Cytological Immunostaining of HMGA2, LRP1B, and TP63 as Potential Biomarkers for Triaging Human Papillomavirus-Positive Women

Direct Comparison of HPV16 Viral Genomic Integration, Copy Loss, and Structural Variants in Oropharyngeal and Uterine Cervical Cancers Reveal Distinct Relationships to E2 Disruption and Somatic Alteration

Squamous cell carcinoma of the oropharynx caused by HPV type 16 (HPV16+ OPSCC) is the most common HPV-associated malignancy in the USA and has many molecular differences from uterine cervical squamous cell carcinoma (UCSCC). Our understanding of HPV oncogenesis relied on studies of UCSCC revealing a consensus model reliant on HPV integration with a loss of E2. Here, we compare patterns of HPV integration in UCSCC and OPSCC by analysis of affinity capture sequencing of the HPV16 genome in 104 OPSCC and 44 UCSCC tumors. These cohorts were contemporaneously sequenced using an identical strategy. Integration was identified using discordant read pair clustering and assembly-based approaches. Viral integration sites, structural variants, and copy losses were examined. While large-scale deep losses of HPV16 genes were common in UCSCC and were associated with E2 loss, deep copy losses of the HPV16 genome were infrequent in HPV16+ OPSCC. Similarly, structural variants within HPV16 favored E2 loss in UCSCC but not OPSCC. HPV16 integration sites were non-random, with recurrent integration hot-spots identified. OPSCC tumors had many more integration sites per tumor when compared to UCSCC and had more integration sites in genomic regions with high gene density. These data show that viral integration and E2 disruption are distinct in UCSCC and OPSCC. Our findings also add to growing literature suggesting that HPV tumorigenesis in OPSCC does not follow the model developed based on UCSCC.

LRP1B: A Giant Lost in Cancer Translation

Low-density lipoprotein receptor-related protein 1B (LRP1B) is a giant member of the LDLR protein family, which includes several structurally homologous cell surface receptors with a wide range of biological functions from cargo transport to cell signaling. LRP1B is among the most altered genes in human cancer overall. Found frequently inactivated by several genetic and epigenetic mechanisms, it has mostly been regarded as a putative tumor suppressor. Still, limitations in LRP1B studies exist, in particular associated with its huge size. Therefore, LRP1B expression and function in cancer remains to be fully unveiled. This review addresses the current understanding of LRP1B and the studies that shed a light on the LRP1B structure and ligands. It goes further in presenting increasing knowledge brought by technical and methodological advances that allow to better manipulate LRP1B expression in cells and to more thoroughly explore its expression and mutation status. New evidence is pushing towards the increased relevance of LRP1B in cancer as a potential target or translational prognosis and response to therapy biomarker.

Human Papillomavirus Detection by Whole-Genome Next-Generation Sequencing: Importance of Validation and Quality Assurance Procedures

Next-generation sequencing (NGS) yields powerful opportunities for studying human papillomavirus (HPV) genomics for applications in epidemiology, public health, and clinical diagnostics. HPV genotypes, variants, and point mutations can be investigated in clinical materials and described in previously unprecedented detail. However, both the NGS laboratory analysis and bioinformatical approach require numerous steps and checks to ensure robust interpretation of results. Here, we provide a step-by-step review of recommendations for validation and quality assurance procedures of each step in the typical NGS workflow, with a focus on whole-genome sequencing approaches. The use of directed pilots and protocols to ensure optimization of sequencing data yield, followed by curated bioinformatical procedures, is particularly emphasized. Finally, the storage and sharing of data sets are discussed. The development of international standards for quality assurance should be a goal for the HPV NGS community, similar to what has been developed for other areas of sequencing efforts including microbiology and molecular pathology. We thus propose that it is time for NGS to be included in the global efforts on quality assurance and improvement of HPV-based testing and diagnostics.

LRP1B mutation is associated with tumor HPV status and promotes poor disease outcomes with a higher mutation count in HPV-related cervical carcinoma and head & neck squamous cell carcinoma

Human papillomavirus (HPV) infection and gene mutations were reputed as key factors in cervical carcinoma (CC) and head and neck squamous cell carcinoma (HNSCC). However, the associations of HPV status and gene mutations remain to be determined. This study aims to identify molecular patterns of LRP1B mutation and HPV status via rewiring tumor samples of HNSCC (n=1478) and CC (n=178) from the TCGA dataset. Here, we found that LRP1B mutation was associated with HPV status in CC (P=0.040) and HNSCC (P=0.044), especially in HPV 16 integrated CC (P=0.036). Cancer survival analysis demonstrated that samples with LRP1B mutation showed poor disease outcomes in CC (P=0.013) and HNSCC (P=0.0124). In addition, the expression status of LPR1B was more favorable for prediction than TP53 or RB1 in CC and HNSCC. Mutation clustering analysis showed that samples with LRP1B mutation showed higher mutation count in CC (P=1.76e-67) and HNSCC (P<10e-10). Further analysis identified 289 co-occurrence genes in these two cancer types, which were enriched in PI3K signaling, cell division process, and chromosome segregation process, et al. The 289-co-occurrence gene signature identified a cluster of patients with a higher portion of copy number variation (CNV) lost in the genome, different tumor HPV status (P<10e-10), higher mutation count (P<10e-10), higher fraction genome altered value (P=2.078e-4), higher aneuploidy score (P=3.362e-4), and earlier started the smoking year (P=2.572e-4), which were associated with shorter overall survival (P=0.0103) in CC and HNSCC samples. Overall, LRP1B mutation was associated with tumor HPV status and was an unfavorable prognostic biomarker for CC and HNSCC.

