| Literature DB >> 35402283 |
Lingyi Zhang1,2, Wenxi Tan2, Hongmei Yang1,3, Songling Zhang4, Yun Dai1.
Abstract
Cervical cancer is the most prevalent gynecologic malignancy, especially in women of low- and middle-income countries (LMICs). With a better understanding of the etiology and pathogenesis of cervical cancer, it has been well accepted that this type of cancer can be prevented and treated via early screening. Due to its higher sensitivity than cytology to identify precursor lesions of cervical cancer, detection of high-risk human papillomavirus (HR-HPV) DNA has been implemented as the primary screening approach. However, a high referral rate for colposcopy after HR-HPV DNA detection due to its low specificity in HR-HPV screening often leads to overtreatment and thus increases the healthcare burden. Emerging evidence has demonstrated that detection of host cell gene and/or HPV DNA methylation represents a promising approach for the early triage of cervical cancer in HR-HPV-positive women owing to its convenience and comparable performance to cytology, particularly in LMICs with limited healthcare resources. While numerous potential markers involving DNA methylation of host cell genes and the HPV genome have been identified thus far, it is crucial to define which genes or panels involving host and/or HPV are feasible and appropriate for large-scale screening and triage. An ideal approach for screening and triage of CIN/ICC requires high sensitivity and adequate specificity and is suitable for self-sampling and inexpensive to allow population-based screening, particularly in LMICs. In this review, we summarize the markers of host cell gene/HR-HPV DNA methylation and discuss their triage performance and feasibility for high-grade precancerous cervical intraepithelial neoplasia or worse (CIN2+ and CIN3+) in HR-HPV-positive women.Entities:
Keywords: DNA methylation; cervical cancer; cervical intraepithelial neoplasia; high-risk human papillomavirus; host cell gene; triage
Year: 2022 PMID: 35402283 PMCID: PMC8990922 DOI: 10.3389/fonc.2022.831949
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 6.244
Figure 1The mechanistic basis for detection of host gene and HPV DNA methylation for early screening of CIN/ICC. During persistent HR-HPV infection and cervical oncogenesis, hypermethylation of the host gene and viral genomic DNA is closely associated with the severity of CIN lesions and the risk of progression to ICC. With understanding the molecular mechanisms for HPV-mediated carcinogenesis, the positive correlation has been well established between CIN/ICC and hypermethylation of the CpG sites of HPV genomes (e.g., L1, L2, and E2BS) (A), or between CIN/ICC and hypermethylation of the CpG sites of host cell gene promoters (B). A number of studies have demonstrated that abnormal DNA methylations of host genes and/or HPVs, particularly in combination of multiple genes (i.e., gene panels), are capable of distinguishing non-progressive HPV infections from those associated with the potential to develop into ICC, therefore representing promising biomarkers for the triage of CIN lesions in HR-HPV infected women. Accordingly, a flowchart illustrates the potential process for the screening and triage of cervical cancer by integrating host cell gene/HPV DNA methylation detection in the future (C).
Risk classification of HPVs in cervical cancer.
| Category | Virus types |
|---|---|
| High risk HPV (HR-HPV) | HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 |
| Probable HR-HPV | HPV 68 |
| Possible HR-HPV | HPV 26, 53, 66, 67, 70, 73, 82 |
Figure 2The alterations of DNA methylation-regulatory genes and their relationship with patient survival in ICC. The molecular alterations of DNA methylation modifiers at the genetic, transcriptomic, and protein levels, as well as their effects on the outcome of patients with ICC, are analyzed using various public available databases. (A) Genetic mutations (black—nonsense, green—missense, brown—in-frame deletion) of DNMTs and TETs in ICC, using the Cervical Squamous Cell Carcinoma dataset (TGCA, PanCancer Atlas; n = 294) on the cBioPortal for Cancer Genomics platform (www.cbioportal.org). (B) Immunohistochemical (IHC) staining of DNMTs and TETs in ICC, using the Cervical Cancer dataset on the Human Protein Atlas platform (www.proteinatlas.org). Representative images are shown. For each bar graph, the y-axis indicates the number of cases; the left bar indicates staining intensity (blue—strong, red—moderate, green—weak, purple—negative); the right bar indicates quantity (blue—>75%, red—25%~75%. green—<25%, purple—none). Note: the IHC data for TET1 are not available. (C) Relationship between mRNA levels of DNMTs or TETs and overall survival of ICC patients, using the Tumor Cervical Squamous Cell Carcinoma - TCGA dataset (TCGA ID: CESC; n = 303; DNMT1: high = 155, low = 148; DNMT3A: high = 270, low = 33; DNMT3B: high = 231, low = 72; TET1: high = 290, low = 13; TET2: high = 290, low = 13; TET3: high = 246, low = 57) on the R2: Genomics Analysis and Visualization Platform (http://r2.amc.nl) and the Cervical Cancer dataset (n = 291; DNMT1: high = 101, low = 190; DNMT3A: high = 204, low = 87; DNMT3B: high = 228, low = 63; TET1: high = 198, low = 93; TET2: high = 106, low = 185; TET3: high = 229, low = 62) on the Human Protein Atlas (HPA) platform (www.proteinatlas.org). Positive correlation = high mRNA levels correlate with poor outcome; Negative correlation = low mRNA levels correlate with poor outcome.
