Open Access

Genomic markers of ovarian adenocarcinoma and its relevancy to the effectiveness of chemotherapy

  • Authors:
    • Monika Englert‑Golon
    • Bartosz Burchardt
    • Bartlomiej Budny
    • Szymon Dębicki
    • Blanka Majchrzycka
    • Elzbieta Wrotkowska
    • Piotr Jasiński
    • Katarzyna Ziemnicka
    • Radosław Słopień
    • Marek Ruchała
    • Stefan Sajdak
  • View Affiliations

  • Published online on: July 17, 2017     https://doi.org/10.3892/ol.2017.6590
  • Pages:3401-3414
  • Copyright: © Englert‑Golon et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Ovarian cancer is the eighth most common cancer and the seventh highest cause of cancer‑associated mortality in women worldwide. It is the second highest cause of mortality among female reproductive malignancies. The current standard first‑line treatment for advanced ovarian cancer includes a combination of surgical debulking and standard systemic platinum‑based chemotherapy with carboplatin and paclitaxel. Although a deeper understanding of this disease has been attained, relapse occurs in 70% of patients 18 months subsequent to the first‑line treatment. Therefore, it is crucial to develop a novel drug that effectively affects ovarian cancer, particularly tumors that are resistant to current chemotherapy. The aim of the present study was to identify genes whose expression may be used to predict survival time or prognosis in ovarian cancer patients treated with chemotherapy. Gene or protein expression is an important issue in chemoresistance and survival prediction in ovarian cancer. In the present study, the research group consisted of patients treated at the Surgical Clinic of the Gynecology and Obstetrics Gynecological Clinical Hospital, Poznan University of Medical Sciences (Poznan, Poland) between May 2006 and November 2014. Additional eligibility criteria were a similar severity (International Federation of Gynecolgy and Obstetrics stage III) at the time of diagnosis, treatment undertaken in accordance with the same schedule, and an extremely good response to treatment or a lack of response to treatment. The performance of the OncoScan® assay was evaluated by running the assay on samples obtained from the four patients and by following the recommended protocol outlined in the OncoScan assay manual. The genomic screening using Affymetrix OncoScan Arrays resulted in the identification of large genomic rearrangements across all cancer tissues. In general, chromosome number changes were detected in all examined tissues. The OncoScan arrays enabled the identification of ~100 common somatic mutations. Chemotherapy response in ovarian cancer is extremely complex and challenging to study. The present study identified specific genetic alterations associated with ovarian cancer, but not with response for treatment.

Introduction

Ovarian cancer is the eighth most common cancer and the seventh leading cause of cancer-associated mortality in women worldwide. It is the second highest cause of mortality among female reproductive malignancies and accounts for 140,200 mortalities each year. The estimated incidence and number of mortalities in the USA from ovarian cancer is 21,980 cases and 14,270 mortalities, respectively, for 2014 (1,2). Ovarian cancer is the fourth most common malignancy in women and is the leading cause of gynecological cancer-associated mortality. Poland is one of the countries with high morbidity rates for ovarian carcinoma. Epidemiological data show steady rise of ovarian cancer incidence. Due to late-onset symptoms, ovarian cancer is mainly diagnosed in an advanced stage. In total, 60–70% of patients present with stage III or IV disease and are therefore associated with poor survival. The International Federation of Gynecology and Obstetrics (FIGO) staging classification in ovarian cancer has an independent prognostic role. The major role of the staging system is not only to provide universal terminology that may be used in different oncological hospitals worldwide, but it also informs us about the prognosis and outcome prediction subsequent to specific treatment. The majority of ovarian cancer patients are diagnosed with late-stage disease as the asymptomatic progression is poorly understood, and an efficient screening strategy is not presently available (35). The current standard first-line treatment for advanced ovarian cancer includes a combination of surgical debunking and standard systemic platinum-based chemotherapy with carboplatin and paclitaxel (6,7). This standard treatment results in >80% response rates and 40–60% complete responses; however, the majority of patients with advanced disease (stages III–IV) will eventually relapse, even with initial disease response. Improvement in survival has also been poor in ovarian cancer. Gene expression-based tools for the prediction of patient prognosis subsequent to surgery or chemotherapy are currently available for certain cancers. The prediction of cancer prognosis using molecular signatures is a popular research field, within which a wide variety of approaches have been considered (7). Popular RNA or protein expression measurement techniques include cDNA hybridization microarrays, end-point and quantitative reverse transcription polymerase chain reaction (PCR), and immunohistochemistry approaches (8). Although a deeper understanding of this disease has been attained, relapse continues to occur in 70% of patients 18 months following the first-line treatment. Therefore, it is crucial to develop a novel drug that effectively impacts on ovarian cancer, particularly one that is resistant to current chemotherapy. The 5-year survival rate of ovarian cancer patients with stage I is 92%. However, patients diagnosed in the late stage have poor prognosis, with a 5-year survival rate of only 19% for stage IV patients. The median progression-free survival time ranges between 16 and 21 months, and the median overall survival time ranges between 24 and 60 months (9,10). Subsequent to repeated cycles of chemotherapy, recurrent ovarian cancer eventually develops resistance to numerous available cytotoxic agents. As a result, studies into the mechanisms of drug-resistance, biomarkers for drug resistance, and the development of new-targeted therapies have been the subject of numerous ovarian cancer studies (11). Although patients receiving standard therapy, including surgical cytoreduction and platinum-based combination chemotherapies, may have an initial favorable response, the majority of patients experience relapse within 5 years (12). Consequently, there is an urgent requirement for novel treatments for this deadly disease.

The aim of the present study was to identify genes of which the expression may be used to predict survival time or prognosis in ovarian cancer patients treated witch chemotherapy. As aforementioned, the presence of resistance to the chemotherapy agent administered dramatically affects the survival of a patient. It is therefore reasonable to expect the gene signatures identified to include genes responsible for chemoresistance, which will affect the mechanism of action of the drug. Gene or protein expression is an important issue of chemoresistance and survival prediction in ovarian cancer. The concept of identifying gene signatures is popular, but requires careful handling to extract the information required for this to be successful. There are certain previous studies that investigated the differing response of different types of ovarian cancer to chemotherapy (13). Identification of biomarkers that can reliably predict drug sensitivity and resistance is extremely important.

