Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

Whole-Exome Sequencing Could Distinguish Primary Pulmonary Squamous Cell Carcinoma From Lung Metastases in Individuals With Cervical Squamous Cell Carcinoma

Aims: Metastatic cervical carcinoma is hard to cure using traditional treatment and new therapeutic approaches are needed. However, the process of clonal evolution and the molecular alterations that contribute to tumor progression from primary to metastatic carcinoma remain unclear. It is currently difficult to distinguish between the primary pulmonary squamous cell carcinoma (PPSCC) and metastatic cervical squamous cell carcinoma (CSCC). Methods: Paired primary CSCC and lung/lymph nodes metastatic lesions from eight patients were analyzed by whole-exome sequencing (WES). WES data of matched specimens and normal samples were aligned to the human reference genome and analyzed to identify somatic mutations in primary and metastatic lesions. Results: A total of 1,254 somatic variants were identified. All the primary lesions and metastatic lesions shared mutations, the percentage of shared mutations between primary lesions and corresponding metastatic lesions varied significantly, ranging from 6% to 70%. In other words, all the metastatic lesions are clonally related to primary lesions, confirming WES could prove they are metastatic from the cervix but not PPSCC. We tried to apply a gene panel to help distinguish PPSCC and metastatic CSCC but failed because the mutations were widely distributed in CSCC. Interestingly, lymph nodes metastasis (LNM) harbored fewer cancer driver mutations than primary CSCC specimens with a significant difference. Besides this, there was no significant difference in somatic mutations and copy number variation (CNV) between primary and metastatic CSCC. Conclusion: Our data demonstrate that WES is an additional helpful tool in distinguishing PPSCC and metastatic CSCC, especially for certain difficult cases.

Identification of Potential Driver Genes Based on Multi-Genomic Data in Cervical Cancer

Background: Cervical cancer became the third most common cancer among women, and genome characterization of cervical cancer patients has revealed the extensive complexity of molecular alterations. However, identifying driver mutation and depicting molecular classification in cervical cancer remain a challenge.

Methods: We performed an integrative multi-platform analysis of a cervical cancer cohort from The Cancer Genome Atlas (TCGA) based on 284 clinical cases and identified the driver genes and possible molecular classification of cervical cancer.

Results: Multi-platform integration showed that cervical cancer exhibited a wide range of mutation. The top 10 mutated genes were TTN, PIK3CA, MUC4, KMT2C, MUC16, KMT2D, SYNE1, FLG, DST, and EP300, with a mutation rate from 12 to 33%. Applying GISTIC to detect copy number variation (CNV), the most frequent chromosome arm-level CNVs included losses in 4p, 11p, and 11q and gains in 20q, 3q, and 1q. Then, we performed unsupervised consensus clustering of tumor CNV profiles and methylation profiles and detected four statistically significant expression subtypes. Finally, by combining the multidimensional datasets, we identified 10 potential driver genes, including GPR107, CHRNA5, ZBTB20, Rb1, NCAPH2, SCA1, SLC25A5, RBPMS, DDX3X, and H2BFM.

Conclusions: This comprehensive analysis described the genetic characteristic of cervical cancer and identified novel driver genes in cervical cancer. These results provide insight into developing precision treatment in cervical cancer.

Genomic and transcriptomic characterization of the human glioblastoma cell line AHOL1

Cancer cell lines are widely used as in vitro models of tumorigenesis, facilitating fundamental discoveries in cancer biology and translational medicine. Currently, there are few options for glioblastoma (GBM) treatment and limited in vitro models with accurate genomic and transcriptomic characterization. Here, a detailed characterization of a new GBM cell line, namely AHOL1, was conducted in order to fully characterize its molecular composition based on its karyotype, copy number alteration (CNA), and transcriptome profiling, followed by the validation of key elements associated with GBM tumorigenesis. Large numbers of CNAs and differentially expressed genes (DEGs) were identified. CNAs were distributed throughout the genome, including gains at Xq11.1-q28, Xp22.33-p11.1, Xq21.1-q21.33, 4p15.1-p14, 8q23.2-q23.3 and losses at Yq11.21-q12, Yp11.31-p11.2, and 15q11.1-q11.2 positions. Nine druggable genes were identified, including HCRTR2, ETV1, PTPRD, PRKX, STS, RPS6KA6, ZFY, USP9Y, and KDM5D. By integrating DEGs and CNAs, we identified 57 overlapping genes enriched in fourteen pathways. Altered expression of several cancer-related candidates found in the DEGs-CNA dataset was confirmed by RT-qPCR. Taken together, this first comprehensive genomic and transcriptomic landscape of AHOL1 provides unique resources for further studies and identifies several druggable targets that may be useful for therapeutics and biologic and molecular investigation of GBM.

