Copy number variations of neurotrophic tyrosine receptor kinase 3 (NTRK3) may predict prognosis of ovarian cancer

A comprehensive analysis of somatic alterations in Chinese ovarian cancer patients

Ovarian cancer is one of the most common cancers in women and is often diagnosed as advanced stage because of the subtle symptoms of early ovarian cancer. To identify the somatic alterations and new biomarkers for the diagnosis and targeted therapy of Chinese ovarian cancer patients, a total of 65 Chinese ovarian cancer patients were enrolled for detection of genomic alterations. The most commonly mutated genes in ovarian cancers were TP53 (86.15%, 56/65), NF1 (13.85%, 9/65), NOTCH3 (10.77%, 7/65), and TERT (10.77%, 7/65). Statistical analysis showed that TP53 and LRP1B mutations were associated with the age of patients, KRAS, TP53, and PTEN mutations were significantly associated with tumor differentiation, and MED12, LRP2, PIK3R2, CCNE1, and LRP1B mutations were significantly associated with high tumor mutational burden. The mutation frequencies of LRP2 and NTRK3 in metastatic ovarian cancers were higher than those in primary tumors, but the difference was not significant (P = 0.072, for both). Molecular characteristics of three patients responding to olapanib supported that BRCA mutation and HRD related mutations is the target of olaparib in platinum sensitive patients. In conclusion we identified the somatic alterations and suggested a group of potential biomarkers for Chinese ovarian cancer patients. Our study provided a basis for further exploration of diagnosis and molecular targeted therapy for Chinese ovarian cancer patients.

Exon Coverage Variations Between Cancer Tissues and Adjacent Non-Cancerous Tissues are Prognostic Factors in Gastric Cancer

Introduction

Gastric cancer is highly heterogeneous both clinically and pathologically and is one of the leading causes of cancer-related deaths worldwide. Genomic coverage variations, also known as copy number variations (CNVs), play a critical role in the carcinogenesis of gastric cancer. Many studies have demonstrated that DNA CNVs are important factors affecting the expression of protein-encoding genes in the gastric cancer genome.

Methods

Thirty gastric cancer patients from a Chinese population were enrolled. Genomic DNA was extracted from gastric cancer tissue and matched adjacent non-cancerous tissue from each patient. A panel of 1,021 genes including 3300 exons was designed and subjected to next-generation sequencing. Copy numbers of each gene and exon were calculated for each tissue. Coverage variations between gastric cancer tissue and matched adjacent non-cancerous tissue were also calculated, and we examined the correlation between overall survival of patients and coverage variation type for each exon.

Results

DNA from cancerous tissue and corresponding adjacent non-cancerous tissue were significantly different with respect to the pattern of gene copy number. Exon copy numbers were highly consistent among non-cancerous samples and confirmed that non-cancerous tissue contain diploid genomes. In contrast, the gene coverage pattern among cancerous tissue showed significant differences and confirmed that gastric cancer is a genetically heterogeneous disease. Numerous exon coverage variations were identified in gastric cancer tissue compared with matched, adjacent non-cancerous tissue. Overall survival between patients with and without coverage variations in regions of NOTCH2, NTRK3, ERBB2 and RERE exons exhibited significant differences. This is consistent with previous reports and indicates that these findings may have prognostic value.

Conclusion

Our results confirm that gastric cancer is a genetically heterogeneous disease. Exon coverage variations between cancer tissue and their adjacent non-cancerous tissue were shown to be associated with prognosis in gastric cancer.

Six-mRNA risk score system and nomogram constructed for patients with ovarian cancer

Platinum is a commonly used drug for the treatment of ovarian cancer (OC). The aim of the current study was to design and construct a risk score system for predicting the prognosis of patients with OC receiving platinum chemotherapy. The mRNA sequencing data and copy number variation (CNV) information (training set) of patients with OC were downloaded from The Cancer Genome Atlas database. A validation set, GSE63885, was obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and CNV genes (DECNs) between platinum-resistant and platinum-sensitive groups were identified using the limma package. The intersection between DEGs and DECNs were selected. Cox regression analysis was used to identify the genes and clinical factors associated with prognosis. Risk score system assessment and nomogram analysis were performed using the survival and rms packages in R. Gene Set Enrichment Analysis was used to identify the enriched pathways in high and low risk score groups. From 1,144 DEGs and 1,864 DECNs, 48 genes that occurred in the two datasets were selected. A total of six independent prognostic genes (T-box transcription factor T, synemin, tektin 5, growth differentiation factor 3, solute carrier family 22 member 3 and calcium voltage-gated channel subunit α1 C) and platinum response status were revealed to be associated with prognosis. Based on the six independent prognostic genes, a risk score system was constructed and assessed. Nomogram analysis revealed that the patients with the sensitive status and low risk scores had an improved prognosis. Furthermore, the current study revealed that the 574 DEGs identified were involved in eight pathways, including chemokine signaling pathway, toll-like receptor signaling pathway, cytokine-cytokine receptor interaction, RIG I like receptor signaling pathway, natural killer cell mediated cytotoxicity, apoptosis, T cell receptor signaling pathway and Fc ε receptor 1 signaling pathway. The six-mRNA risk score system designed in the present study may be used as prognosis predictor in patients with OC, whereas the nomogram may be valuable for identifying patients with OC who may benefit from platinum chemotherapy.

A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer

Background

Over 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening.

Methods

In the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n = 106), endometrial cancer (n = 74), benign ovarian tumors (n = 150) and healthy population controls (n = 399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n = 280), endometrial cancer (n = 228), women with benign ovarian tumors (n = 76) and healthy controls (n = 57).

Results

In the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III-IV with a sensitivity of 0.88 and specificity of 0.92 (AUC = 0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p = 9.56e-22). Also, population controls could be distinguished from ovarian cancer stage III-IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC = 0.89).

Conclusion

The PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination.

Funding

The Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.

Centromere protein U facilitates metastasis of ovarian cancer cells by targeting high mobility group box 2 expression

Ovarian carcinoma is a fatal malignancy in gynecological malignancies, and the prognosis still remains poor due to the lack of effective therapeutic targets. This study demonstrated that centromere protein U (CENPU) was up-regulated in ovarian cancer. The ectopic expression of CENPU in ovarian cancer cells expedited the proliferation, migration and invasion of ovarian cancer cells in vitro. Besides, the over-expression of CENPU markedly advanced the tumorigenicity of ovarian cancer cells in vivo whereas knocked-down CENPU resulted in opposite outcome. In addition, high mobility group box 2 (HMGB2) identified as a down-target of CENPU in ovarian cancer cells was positively correlated with the expression level of CENPU in ovarian cancer tissues. Finally, it was demonstrated that CENPU could enhance the aggressiveness ability of the ovarian cancer cells by regulating HMGB2. This research provided new insight for CENPU, promoted the progression of ovarian cancer and represented a novel target for anti-ovarian cancer therapy.