Materials and methods

In the present study, the research group consisted of patients treated at the Surgical Clinic of the Gynecology and Obstetrics Gynecological Clinical Hospital, Poznan University of Medical Sciences (Poznan, Poland) between May 2006 and November 2014. Of the 2,000 patients, four who suffered from ovarian serum carcinoma were chosen. Additional eligibility criteria were a similar severity (FIGO stage IIIC) at the time of diagnosis, treatment undertaken in accordance with the same schedule, and an extremely good response to treatment or a lack of response to treatment. Finally, two patients who had an exceptionally good response to treatment and two patients who did not respond to treatment were selected. A detailed description of the therapeutic effects of the patients enrolled in the present study is subsequently reported. Informed consent was obtained from all patients, and ethical approval was provided by the Bioethics Committee of Poznan University of Medical Sciences.

The tissue samples were collected from neoplastic lesions removed during surgery prior to starting drug therapy. The tissues were stored in paraffin blocks.

Case reports
Case 1

Patient 1 (48 years of age) was classified as having a good response to treatment. The patient was referred from a gynecological ward of Gniezno County Hospital (Gniezo, Poland) in October 2007 with a suspected neoplastic process that extended from the ovary, for treatment at the. Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital (Poznan, Poland). On admission, vaginal and transabdominal ultrasounds were performed, which showed conglomerate tumors occupying the pelvis. This ovarian tumor had the following dimensions, 7×8 and 6×5.9 cm infiltrated the large intestine (descending colon and anus) and bladder. The level of the marker cancer antigen (CA) 125 was 207 IU/ml in the blood (normal reference values are <35 IU ml). Subsequent to preparation, partial excision of the pelvic tumor, with reconstruction of the walls of the bladder and anastomosis of the proximal descending colon and the rectum was performed. Unfortunately, due to infiltration of the tumor into the left iliac vessels, the whole tumor was not removed Subsequent to a period of recuperation in November 2007, treatment was commenced with first-line chemotherapy, consisting of paclitaxel and cisplatin (intravenous infusion of paclitaxel 175 mg/m2 and 75 mg/m2 cisplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles) which lasted continuously until February 2008. At the start of this stage of treatment, a lesion in the vicinity of the left iliac vessels were visible on transvaginal ultrasound, 1.0×0.7 cm in size, while the CA125 level was 50 IU/ml in the blood. Subsequent to a cycle of paclitaxel and cisplatin chemotherapy (intravenous infusion of paclitaxel 175 mg/m2 and 75 mg/m2 cisplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles.), this lesion was invisible and the CA125 level was 13 IU/ml in the blood. At a follow-up in late April 2008, ultrasound examinations found recurrence in the vicinity of the left iliac vessels, with a dimension of 4×4×5 cm and the patient was admitted to the oncology clinic of the Gynecology and Obstetrics Gynecological Clinical Hospital (Poznan, Poland). It was decided to perform surgery to remove the lesion. Considering the high infiltration of the left iliac vessels and subsequent to consultation with a vascular surgeon, the lesion was not entirely removed, leaving a fragment of a tumor measuring ~0.5×0.5 cm around the left common iliac artery. The next stage of treatment was second-line chemotherapy consisting of cyclophosphamide and cisplatin (intravenous infusion of cyclophosphamide 750 mg/m2 and 75 mg/m2 cisplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles, which started at the end of May 2008. However, subsequent to 2 cycles of chemotherapy, the patient had a strong anaphylactic reaction to the chemotherapy, which resulted in a change to topotecan (to 1.5 mg/m2 for 5 days every 3 weeks). The level of CA125 (7 IU/ml) in the blood had decreased to 3 IU/ml at the end of therapy, the baseline was following completion of the topotecan treatment. Chemotherapy was completed in late October/November 2008, with the ultrasound also revealing no pelvic lesions; it was decided to continue treatment on an outpatient basis, with one follow-up every 3 weeks. During a follow-up in late December 2008, a recurrence 7×5×5 cm in size was observed around the left iliac vessels. In addition, the patient experienced deterioration in general condition, including a lack of appetite, weakness and weight loss (12 kg within 7 weeks). At the request of the patient, further treatment was not commenced, and it was decided in consultation with the patient for palliative care to be administered at their place of residence. The patient succumbed in mid-January 2009. At the request of the family, no autopsy was performed.

Case 2

Patient 2 (50 years of age) was classified as having a good response to treatment. The patient presented to the gynecological clinic of the local hospital in Kościan (Kościan County Hospital) in February 2009 subsequent to the accidental detection of a polycystic solid tumor in the pelvic cavity, posterior to the uterus, during abdominal ultrasound. The patient was urgently admitted to the Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital in March 2009 and a transvaginal ultrasonography revealed a tumor 9×5×5 cm in size that was in contact with the ascending colon and bladder. The patient reported a history of partial hysterectomy in July 2007. The CA125 level in the blood was 175 IU/ml. Subsequent to preparation, surgery was performed to remove the lesions originating from the right ovary, with the macroscopically unchanged left ovary. Following a period of recovery, first-line chemotherapy consisting of paclitaxel and carboplatin (6 cycles intravenous infusion of paclitaxel, 175 mg/m2 lasting 3 h, followed by 400 mg/m2 carboplatin per cycle, with 3 weeks between cycles.) was commenced in mid-April 2009. Throughout the administration of chemotherapy, there were no lesions in the pelvic cavity and the level of the marker CA125 in the blood dropped between 40 IU/ml at the start of chemotherapy and 13 IU/ml at its completion. In the period between September 2009 and February 2013, the patient was admitted to the Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital. In March 2013 during a routine follow-up, a pelvic lesion 7×10×5 cm in size was identified in the right ovary. The patient was admitted to the clinic in order to perform surgery to remove the lesion. The CA125 level was 51 IU/ml. Underwent radical changes and the removal of deciding to start at the beginning of March 2013 chemotherapy (3 cycles of intravenous infusion of paclitaxel 175 mg/m2 and carboplatin 400 mg/m2 per cycle lasting 3 h with 3 weeks break between chemotherapy cycles). During the third course of chemotherapy, the patient developed an adverse reaction to carboplatin (palmar-plantar erythrodysesthesia) that resulted in carboplatin being replaced by cisplatin (3 cycles of intravenous infusion of 75 mg/m2 cisplatin per cycle; 3 weeks break between chemotherapy cycles). Chemotherapy was completed in August 2014, and the patient was referred for follow-up. The last follow-up took place in October 2014. No lesions were detected in the pelvic cavity and the level of CA125 in the blood was 10 IU/ml. The patient succumbed to cardiogenic shock in mid-December 2014. At the request of the family, no autopsy was performed.

