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Page 4 of 38 J Cancer Metastasis Treat 2020;6:5 I http://dx.doi.org/10.20517/2394-4722.2020.13

analysis of patients with benign tumors and ovarian cancer to construct an early detection model of ovarian
cancer. Gene expression data from TCGA database have been analyzed using the deep neural network
model to develop a model for predicting platinum-sensitivity in high-grade serous ovarian cancer. Lastly,
we integrated clinico-pathologic and multi-omics data to reveal multiple factors associated with ovarian
cancer progression.

4. Genetic and epigenetic regulation of therapy resistance in ovarian cancer by long non-
coding RNAs

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Danny N. Dhanasekaran , Ji Hee Ha , Ranagasudhagar Radhakrishanan , Muralidharan
1
Jayaraman , Ciro Isidoro , Yong Sang Song 3
2
1 Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA.
2 Università del Piemonte Orientale, Novara 28100, Italy.
3 Seoul National University, Seoul 03080, Korea.

Background and aim: Ovarian cancer remains the most fatal gynecological cancer in the world, with a five-
year survival rate of only 46% for the localized disease and 29% for the distant-stage disease. With the
recent analysis of cancer genome, long non-coding RNAs (lncRNAs) are emerging as critical players in the
pathobiology of many cancers, thus identifying them as new genomic targets for precision cancer medicine.
Therefore, we sought to identify the critical lncRNA(s) involved in ovarian cancer genesis, progression,
therapy resistance, and disease recurrence.

Experimental procedure: To identify the lncRNAs critically involved in ovarian cancers, we carried out a
global analysis of mRNAs as well as lncRNAs that are differentially expressed in patient-derived ovarian
cancer cells, using a series of biased and unbiased transcriptome analyses.

Results: The results indicate 1351 lncRNAs and 1591 mRNAs were significantly dysregulated in patient-
derived cancer cells compared to normal fallopian tube-derived epithelial control cells. Co-expression
network analysis of coding and noncoding RNAs identified the etiological role for several, thus far,
unidentified lncRNAs and mRNAs in ovarian cancer. Further analyses indicated that the lncRNA-regulated
gene expression network in ovarian cancer involves both genetic and epigenetic mechanisms.

Conclusion: Our findings with representative lncRNAs indicate that they can serve as a novel diagnostic
as well as prognostic biomarkers. In addition, the findings that the silencing of specific lncRNAs inhibits
xenograft tumor growth identify them as new therapeutic targets in ovarian cancer.

5. Radiotherapy and immunotherapy promote tumoral lipid oxidation and ferroptosis

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Michael Green , Weimin Wang , Xueting Lang , Jiali Yu , Jae Eun Choi , Ilona Kryczek , Everett
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2
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Stone , George Georgiou , Marcin Cieslik , Daniel Wahl , Meredith Morgan , Arul Chinnaiyan ,
Theodore Lawrence , Weiping Zou 1
1
1 University of Michigan, Ann Arbor, MI 48104, USA.
2 University of Texas, Austin, TX 78712, USA.
Background and aim: Cancer immunotherapy restores or enhances the effector function of CD8+ T cells
in the tumor microenvironment. Radiotherapy can indirectly stimulate CD8+ T cell function through
innate immune signaling. Direct connections between radiotherapy and adaptive CD8+ T cell function