these cancers, HPV type 16 is the most common HR type. The HR viral oncogenes E6 and E7 partner with cellular proteins to drive cancer and modulate immune pathways; previously, we demonstrated in keratinocytes that HPV 16 E6 and high expression of the endogenous host protein partner NFX1-123 led to the increased expression of multiple genes, including Notch1, secretory leukocyte peptidase inhibitor (SLPI), and retinoic acid early transcript 1G (RAET1G). The present study was conducted to determine if NFX1-123 was highly expressed in cervical cancer and if genes increased by NFX1-123 and 16E6 in keratinocytes were also increased in cervical cancers.

Materials and Methods

The Cancer Genome Atlas (TCGA) database and The Human Protein Atlas database were used to compare relative mRNA and protein gene expression, respectively, in the normal cervix and cervical cancers. Formalin-fixed paraffin-embedded (FFPE) normal cervix and HPV 16 positive cervical cancer samples were analyzed for relative protein expression by immunohistochemical staining. Protein expression of a subset of regulated genes was quantified by Western blot of HPV positive and negative cell lines.

Results

Immunohistochemical staining of HPV 16 positive cervical dysplasias and cancers revealed high NFX1-123, Ki67, and Notch1 expression. NFX1 and NFX1L1 mRNA levels were increased in cervical cancers compared to normal cervix in the TCGA database. Fourteen genes previously identified as upregulated in keratinocytes with 16E6 and overexpressed NFX1-123 also had high mRNA expression and selected genes had high protein expression in cervical cancers and cell lines.

Conclusion

In cervical cancer, NFX1-123 is highly expressed, and 16E6 and NFX1-123 together alter the expression of a wide set of genes. The involvement of these genes in cell proliferation, differentiation, invasion, and metastasis provides further insight into potential ways that HR HPVs promote cancer initiation and maintenance.

Simultaneous detection and comprehensive analysis of HPV and microbiome status of a cervical liquid-based cytology sample using Nanopore MinION sequencing

Human papillomavirus (HPV) is a major pathogen that causes cervical cancer and many other related diseases. HPV infection related cervical microbiome could be an induce factor of cervical cancer. However, it is uncommon to find a single test on the market that can simultaneously provide information on both HPV and the microbiome. Herein, a novel method was developed in this study to simultaneously detect HPV infection and microbiota composition promptly and accurately. It provides a new and simple way to detect vaginal pathogen situation and also provide valuable information for clinical diagnose. This approach combined multiplex PCR, which targeted both HPV16 E6E7 and full-length 16S rRNA, and Nanopore sequencing to generate enough information to understand the vagina condition of patients. One HPV positive liquid-based cytology (LBC) sample was sequenced and analyzed. After comparing with Illumina sequencing, the results from Nanopore showed a similar microbiome composition. An instant sequencing evaluation showed that 15 min sequencing is enough to identify the top 10 most abundant bacteria. Moreover, two HPV integration sites were identified and verified by Sanger sequencing. This approach has many potential applications in pathogen detection and can potentially aid in providing a more rapid clinical diagnosis.

Squamous cell carcinoma of the common bile duct: A case report with genomic profiling

Squamous cell carcinoma of the extrahepatic bile ducts is a very rare type of cancer with a virtually unknown pathogenesis. We present the case of a 66-year-old woman who underwent a pancreaticoduodenectomy with the postoperative diagnosis of squamous cell carcinoma of the common bile duct. Microscopically, the entire common bile duct showed squamous metaplasia. Besides, an invasive squamous cell carcinoma was found, stage pT3pN0. A next generation sequencing assay covering 315 tumor-related genes revealed genomic alterations in seven genes: FBXW7, CREBBP, CTCF, FAT1, MAGI2, MLL2, and NOTCH1.

Human Papilloma Virus-Associated Cervical Cancer and Health Disparities

Cervical cancer develops through persistent infection with high-risk human papilloma virus (hrHPV) and is a leading cause of death among women worldwide and in the United States. Periodic surveillance through hrHPV and Pap smear-based testing has remarkably reduced cervical cancer incidence worldwide and in the USA. However, considerable discordance in the occurrence and outcome of cervical cancer in various populations exists. Lack of adequate health insurance appears to act as a major socioeconomic burden for obtaining cervical cancer preventive screening in a timely manner, which results in disparate cervical cancer incidence. On the other hand, cervical cancer is aggressive and often detected in advanced stages, including African American and Hispanic/Latina women. In this context, our knowledge of the underlying molecular mechanism and genetic basis behind the disparate cervical cancer outcome is limited. In this review, we shed light on our current understanding and knowledge of racially disparate outcomes in cervical cancer.

Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles

From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical cancer takes decades. High-sensitivity HPV DNA testing is currently recommended as primary screening method for cervical cancer, whereas better triage methodologies are encouraged to provide accurate risk management for HPV-positive women. Given that virus-driven genomic variation accumulates during cervical carcinogenesis, we designed a 39 Mb custom capture panel targeting 17 HPV types and 522 mutant genes related to cervical cancer. Using capture-based next-generation sequencing, HPV integration status, somatic mutation and copy number variation were analyzed on 34 paired samples, including 10 cases of HPV infection (HPV+), 10 cases of cervical intraepithelial neoplasia (CIN) grade and 14 cases of CIN2+ (CIN2: n = 1; CIN2-3: n = 3; CIN3: n = 9; squamous cell carcinoma: n = 1). Finally, the machine learning algorithm (Random Forest) was applied to build the risk stratification model for cervical precursor lesions based on CIN2+ enriched biomarkers. Generally, HPV integration events (11 in HPV+, 25 in CIN1 and 56 in CIN2+), non-synonymous mutations (2 in CIN1, 12 in CIN2+) and copy number variations (19.1 in HPV+, 29.4 in CIN1 and 127 in CIN2+) increased from HPV+ to CIN2+. Interestingly, ‘common’ deletion of mitochondrial chromosome was significantly observed in CIN2+ (P = 0.009). Together, CIN2+ enriched biomarkers, classified as HPV information, mutation, amplification, deletion and mitochondrial change, successfully predicted CIN2+ with average accuracy probability score of 0.814, and amplification and deletion ranked as the most important features. Our custom capture sequencing combined with machine learning method effectively stratified the risk of cervical lesions and provided valuable integrated triage strategies.