Case 3

Patient 3 (49 years of age) was classified as being unresponsive to treatment. In October 2009, the patient was admitted to the Department of Gynecology, Konin district hospital (Konin, Poland) due to a pelvic tumor. On admission to the Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital, transvaginal ultrasonography revealed a solid lesion with multiple compartments that filled the entire pelvis, with smaller dimensions totaling 12×10×17 cm. The tumor infiltrated the bladder and bowel. There was no point in time at which the point where the cancer lesion came from could be reached. The level of CA125 in the blood was 156 IU/ml. Subsequent to preparation, non-radical resection of the tumor was performed, including the uterus and ovaries, a fragment of the wall of the bladder and a section of the descending colon. Among the surgically reconstructed section, colon end-to-side colon anastomosis was performed. However, a small residual section infiltrating the jejunum was left. Following a period of recuperation in mid-November 2009, first-line chemotherapy consisting of paclitaxel and carboplatin (6 cycles of intravenous infusion of paclitaxel 175 mg/m2 and 400 mg/m2 carboplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles) was commenced. During the examination prior to the first treatment cycle, lesions were detected in the pelvis and the blood CA125 level was 21 IU/ml. Following 3 cycles of chemotherapy, pelvic free fluid appeared, and the amount of fluid increased in the following cycle. Prior to the last cycle of (February 2010) chemotherapy, a lesion that involved the bladder wall, 2×2×3 cm in size, was observed during the ultrasound. Due to the poor condition and increasing shortness of breath of the patient, the peritoneal cavity was punctured, and over 3 days, 5 l of fluid were removed. Subsequent to another week of hospitalization and further deterioration in the general condition of the patient, further treatment was not administered at the patient's request, and the patient was discharged. Palliative care was administered between discharge (beginning of April 2010) and early June 2010, when the patient succumbed to ovarian cancer.

Case 4

Patient 4 (49 years of age) was classified as being unresponsive to treatment. In November 2010, the patient was referred to Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital by a physician, due to the detection of bilateral ovarian tumors by screening ultrasound. On admission, transvaginal ultrasound was performed, and a solid tumor with central vascularization, measuring 2×1×2 cm, was identified in the left ovary, and a multi-element solid tumor located centrally with peripheral vasculature, measuring 4×3×5 cm, was identified in the right ovary. The level of CA125 in the blood was 410 IU/ml. A radical hysterectomy with removal of the two ovaries, tumors and lymph nodes was performed. Following a period of recovery, first-line chemotherapy consisting of carboplatin and paclitaxel (6 cycles of intravenous infusion of paclitaxel 175 mg/m2 and 400 mg/m2 carboplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles) was commenced in mid-December 2010. At the starting of chemotherapy, the CA125 level in the blood was 47 IU/ml, and subsequent to the completion of chemotherapy, it was 46 IU/ml. In May 2011, subsequent to finishing the whole course of treatment, the patient was referred to the Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital for follow-up. In June 2011, ultrasound examinations observed a lesion 2×2×0.5 cm in size, which gradually widened (between December 2010 and May 2011) to 7×10×6 cm in size. There was also an increase in the level of CA125 in the blood to 211 IU/ml in February 2013. The patient did not agree to the proposed hospitalizations and surgical procedures. In February 2013, a painful lump 2×2 cm in size was observed in the postoperative scar. Subsequent to obtaining consent from the patient to perform the surgery, a localized lesion in the vagina was removed. In addition, a partly invasive bladder recurrence was removed by local resection of the bladder wall, and a tumor located in the subcutaneous tissue, which was identified as metastasis, was also removed. Following a period of recuperation, second-line chemotherapy consisting of paclitaxel and carboplatin (6 cycles of intravenous infusion of paclitaxel 175 mg/m2 and 400 mg/m2 carboplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles) was commenced in April 2013. Prior to the fourth cycle of chemotherapy, transvaginal ultrasound was performed, and identified a localized bladder lesion 2×1×1 cm in size, which, despite treatment, gradually increased in size over 3 cycles (13 weeks). Subsequent to completion of chemotherapy treatment for the localized lesion (4×4×3 cm above the vagina) and the level of CA125 in the blood increased from the initial 13 IU/ml to 97 IU/ml subsequent to treatment. In April 2014, the patient refused to consent to the subsequent chemotherapy and self-discharged. In December 2014, the patient was presented again to the Surgical Gynecology Clinic of the Gynecological and Obstetrics Clinical Hospital with weight loss and weakness and was immediately admitted for treatment. Subsequent to improvement of blood morphology, renal function and the general condition of the patient, the proposed chemotherapy regimen Caelyx (doxorubicin) (6 cycles of 50 mg/m2 doxorubicin per cycle, with 3 weeks between chemotherapy cycles) was administered. In total, six cycles of chemotherapy were administered, which did not stop the growth of the localized lesions in the pelvic cavity. At the end of administrations, the dimensions were 7×5×5 cm and CA125 from level had increased from the original 136 IU/ml to 192 IU/ml. In May 2015, chemotherapy was again attempted, with the fourth-line chemotherapy consisting of paclitaxel and carboplatin (6 cycles of intravenous infusion of paclitaxel 175 mg/m2 and 400 mg/m2 carboplatin per cycle lasting 3 h with 3 weeks break between chemotherapy cycles), which was stopped after 3 courses due to the absence of treatment effects, and the request of the patient to be discharged and discontinue treatment. During the last follow-up, the lesion was 10×9×8 cm in size and the blood CA125 level was 625 IU/ml. The patient succumbed to ovarian cancer in late November 2015.

