Abstract. Cohesins and cohesin-regulated genes are deregulated in numerous types of human cancer. However, data concerning their status and role in endometrial cancer are scarce. This study aimed to determine the clinical significance of double-strand-break repair protein rad21 homolog (RAD21) and runt-related transcription factor 1 (RUNX1) gene dosage and mRNA expression in endometrial cancer. RAD21 is a component of the cohesin complex, crucial for chromosome segregation and DNA repair. RUNX1 is the transcription factor implicated in RAD21 regulation. The study group included 144 endometrial cancer patients. RAD21 and RUNX1 expression profiles were measured by reverse-transcription quantitative PCR. RAD21 gene dosage was determined by quantitative PCR. RAD21 gene dosage was associated with RAD21 mRNA expression (ρ=0.22; p=0.009). Furthermore, RAD21 expression strongly correlated with RUNX1 expression (ρ=0.43; p<0.0000001). Increased RAD21 gene dosage correlated with more advanced tumor stage (p=0.021), higher grade (p= 0.021), cervical involvement (p= 0.01) and the absence of obesity (p=0.025), while RAD21 mRNA expression correlatd with cervical involvement (p=0.027). The mRNA expression of RAD21 and RUNX1 was found to be deregulated and co-dependent in endometrial cancer. RAD21 gene dosage is associated with unfavorable tumor characteristics. However, elucidating the role of these molecular markers in endometrial oncogenesis requires further investigation, including functional studies and survival analysis.

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Liquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumoreducated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene.Biological knowledge from the Kyoto Encyclopedia of Genes and Genomes was also implemented to improve accuracy. Images obtained from samples can then be compared against standard images for specific cancers to determine a diagnosis. We tested imPlatelet on a cohort of 401 non-small cell lung cancer patients, 62 sarcoma patients and 28 ovarian cancer patients. imPlatelet provided excellent discrimination between lung cancer cases and healthy controls, with accuracy equal to 1 in the independent dataset. When discriminating between non-cancer cases and sarcoma or ovarian cancer patients, accuracy equaled 0.91 or 0.95, respectively, in the independent datasets. According to our knowledge, this is the first study implementing an imagebased deep-learning approach combined with biological knowledge to classify human samples.The performance of imPlatelet considerably exceeds previously published methods and our own alternative attempts of sample discrimination. We show that the deep-learning image-based classifier accurately identifies cancer, even when a limited number of samples is available.

Intratumor heterogeneity implies heterogeneous protein function, facilitating tumor adaptation which results in therapeutic failure. We hypothesized that tumor heterogeneity at protein level may influence the course of the disease. As a single biopsy might not represent the full biologic complexity of the tumor, we have analyzed immunohistochemically four different cores obtained from each primary tumor within the cohort of 364 patients with endometrial cancer (EC). The following proteins were examined: estrogen receptor 1 (ESR1), progesterone receptor, epidermal growth factor receptor, v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, receptor tyrosine-protein kinase erbB-3, v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 4, phosphatidylinositol-4,5-bisphosphate 3-kinase, phosphorylated v-akt murine thymoma viral oncogene homolog 1, v-myc avian myelocytomatosis viral oncogene homolog, DNA topoisomerase II alpha 170 kDa (TOP2A), cyclin-dependent kinase inhibitor 2A (CDKN2A), tumor protein p53, RAD21 homolog, S. pombe, and runt-related transcription factor 1. Particularly strong correlation was found between TOP2A and CDKN2A heterogeneity and higher stage of the disease (P = .0002 and P = .0003, respectively). Most correlations with clinicopathologic data were observed for ESR1 heterogeneity that correlated with non-endometrioid carcinomas (P=.02), higher stage (P=.005), grade (P=.01), and the presence of metastases (P = .01). Thirty-nine (11.0%) patients were classified as “globally heterogeneous”. Cumulative tumor heterogeneity strongly correlated with the presence of metastases, higher stage, and higher grade of the disease (all P b .05). It also carried negative prognostic value (P=.0008). We show that the degree of heterogeneity in EC might serve as a clinically valid molecular marker.

Our data do not confirm the role of HOTAIR in EMT-mediated CSC formation in EC. Neither does the diversity of EC molecular subtypes influence these processes. But HOTAIR expression could serve as an independent prognostic factor in EC. The clinical importance of the above discoveries requires further studies.