Discovery of key genes as novel biomarkers specifically associated with HPV-negative cervical cancer

Cervical cancer is a common female malignancy that is mainly caused by human papillomavirus (HPV) infection. However, the incidence of HPV-negative cervical cancer has shown an increasing trend in recent years. Because the mechanism of HPV-negative cervical cancer development is unclear, this study aims to find the pattern of differential gene expression in HPV-negative cervical cancer and verify the underlying potential mechanism. Differentially expressed genes were compared among HPV-positive cervical cancer, HPV-negative cervical cancer, and normal cervical tissues retrieved from TCGA. Subsequently, dysregulated differentially expressed genes specifically existed in HPV-negative cervical cancer tissues and HPV-negative cell lines were validated by qRT-PCR, western blotting, and immunohistochemical staining. We found seventeen highly expressed genes that were particularly associated with HPV-negative cervical cancer from analysis of TCGA database. Among the 17 novel genes, 7 genes (preferentially expressed antigen in melanoma [PRAME], HMGA2, ETS variant 4 [ETV4], MEX3A, TM7SF2, SLC19A1, and tweety-homologs 3 [TTYH3]) displayed significantly elevated expression in HPV-negative cervical cancer cells and HPV-negative cervical cancer tissues. Additionally, higher expression of MEX3A and TTYH3 was associated with a shorter overall survival of patients with HPV-negative cervical cancer. Our study implies that these seven genes are more likely to provide novel insights into the occurrence and progression of HPV-negative cervical cancer.

HIVID2: an accurate tool to detect virus integrations in the host genome

MOTIVATION

Virus integration in the host genome is frequently reported to be closely associated with many human diseases, and the detection of virus integration is a critically challenging task. However, most existing tools show limited specificity and sensitivity. Therefore, the objective of this study is to develop a method for accurate detection of virus integration into host genomes.

RESULTS

Herein, we report a novel method termed HIVID2 that is a significant upgrade of HIVID. HIVID2 performs a paired-end combination (PE-combination) for potentially integrated reads. The resulting sequences are then remapped onto the reference genomes, and both split and discordant chimeric reads are used to identify accurate integration breakpoints with high confidence. HIVID2 represents a great improvement in specificity and sensitivity, and predicts breakpoints closer to the real integrations, compared with existing methods. The advantage of our method was demonstrated using both simulated and real data sets. HIVID2 uncovered novel integration breakpoints in well-known cervical cancer-related genes, including FHIT and LRP1B, which was verified using protein expression data. In addition, HIVID2 allows the user to decide whether to automatically perform advanced analysis using the identified virus integrations. By analyzing the simulated data and real data tests, we demonstrated that HIVID2 is not only more accurate than HIVID but also better than other existing programs with respect to both sensitivity and specificity. We believe that HIVID2 will help in enhancing future research associated with virus integration.

AVAILABILITY

HIVID2 can be accessed at https://github.com/zengxi-hada/HIVID2/.

CONTACT

Xi Zeng (zengxi@mail.hzau.edu.cn), Linghao Zhao (michael_yifan@126.com).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Accurate Detection of HPV Integration Sites in Cervical Cancer Samples Using the Nanopore MinION Sequencer Without Error Correction

During the carcinogenesis of cervical cancer, the DNA of human papillomavirus (HPV) is frequently integrated into the human genome, which might be a biomarker for the early diagnosis of cervical cancer. Although the detection sensitivity of virus infection status increased significantly through the Illumina sequencing platform, there were still disadvantages remain for further improvement, including the detection accuracy and the complex integrated genome structure identification, etc. Nanopore sequencing has been proven to be a fast yet accurate technique of detecting pathogens in clinical samples with significant longer sequencing length. However, the identification of virus integration sites, especially HPV integration sites was seldom carried out by using nanopore platform. In this study, we evaluated the feasibility of identifying HPV integration sites by nanopore sequencer. Specifically, we re-sequenced the integration sites of a previously published sample by both nanopore and Illumina sequencing. After analyzing the results, three points of conclusions were drawn: first, 13 out of 19 previously published integration sites were found from all three datasets (i.e., nanopore, Illumina, and the published data), indicating a high overlap rate and comparability among the three platforms; second, our pipeline of nanopore and Illumina data identified 66 unique integration sites compared with previous published paper with 13 of them being verified by Sanger sequencing, indicating the higher integration sites detection sensitivity of our results compared with published data; third, we established a pipeline which could be used in HPV integration site detection by nanopore sequencing data without doing error correction analysis. In summary, a new nanopore data analysis method was tested and proved to be reliable in integration sites detection compared with methods of existing Illumina data analysis pipeline with less sequencing data required. It provides a solid evidence and tool to support the potential application of nanopore in virus status identification.