Genetic examination

The proceeding of a genetic examination was performed as previously described (14). Four formalin-fixed paraffin-embedded (FFPE) ovarian carcinoma tissue samples were obtained from the Cancer Pathology Department at Poznan University of Medical Sciences. The FFPE blocks were no older than 5 years.

In order to obtain a high content of cancer cells for DNA extraction, 5–10 sections (5-µm thick) were cut from each paraffin block, and a set of slides was prepared. One slide per patient was then stained routinely with hematoxylin and eosin to identify regions containing a high concentration of cancer cells. Based on this estimation, regions of interest were dissected from the unstained slides. The dissected cells were then put into a 1.5 Eppendorf tube and DNA was extracted using QIAamp DNA FFPE Tissue kit (Qiagen GmbH, Hilden, Germany), according to the manufacturer's protocol. Following the extraction, DNA was inspected using NanoDrop spectrophotometer (NanoDrop; Thermo Fisher Scientific, Inc.) and the Qubit 2.0, Quant-iT™ PicoGreen® dsDNA Assay kit (Thermo Fisher Scientific, Inc.). A final concentration of 12 ng/µl DNA in Tris-EDTA buffer (10 mM Tris-HCl, 0.1 mM disodium EDTA, pH 8) was than utilized for the OncoScan® assay (Affymetrix, Inc., Santa Clara, CA, USA). In total, 80 ng of DNA (in 6.6 µl) from each sample were processed. The advantage of the OncoScan assay is possibility of simultaneous identification of copy number alterations, loss of heterozygosity (LOH) and somatic mutations (SMs) in a single experiment. This is possibly due to the use of molecular inversion probe (MIP) technology, and capturing >220,000 small nucleotide polymorphism (SNP) genotypes focused on ~900 cancer locations, distributed across the genome. Another advantage is the ability to identify selected ‘hotspot’ somatic mutations in nine genes that particularly contribute to the development of various cancers [tumor protein p53, B-Raf proto-oncogene, serine/threonine kinase, KRAS proto-oncogene, GTPase, epidermal growth factor receptor, isocitrate dehydrogenase 1, isocitrate dehydrogenase 2, phosphatase and tensin homolog, phosphoinositide-3-kinase catalytic subunit α (PIK3CA) and NRAS proto-oncogene, GTPase]. The experimental procedure includes several steps. Probes were added to the sample DNA, and allowed to anneal at 58°C overnight (16–18 h) subsequent to an initial denaturation (95°C for 5 min). Samples was then split into two separate reactions, and proceeded as follows: dATP (A) and dTTP (T) (A/T) were added to one reaction, and dGTP (G) and dCTP (C) (G/C) were added to the second in order to conduct gap fill.

Unincorporated and non-circularized MIPs, as well as the remains of the genomic template, were removed by treatment with exonucleases (Affymetrix, Inc.). The circular MIPs that were gap-filled by the A/T or G/C nucleotides were cleaved using the HaeIII enzyme, and their linear form was amplified by PCR. Subsequently, the 120-bp PCR product was cut and the smaller (44-bp) fragment containing the specific SNP genotype was subjected for hybridization onto array. Prior to this, samples were mixed with hybridization buffer and injected into the cartridges for 16–18 h at 49°C and 0.013 × g. Following hybridization, cartridges were removed from the oven, and stained using the GeneChip® Fluidics Station 450 (Affymetrix, Inc.), according to the manufacturer's protocol. Subsequent to staining and washing, arrays were scanned in GeneChip Scanner 3000 7G (Affymetrix, Inc.) and the fluorescence of clusters was measured in order to generate a DAT file. Cluster intensities values were automatically calculated using built-in algorithm from DAT files by the Affymetrix GeneChip Command Console software, version 4.0 (Affymetrix, Inc.), and a CEL file was created.

Genomic data analysis

CEL files were processed using OncoScan Console software, version 1.1.034 (Affymetrix, Inc.), to recalculate probe intensities into genomic landscape (OSCHP file) as well as a set of QC metrics (MAPD SNPQC and waviness). For each sample, a profile of copy number alterations was created, expressed by numerical values. The LOH profile was created for all samples, assuming a high confidence interval of ≥3 Mbp (ChAS option). The TuScan algorithm was also used for calculation of ploidy (i.e. 0, 66 or 100%). Somatic mutations were evaluated and viewed in the ChAS browser (Affymetrix, Inc.). The reliability of calls for SMs depends on the SNPQC parameter, and therefore it was necessary to obtain ndSNPQC ≥26 (‘in-bounds’) for all tested samples. The OncoScan assays are able to detect mutations by relying on the signal intensity of designed clusters, which is translated into the mutation score. This algorithm recognizes three basic thresholds for calls, termed ‘Undetected’ for an absence of SMs, and ‘Lower confidence’ or ‘High confidence’ for detected changes. In the present study, the default mutation score thresholds supplied in the software were used.