Identification of driver genes regulating immune cell infiltration in cervical cancer by multiple omics integration

Cervical cancer (CC) is one of the most common cancers in women. However, copy number alteration (CNA)-driven dysregulated genes and their functions in CC are still rarely investigated. In the present study, we conducted integrative analysis of CNA and gene expression data from The Cancer Genome Atlas (TCGA) cervical cancer to identify dysregulated genes triggered by CNAs. The integration of copy number status and RNA expression revealed 763 amplified and 1,391 deleted genes significantly dysregulated by the CNAs (P-value < 1e-8). Among these CNA genes, five driver genes, including PI3KCA, PI3KCB, DVL3, WWTR1, and ERBB2, exhibited a strong association with immune cell infiltration, suggesting that the pathways that they participate in may be involved in regulating immune cell infiltration. Moreover, we also observed that the genes of immunotherapeutic targets were abundantly expressed in the wild-type samples, suggesting that immunotherapy based on these immunotherapeutic targets may be applied to wild-type samples. In addition, the two CNA driver genes, DVL3 and ERBB2, might be sensitive and resistant biomarkers for examining the tumor's response to chemoradiotherapy, respectively. Particularly, the expression of ERBB2 was also observed to be higher in responders of chemotherapy than non-responders. Furthermore, a subset of CNA genes was identified to predict the prognosis of cervical cancer. In summary, our systematic data analysis of these CNA genes not only improved our understanding of the veiled mechanism behind immune cell infiltration, but also provided the potential clinical application of these CNA genes in cervical cancer.

The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome

Aneuploidy, the unbalanced state of the chromosome content, represents a hallmark of most solid tumors, including colorectal cancer. Such aneuploidies result in tumor specific genomic imbalances, which emerge in premalignant precursor lesions. Moreover, increasing levels of chromosomal instability have been observed in adenocarcinomas and are maintained in distant metastases. A number of studies have systematically integrated copy number alterations with gene expression changes in primary carcinomas, cell lines, and experimental models of aneuploidy. In fact, chromosomal aneuploidies target a number of genes conferring a selective advantage for the metabolism of the cancer cell. Copy number alterations not only have a positive correlation with expression changes of the majority of genes on the altered genomic segment, but also have effects on the transcriptional levels of genes genome-wide. Finally, copy number alterations have been associated with disease outcome; nevertheless, the translational applicability in clinical practice requires further studies. Here, we (i) review the spectrum of genetic alterations that lead to colorectal cancer, (ii) describe the most frequent copy number alterations at different stages of colorectal carcinogenesis, (iii) exemplify their positive correlation with gene expression levels, and (iv) discuss copy number alterations that are potentially involved in disease outcome of individual patients.

The high-risk HPV oncogene E7 upregulates miR-182 expression through the TGF-β/Smad pathway in cervical cancer

Accumulating experimental evidence has shown that the aberrant expression of microRNAs (miRNAs) is involved in the development and progression of human cervical cancer. Previously, we identified miR-182 as an oncomiRNA in cervical cancer. However, the mechanism by which miR-182 is regulated and the interaction between human papillomavirus (HPV) and miR-182 in cervical cancer development remains unknown. In the present study, we explored the link between HPV E7 and miR-182 and verified that high-risk HPV E7 upregulated miR-182 expression through TGF-β/Smad4 signaling pathway in cervical cancer. By contrast, low-risk HPV E7 did not affect the expression of TGF-β and miR-182. Mechanistically, as high-risk HPV E7 bound to pRb, E2F was released from the complex and bound to the TGF-β promoter region, resulting in TGF-β overexpression. Furthermore, the Smad4 signaling pathway was activated upon TGF-β overexpression, which led to an interaction between Smad4 and the miR-182 promoter region, subsequently inducing the upregulation of miR-182 in both cervical cancer cells and the surrounding normal cells. In conclusion, this newly identified high-risk HPV E7/TGF-β/miR-182 regulatory network might inform the development of specific therapeutic strategies for cervical cancer.