Comparison of host gene methylation markers alone or in combination for detecting CIN2+/CIN3+ in HR-HPV-positive women.
| Gene/gene panel | Tissue type | Sample number | CIN2+ | CIN3+ | Ref | ||
|---|---|---|---|---|---|---|---|
| Sensitivity (%) | Specificity (%) | Sensitivity (%) | Specificity (%) | ||||
| FAM19A4 | Scrapes | 218 | 69.2 | 69.9 | 75.8 | 67.0 | ( |
| FAM19A4 | Scrapes | 508 | 57.8 | 74.1 | 75.6 | 71.1 | ( |
| FAM19A4 | Vaginal lavage | 450 | 44.4 | 82.8 | 65.3 | 81.3 | ( |
| JAM3 | Scrapes | 128 | 63.0 | 90.0 | 82.0 | 88.0 | ( |
| C13ORF18 | Scrapes | 128 | 49.0 | 92.0 | 65.0 | 91.0 | ( |
| EPB41L3 | Scrapes | 128 | 67.0 | 57.0 | 88.0 | 61.0 | ( |
| TERT | Scrapes | 128 | 69.0 | 62.0 | 76.0 | 60.0 | ( |
| ZNF582 | Scrapes | 230 | NA | NA | 83.0 | 71.0 | ( |
| PTPRR | Scrapes | 230 | NA | NA | 92.0 | 49.0 | ( |
| PAX1 | Scrapes | 230,55 | NA | NA | 46.0,60.0 | 86.0,100.0 | ( |
| SOX1 | Scrapes | 230,55 | NA | NA | 62.0,63.0 | 76.0,74.0 | ( |
| POU4F3 | Scrapes | 100 | NA | NA | 88.0 | 82.0 | ( |
| POU4F3 | Scrapes | 55 | NA | NA | 74.0 | 89.0 | ( |
| CADM1/MAL | FFPE | 261 | NA | NA | 70.0 | 78.0 | ( |
| CADM1/MAL | Scrapes | 236 | NA | NA | 60.5~100 | 83.3 | ( |
| FAM19A4/miR124-2 | Scrapes | 2384 | 33.3~61.1 | 71.1~80.3 | 75.0~78.2 | 71.1~80.3 | ( |
| CCNA1/C13ORF18 | Scrapes | 89 | 37.0 | 96.0 | NA | NA | ( |
| C13ORF18/JAM3/ | Scrapes | 107 | 65.0 | NA | 82.0 | NA | ( |
| C13ORF18/JAM3/ | Scrapes | 215 | 74.0 | 76.0 | NA | NA | ( |
| C13ORF18/EPB41L3/ | Scrapes | 235 | 80.0 | 66.0 | 95.0 | 64.0 | ( |
| ANKRD18CP/ | Scrapes | 235 | 60.0 | 68.0 | 68.0 | 67.0 | ( |
| SOX1/ZSCAN1 | Scrapes | 235 | 63.0 | 84.0 | 79.0 | 81.0 | ( |
| DLX1/ITGA4/RXFP3/ | Scrapes | 217 | 56.0 | 88.7 | 76.2 | 82.9 | ( |
| AJAP1/MAG12/POU4F3 | Scrapes | 100 | NA | NA | 73.0 | 97.0 | ( |
| AJAP1/EDN3/EPO/ | Scrapes | 100 | NA | NA | 73.0 | 98.0 | ( |
| DAPK1/RARB/TWIST1 | Biopsy | 319 | NA | NA | 52.0 | 95.0 | ( |
| ASTN1/DLX1/ITGA4/ | Scrapes | 189 | NA | NA | 67.4 | 76.0 | ( |
| EPB41L3/SOX1/DCC | Scrapes | 167 | NA | NA | 70.0 | 91.0 | ( |
| EPB41L3/SOX1 | Scrapes | 167 | NA | NA | 76.0 | 87.0 | ( |
| EPB41L3/DCC | Scrapes | 167 | NA | NA | 76.0 | 86.0 | ( |
| SOX1/DCC | Scrapes | 167 | NA | NA | 75.0 | 84.0 | ( |
| SOX1/PAX1/LMX1A/ | Scrapes | 185 | NA | NA | 88.0 | 82.0 | ( |
NA, not available.
Comparison of HPV DNA methylation markers for detecting CIN2+/CIN3+.
| Gene/Gene panel | Tissue type | Sample number | CIN2+ | CIN3+ | AUC | Ref | ||
|---|---|---|---|---|---|---|---|---|
| Sensitivity(%) | Specificity(%) | Sensitivity(%) | Specificity(%) | |||||
| HPV18,31,45 genomes | Cytology | 188 | NA | NA | NA | NA | 0.85/0.81/0.98 | ( |
| HPV16 genome | Exfoliated cell | 273 | 91.0 | 60.0 | NA | NA | 0.82 | ( |
| HPV16 L1 | Cytology | 145 | NA | NA | 75.7 | 77.5 | 0.85 | ( |
| HPV16 L1/LCR | Cytology | 77 | NA | NA | 85.7 | 78.4 | 0.80 | ( |
| HR-HPV 16/18/31/33/35/39/45/51/52/56/58/59 L1/L2 | Cytology | 659 | NA | NA | 80.0 | 65.6 | 0.46 | ( |
| EPB41L3/HPV16/18/31 | Cytology | 1493 | 90.0 | 36.0 | NA | NA | 0.80 | ( |
| EPB41L3/HPV16/18/31/33 | Cytology | 1493 | 90.0 | 49.0 | NA | NA | 0.82 | ( |
| EPB41L3/HPV16/18/31/33 | Cytology | 341 | 74.0 | 65.0 | NA | NA | 0.78 | ( |
| EPB41L3/HPV16/18/31/33 | Cytology | 257 | 75.7 | 44.0 | 93.2 | 41.8 | 0.81/0.85 | ( |
| EPB41L3/HPV16/18/31/33 | Exfoliated cell | 316 | 62.0 | 73.0 | 70.3 | 76.6 | 0.75/0.81 | ( |
NA, not available; AUC, area under the curve.