Results

Genomic studies

Genomic screening using Affymetrix OncoScan arrays resulted in the identification of large genomic rearrangements across all of the cancer tissues. In general, chromosome number changes were detected in all examined tissues. Ploidies were found in three out of four examined samples. Patients 1 and 2 showed incomplete tetraploidy, whereas patient 3 showed incomplete triploidy. Patient 4 showed diploidy, according to the TuScan algorithm, with hypoploidy of chromosomes 13 and 15. The detailed analysis of regions presenting LOH resulted in the detection of 152 LOH segments with a minimum 3 Mbp size (Table I). These findings are shown in Fig. 1, and the location of each altered segment was depicted. Subsequently, unique overlapping regions in patients presenting sensitivity for treatment (patients 1 and 2) vs. patients showing resistance (patients 3 and 4) were assessed. For the first cohort, only 5 segments on chromosomes 4, 6, 8, 9 and 16 were identified (Table II; Fig. 2). Within those regions, 10 cancer genes were identified using the COSMIC database. For the second cohort, 20 regions on chromosomes 3–5, 7–9, 10, 11, 14–16 and 19 were identified. Within the selected segments, 45 different cancer genes were found (Table III; Fig. 3). The identified LOH regions for all patients are presented in Fig. 1.

Table I.

LOH regions identified in all examined patients.

Table I.

LOH regions identified in all examined patients.

