The ovarian cancer proteome

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Epithelial carcinoma of the ovary is one of the most common gynecologic malignancies and the fifth most frequent cause of cancer death in women. 50% of all ovarian cancers are diagnosed in women older than 65 years of age. Approximately 5 to 10% of ovarian cancers are familial.

Ovarian cancer is typically denoted as a silent cancer since symptoms occur late in the course of the disease. A majority of ovarian epithelial cancers are diagnosed during or after abdominal exploration to investigate a pelvic or abdominal mass detected on physical examination. By the time of discovery, approximately 70% of the tumors have spread beyond the ovary and are in such cases rarely curable by surgical resection or surgery combined with postoperative chemotherapy and/or radiation therapy. The dismal prognosis has stimulated research efforts for early detection of ovarian cancer.

Ovarian epithelial cancer is bilateral (involving both ovaries) in one-third to one-half of the cases. The FIGO (International Federation of Gynaecology and Obstetrics) staging system recognizes four stages for ovarian cancer. Patients with Stage I tumors have a 5-year survival of 80%, while the 5-year survival of Stage IV patients is merely 8%.

Here, we explore the ovarian cancer proteome using TCGA transcriptomics data and antibody based protein data. 507 genes are suggested as prognostic based on transcriptomics data from 373 patients; 151 genes associated with unfavourable prognosis and 356 genes associated with favourable prognosis.

TCGA data analysis

In this metadata study we used data from TCGA where transcriptomics data was available from 373 females with ovarian serous cystadenocarcinoma. 143 of the patients were still alive at the time of data collection. Information on stage distribution was missing.

Unfavourable prognostic genes in ovarian cancer

For unfavourable genes, higher relative expression levels at diagnosis gives significantly lower overall survival for the patients. There are 151 genes associated with unfavourable prognosis in ovarian cancer. In Table 1, the top 20 most significant genes related to unfavourable prognosis are listed.

KRT7 is a gene associated with unfavourable prognosis in ovarian cancer. The best separation is achieved by an expression cutoff at 181.1 fpkm which divides the patients into two groups with 16% 5-year survival for patients with high expression versus 38% for patients with low expression, p-value: 9.42e-5. Immunohistochemical staining using an antibody targeting KRT7 (CAB000028) shows differential expression pattern in ovarian cancer samples.

MRC2 is another gene associated with unfavourable prognosis in ovarian cancer. The best separation is achieved by an expression cutoff at 23.6 fpkm which divides the patients into two groups with 22% 5-year survival for patients with high expression versus 34% for patients with low expression, p-value: 1.68e-4. Immunohistochemical staining using an antibody targeting MRC2 (HPA041991) shows differential expression pattern in ovarian cancer samples.

Favourable prognostic genes in ovarian cancer

For favourable genes, higher relative expression levels at diagnosis gives significantly higher overall survival for the patients. There are 356 genes associated with favourable prognosis in ovarian cancer. In Table 2, the top 20 most significant genes related to favourable prognosis are listed.

NOL7 is a gene associated with favourable prognosis in ovarian cancer. The best separation is achieved by an expression cutoff at 28.6 fpkm which divides the patients into two groups with 41% 5-year survival for patients with high expression versus 19% for patients with low expression, p-value: 3.64e-5. Immunohistochemical staining using an antibody targeting NOL7 (HPA029185) shows differential expression pattern in ovarian cancer samples.

TERF2IP is a another gene associated with favourable prognosis in ovarian cancer. The best separation is achieved by an expression cutoff at 12.0 fpkm which divides the patients into two groups with 38% 5-year survival for patients with high expression versus 16% for patients with low expression, p-value: 6.14e-5. Immunohistochemical staining using an antibody targeting TERF2IP (CAB018660) shows differential expression pattern in ovarian cancer samples.

The ovarian cancer transcriptome

The transcriptome analysis shows that 72% (n=14034) of all human genes (n=19571) are expressed in ovarian cancer. All genes were classified according to the ovarian cancer-specific expression into one of five different categories, based on the ratio between mRNA levels in ovarian cancer compared to the mRNA levels in the other 16 analyzed cancer tissues. 150 genes show some level of elevated expression in ovarian cancer compared to other cancers (Figure 1). The elevated category is further subdivided into three categories as shown in Table 3.

Figure 1. The distribution of all genes across the five categories based on transcript abundance in ovarian cancer as well as in all other cancer tissues.

Additional information

Ovarian epithelial cancers are classified into serous, mucinous, endometrioid, clear cell, transitional cell, squamous cell, mixed epithelial and undifferentiated categories depending on histomorphologic features. The most common forms include sero-papillary, mucinous and endometrioid subtypes. Several histologic grading systems have been proposed with the WHO system being widely employed. Grade 1 (well-differentiated) endometrial cancers show less than 5% of solid tumor growth pattern (without lumen formation) and uniform oval nuclei with evenly dispersed chromatin. In Grade 3 (poorly differentiated) cancers more than 50% of the tumor is composed of solid tumor cell masses and tumor cell nuclei show coarse chromatin and prominent nucleoli. In Grade 2 cancers, between 6-50% of the tumor is composed of solid masses and nuclei display intermediate features compared to Grade 1 and Grade 3 cancers.

Relevant links and publications

Uhlen M et al, 2017. A pathology atlas of the human cancer transcriptome. Science.
PubMed: 28818916 DOI: 10.1126/science.aan2507

Cancer Genome Atlas Research Network et al, 2013. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet.
PubMed: 24071849 DOI: 10.1038/ng.2764

Uhlén M et al, 2015. Tissue-based map of the human proteome. Science
PubMed: 25613900 DOI: 10.1126/science.1260419

Histology dictionary - Ovarian cancer