No.SampleTypeChrom.CytobandGenomic location startGenomic location endSize (Kbp)Gene count
  11_189975.OSCHPLOH1p21.31158379199631179519526.124161
  2 4_208156_15.OSCHPLOH1p31.3894735226809520621378.31696
  3 3_8376_10.OSCHPLOH1p36.2333275981789287025383.111392
  4 3_8376_10.OSCHPLOH1p36.3347383557541913984.16497
  51_189975.OSCHPLOH1p36.333376019775419133006.006524
  6 3_8376_10.OSCHPLOH1q23.318037733916337753516999.804144
  7 3_8376_10.OSCHPLOH1q31.21975741341915101246064.0124
  8 2_203344_15.OSCHPLOH1q32.121660507120064936515955.706180
  9 2_203344_15.OSCHPLOH1q4324921287823725782311955.055102
  10 3_8376_10.OSCHPLOH2p21902450354299316547251.87302
  11 3_8376_10.OSCHPLOH2p25.3397670742149339745.581250
  12 2_203344_15.OSCHPLOH2q11.211292881510183127011097.54579
  131_189975.OSCHPLOH2q1314146360411413819127325.413127
  14 2_203344_15.OSCHPLOH2q36.12281576612244634133694.24818
  15 3_8376_10.OSCHPLOH2q36.324305233123064176212410.569154
  16 2_203344_15.OSCHPLOH2q36.324305233123090387412148.457152
  17 3_8376_10.OSCHPLOH3p21.3151927415460010625926.353143
  18 4_208156_15.OSCHPLOH3p21.3153323914502484263075.48882
  19 3_8376_10.OSCHPLOH3p26.3115399556341011476.54569
  20 4_208156_15.OSCHPLOH3p26.3493461306341049282.72368
  21 4_208156_15.OSCHPLOH3q22.316497284013829696726675.873147
  22 3_8376_10.OSCHPLOH3q25.3216821943715742632810793.10939
  23 3_8376_10.OSCHPLOH3q27.119785256418441600813436.556129
  24 3_8376_10.OSCHPLOH4p15.135668267299509645717.3031
  25 2_203344_15.OSCHPLOH4p16.38060637715657989.072107
  261_189975.OSCHPLOH4p16.3490924547156549020.889278
  271_189975.OSCHPLOH4q1119091565052684890138230.76611
  28 2_203344_15.OSCHPLOH4q1119091565052684890138230.76611
  29 3_8376_10.OSCHPLOH4q22.31140683069774843516319.87190
  30 4_208156_15.OSCHPLOH4q2419091565010327188787643.763337
  31 3_8376_10.OSCHPLOH4q2617747815611981594357662.213207
  32 4_208156_15.OSCHPLOH5p14.133066481281420984924.38312
  33 3_8376_10.OSCHPLOH5q11.1688283724944196519386.40787
  34 4_208156_15.OSCHPLOH5q11.2688283725116411417664.25883
  351_189975.OSCHPLOH5q11.2688283725286436415964.00877
  36 2_203344_15.OSCHPLOH5q11.2688283725508169313746.67956
  37 3_8376_10.OSCHPLOH5q13.2900490577030667719742.38109
  38 2_203344_15.OSCHPLOH5q13.21199199587030667749613.281206
  391_189975.OSCHPLOH5q13.218069831270306677110391.635749
  40 4_208156_15.OSCHPLOH5q13.218069831270306677110391.635749
  41 3_8376_10.OSCHPLOH5q21.11068619751012063685655.6079
  42 3_8376_10.OSCHPLOH5q21.31149575611078534107104.15133
  43 3_8376_10.OSCHPLOH5q22.31215393981151804156358.98320
  44 2_203344_15.OSCHPLOH5q23.21248808651214811823399.68311
  45 3_8376_10.OSCHPLOH5q23.31327831871296328623150.32534
  46 2_203344_15.OSCHPLOH5q31.11369352281335685043366.72433
  47 3_8376_10.OSCHPLOH5q31.21425590921389653753593.717106
  48 2_203344_15.OSCHPLOH5q321506544811474800793174.40248
  49 2_203344_15.OSCHPLOH5q33.11543368321507890503547.78221
  50 3_8376_10.OSCHPLOH5q33.117667542315173861124936.812137
  51 2_203344_15.OSCHPLOH5q33.218069831215527721425421.098200
  52 2_203344_15.OSCHPLOH6p25.32170460220490821499.694116
  531_189975.OSCHPLOH6p25.35877050220490858565.594708
  54 3_8376_10.OSCHPLOH6q11.169746054618863927859.6628
  551_189975.OSCHPLOH6q11.117091305161886392109026.659512
  56 2_203344_15.OSCHPLOH6q22.3217091305112647176044441.291261
  57 3_8376_10.OSCHPLOH6q23.317091305113573935435173.697205
  58 4_208156_15.OSCHPLOH6q23.317091305113826643032646.621189
  59 3_8376_10.OSCHPLOH7p15.3358735402188256013990.98118
  60 4_208156_15.OSCHPLOH7p22.3507001534142050658.733348
  611_189975.OSCHPLOH8p23.126419805809476218325.043147
  62 4_208156_15.OSCHPLOH8p23.127024823809476218930.061148
  63 3_8376_10.OSCHPLOH8p23.130191040809476222096.278182
  641_189975.OSCHPLOH8p23.370041471724166831.73136
  65 3_8376_10.OSCHPLOH8p23.370041471724166831.73136
  66 4_208156_15.OSCHPLOH8p23.370041471724166831.73136
  67 4_208156_15.OSCHPLOH8q11.2153114569498452073269.3625
  68 4_208156_15.OSCHPLOH8q12.11176820095951575558166.254254
  69 2_203344_15.OSCHPLOH8q12.366046002629960383049.96412
  701_189975.OSCHPLOH8q13.31111545327142871639725.816192
  71 3_8376_10.OSCHPLOH8q24.221407898471349864905803.35710
  72 2_203344_15.OSCHPLOH9p22.3245596531436458910195.06459
  731_189975.OSCHPLOH9p24.33343415320473733229.416138
  74 4_208156_15.OSCHPLOH9q21.1178561334709843717576.96337
  751_189975.OSCHPLOH9q21.121410547617313414367920.618659
  76 3_8376_10.OSCHPLOH9q21.13992349977493750224297.495145
  77 2_203344_15.OSCHPLOH9q21.13935998907906462314535.26767
  78 3_8376_10.OSCHPLOH9q31.113624163910783984028401.799301
  79 4_208156_15.OSCHPLOH9q33.214105476112542286415631.897316
  801_189975.OSCHPLOH10p15.33276461312606932638.544188
  811_189975.OSCHPLOH10q23.11354343038257577752858.526437
  82 4_208156_15.OSCHPLOH10q23.11354343038284390352590.4437
  83 3_8376_10.OSCHPLOH10q23.11143817208726800427113.716267
  84 3_8376_10.OSCHPLOH11p11.251575951460897755486.17659
  851_189975.OSCHPLOH11p11.251575951480402603535.69118
  861_189975.OSCHPLOH11p15.537892061927633596.443112
  87 4_208156_15.OSCHPLOH11p15.52702587719276326833.114361
  88 3_8376_10.OSCHPLOH11p15.53878625219276338593.489422
  89 4_208156_15.OSCHPLOH11q12.263386750602122963174.454108
  901_189975.OSCHPLOH11q13.480566396707198969846.5108
  91 4_208156_15.OSCHPLOH11q14.11349388478256044452378.403405
  92 3_8376_10.OSCHPLOH11q14.193535839846647038871.13656
  93 3_8376_10.OSCHPLOH11q22.11184733859951960318953.782155
  941_189975.OSCHPLOH11q22.31162167591083062357910.52462
  951_189975.OSCHPLOH12p13.331291932518939912729.926215
  96 3_8376_10.OSCHPLOH12q13.131338181155205112981766.986724
  97 2_203344_15.OSCHPLOH12q14.162234495590596743174.8213
  98 2_203344_15.OSCHPLOH12q21.331338181158977999644038.119388
  99 4_208156_15.OSCHPLOH12q23.11338181159656452437253.591340
100 3_8376_10.OSCHPLOH13q111119561031908482292871.281429
101 2_203344_15.OSCHPLOH13q111151031501908482296018.328460
102 4_208156_15.OSCHPLOH13q111151031501908482296018.328460
103 3_8376_10.OSCHPLOH14q11.2359301952329913412631.061116
104 4_208156_15.OSCHPLOH14q23.11072820246007127747210.747465
1051_189975.OSCHPLOH14q23.1998738916043620139437.69283
106 3_8376_10.OSCHPLOH14q32.21072820241007856166496.408170
1071_189975.OSCHPLOH15q11.2789385672275239856186.169617
108 3_8376_10.OSCHPLOH15q11.2795480772275239856795.679624
109 4_208156_15.OSCHPLOH15q11.21023973172275239879644.919807
110 2_203344_15.OSCHPLOH15q24.279167603759486703218.93342
111 2_203344_15.OSCHPLOH16p11.235271725318428473428.87816
112 3_8376_10.OSCHPLOH16p13.3237921578388623708.271366
1131_189975.OSCHPLOH16p13.3352717258388635187.839535
1141_189975.OSCHPLOH16q11.2901580054646130843696.697420
115 3_8376_10.OSCHPLOH16q11.2901580054646130843696.697420
1161_189975.OSCHPLOH17p13.32221788340095821816.925399
117 2_203344_15.OSCHPLOH17p13.32221788340095821816.925399
118 3_8376_10.OSCHPLOH17p13.32221788340095821816.925399
119 4_208156_15.OSCHPLOH17p13.32221788340095821816.925399
1201_189975.OSCHPLOH17q11.1458632192532694020536.279472
121 2_203344_15.OSCHPLOH17q11.1802634272532694054936.487952
122 3_8376_10.OSCHPLOH17q11.1802634272532694054936.487952
123 4_208156_15.OSCHPLOH17q11.1802634272532694054936.487952
1241_189975.OSCHPLOH17q23.2802634275839095921872.468320
125 2_203344_15.OSCHPLOH18p11.321049307720631838429.89444
126 4_208156_15.OSCHPLOH18q12.1780077842605743651950.348215
127 2_203344_15.OSCHPLOH18q12.2780077843633567441672.11172
128 3_8376_10.OSCHPLOH18q12.3780077843834930739658.477169
1291_189975.OSCHPLOH18q12.3780077844290872535099.059162
1301_189975.OSCHPLOH19p13.344488432472314201.612154
131 4_208156_15.OSCHPLOH19p13.362223532472315975.122196
132 3_8376_10.OSCHPLOH19p13.390335482472318786.317277
133 2_203344_15.OSCHPLOH19q13.11590932393536607423727.165924
134 4_208156_15.OSCHPLOH19q13.2567319554224144414490.511616
1351_189975.OSCHPLOH19q13.32590932394641664612676.593561
136 4_208156_15.OSCHPLOH20p13168114346909316742.341139
1371_189975.OSCHPLOH20q11.22601261573431329625812.861250
138 2_203344_15.OSCHPLOH20q13.258259236527219555537.28149
139 3_8376_10.OSCHPLOH20q13.260139227527712607367.96757
1401_189975.OSCHPLOH21q11.2480976101434453633753.074295
1411_189975.OSCHPLOH22q11.1512138261605471235159.114549
142 4_208156_15.OSCHPLOH22q11.1512138261605471235159.114549
143 3_8376_10.OSCHPLOH22q11.21512138261993935231274.474492
144 2_203344_15.OSCHPLOH22q11.21512138262102894530184.881467
1451_189975.OSCHPLOHXp22.335841292917794158234.988396
146 3_8376_10.OSCHPLOHXp22.335841292917794158234.988396
147 2_203344_15.OSCHPLOHXq11.165127774617323933395.38112
148 3_8376_10.OSCHPLOHXq11.1760017856173239314269.392102
1491_189975.OSCHPLOHXq11.11552193646173239393486.971623
150 4_208156_15.OSCHPLOHXq11.267429457635545613874.89612
151 3_8376_10.OSCHPLOHXq21.3192806132882657724540.363
152 3_8376_10.OSCHPLOHXq251296074221256783603929.06218

[i] LOH, loss of heterozygosity; Chrom., chromosome

Table II.

The chromosomal regions showing chromosomal alterations identified in patients 1–2 showing sensitiveness for chemotherapy.

Table II.

The chromosomal regions showing chromosomal alterations identified in patients 1–2 showing sensitiveness for chemotherapy.

No.TypeSegmentChrom.Genomic location startGenomic location endSize (Kbp)Cancer genes
1lohLOH_2_15.OSCHP  4526848909783647945151.589FIP1L1, CHIC2, PDGFRA, KIT, KDR
2lohLOH_2_15.OSCHP  6     2049082170460221499.694IRF4, DEK,
3lohLOH_2_15.OSCHP  9143645892455965310195.064NFIB, MLLT3, CDKN2A
4lohLOH_2_15.OSCHP1631842847352717253428.878
5loss Loss1.5_2_15.OSCHP  889900441957596985859.257

[i] LOH, loss of heterozygosity; Chrom., chromosome.

Table III.

The chromosomal regions with alterations identified in patients 3 and 4, who showed chemoresistance.

Table III.

The chromosomal regions with alterations identified in patients 3 and 4, who showed chemoresistance.

No.TypeSegmentChrom.Genomic location startGenomic location endSizeGenes
  1lohLOH_3_10.OSCHP3634101153995511476.545SRGAP3, FANCD2, VHL
  2lohLOH_3_10.OSCHP346001062519274155926.353SETD2
  3lohLOH_3_10.OSCHP315742632816821943710793.109MLF1
  4loss Loss1.0_4_15.OSCHP410489278912686472121971.932TET2, IL2
  5loss Loss1.0_4_15.OSCHP416002631619091565030889.334
  6loss Loss1.0_4_15.OSCHP55150566411387595762370.293IL6ST, PIK3R1, APC
  7lohLOH_3_10.OSCHP7218825603587354013990.98HNRN, PA2B1, HOXA9, HOXA11, HOXA13, JAZF1
  8loss Loss1.3_3_10.OSCHP723008207271157184107.511
  9loss Loss1.7_3_10.OSCHP727127230322196575092.427
10loss Loss1.3_3_10.OSCHP73224042432817742577.318
11loss Loss1.0_4_15.OSCHP81724162617097525998.559PCM1
12loss Loss1.5_4_15.OSCHP912604400913614770210103.693SET, FNBP1, ABL1, NUP214, TSC1, RALGDS
13loss LOH_3_8376_10.OSCHP108726800411438172027113.716BMPR1A, PTEN, TLX1, NFKB2, SUFU, NT5C2, VTI1A, TCF7L2, FGFR2
14lohLOH_4_15.OSCHP111927632702587726833.114HRAS, CARS, NUP98, LMO1, FANCF
15lohLOH_3_10.OSCHP1184664703935358398871.136PICALM
16loss LOH_3_8376_10.OSCHP141007856161072820246496.408
17loss Loss1.3_3_10.OSCHP1571156952792142158057.263PML
18loss Loss1.5_4_15.OSCHP1618069547192664571196.91
19loss Loss1.0_4_15.OSCHP1924723156557925408.561FSTL3, STK11, TCF3, GNA11, MAP2K2, SH3GL1, MLLT1
20loss Loss1.7_3_10.OSCHP19155064980860556535.406

[i] LOH, loss of heterozygosity; Chrom., chromosome.

The OncoScan arrays enabled the identification of ~100 common somatic mutations (Table IV). In the present study, only one mutation was identified, in patient 4. The mutation affected the PIK3CA gene and lead to a glutamic acid-lysine substitution (p.E542K, c.1624G>A; Cosmic ID, COSM760). Notably, the mutation was found in cancer tissue that was diploid and was showing only a hypoploidy of acrocentric chromosomes (chromosomes 13, 15, 18 and 22).

Table IV.

List of the drivers somatic mutations implemented into Affymetrix OncoScan Arrays.

Table IV.

List of the drivers somatic mutations implemented into Affymetrix OncoScan Arrays.

MutationTypeAA changeCDS changeCosmic ID
NRAS:p.Q61R:c.182A>GMissensep.Q61Rc.182A>GCOSM584
NRAS:p.Q61L:c.182A>TMissensep.Q61Lc.182A>TCOSM583
NRAS:p.Q61K:c.181C>AMissensep.Q61Kc.181C>ACOSM580
NRAS:p.G12V:c.35G>TMissensep.G12Vc.35G>TCOSM566
NRAS:p.G12D:c.35G>AMissensep.G12Dc.35G>ACOSM564
NRAS:p.G12S/C:c.34G>A/TMissensep.G12S||p.G12C c.34G>A||c.34G>T COSM563||COSM562
IDH1:p.R132H:c.395G>AMissensep.R132Hc.395G>ACOSM28746
PIK3CA:p.E542K:c.1624G>AMissensep.E542Kc.1624G>ACOSM760
PIK3CA:p.E545K:c.1633G>AMissensep.E545Kc.1633G>ACOSM763
PIK3CA:p.Q546K:c.1636C>AMissensep.Q546Kc.1636C>ACOSM766
PIK3CA:p.H1047R:c.3140A>GMissensep.H1047Rc.3140A>GCOSM775
PIK3CA:p.H1047L:c.3140A>TMissensep.H1047Lc.3140A>TCOSM776
EGFR:p.G719S:c.2155G>AMissensep.G719Sc.2155G>ACOSM6252
EGFR:p.G719C:c.2155G>TMissensep.G719Cc.2155G>TCOSM6253
EGFR:p.G719A:c.2156G>CMissensep.G719Ac.2156G>CCOSM6239
EGFR:p.E746_A750del:c.2235_2249del15In-frame p.E746_A750delELREA c.2235_2249del15COSM6223
EGFR:p.E746_A750del:c.2236_2250del15In-frame p.E746_A750delELREA c.2236_2250del15COSM6225
EGFR:p.E746_T751>A:c.2237_2251del15Deletion In-frame p.E746_T751>A c.2237_2251del15COSM12678
EGFR:p.L747_E749P/del:c.2239_2248>C/GVarious p.L747_A750>P||p.L747_E749delLRE c.2239_2248TTAAGAGAAG >C||c.2239_2247 delTTAAGAGAACOSM12 382||COSM6218
EGFR:p.L747_T751del:c.2240_2254del15In-Frame p.L747_T751delLREAT c.2240_2254del15COSM12369
EGFR:p.L747_P753>S:c.2240_2257del18Deletion In-frame p.L747_P753>S c.2240_2257del18COSM12370
EGFR:p.V769_D770insASV:c.2307_2308ins9In-frame p.V769_D770insASVc.2307_2308ins GCCAGCGTGCOSM12376
EGFR:p.D770_N771insSVD:c.2311_2312ins9In-frame p.D770_N771insSVDc.2311_2312ins GCGTGGACACOSM13428
EGFR:p.H773_V774insNPH:c.2319_2320ins9In-frame p.H773_V774insNPHc.2319_2320ins AACCCCCACCOSM12381
EGFR:p.T790M:c.2369C>TMissensep.T790Mc.2369C>TCOSM6240
EGFR:p.L858R:c.2573T>GMissensep.L858Rc.2573T>GCOSM6224
EGFR:p.L861Q:c.2582T>AMissensep.L861Qc.2582T>ACOSM6213
BRAF:p.V600K:c.1798_1799GT>AAMissensep.V600K c.1798_1799GT>AACOSM473
BRAF:p.V600E:c.1799T>AMissensep.V600Ec.1799T>ACOSM476
BRAF:p.G469E:c.1406G>AMissensep.G469Ec.1406G>ACOSM461
BRAF:p.G469A:c.1406G>CMissensep.G469Ac.1406G>CCOSM460
PTEN:p.R130G:c.388C>GMissensep.R130Gc.388C>GCOSM5219
PTEN:p.R130*:c.388C>TNonsensep.R130*c.388C>TCOSM5152
PTEN:p.R130Q/fs*4:c.389G>A/delGVarious p.R130Q||p.R130fs*4 c.389G>A||c.389delG COSM5033||COSM5817
PTEN:p.R159S:c.477G>TMissensep.R159Sc.477G>TCOSM5287
PTEN:p.R233*:c.697C>TNonsensep.R233*c.697C>TCOSM5154
PTEN:p.P248fs*5:c.741_742insAFrame-Shiftp.P248fs*5c.741_742insACOSM4986
PTEN:p.K267fs*9:c.800delAFrame-Shiftp.K267fs*9c.800delACOSM5809
KRAS:p.A146P:c.436G>CMissensep.A146Pc.436G>CCOSM19905
KRAS:p.Q61H:c.183A>TMissensep.Q61Hc.183A>TCOSM555
KRAS:p.Q61H:c.183A>CMissensep.Q61Hc.183A>CCOSM554
KRAS:p.Q61K/K:c.180_181TC>TA/AAMissensep.Q61Kc.181C>A||c. 180_181TC>AA COSM549||COSM87298
KRAS:p.G13D:c.38G>AMissensep.G13Dc.38G>ACOSM532
KRAS:p.G12D/V:c.35G>A/TMissensep.G12D||p.G12V c.35G>A||c.35G>T COSM521||COSM520
KRAS:p.G12A:c.35G>CMissensep.G12Ac.35G>CCOSM522
KRAS:p.G12C/S:c.34G>T/AMissensep.G12C||p.G12S c.34G>T||c.34G>A COSM516||COSM517
IDH2:p.R172K:c.515G>AMissensep.R172Kc.515G>ACOSM33733
IDH2:p.R140Q:c.419G>AMissensep.R140Qc.419G>ACOSM41590
TP53:p.R306*:c.916C>TNonsensep.R306*c.916C>TCOSM10663
TP53:p.R282W:c.844C>TMissensep.R282Wc.844C>TCOSM10704
TP53:p.R273H/L:c.818G>A/TMissense p.R273H||p.R273L c.818G>A||c.818G>T COSM10660||COSM10779
TP53:p.R273C/S:c.817C>T/AMissense p.R273C||p.R273S c.817C>T||c.817C>A COSM10659||COSM43909
TP53:p.R249S:c.747G>TMissensep.R249Sc.747G>TCOSM10817
TP53:p.R248Q/L:c.743G>A/TMissense p.R248Q||p.R248L c.743G>A||c.743G>T COSM10662||COSM6549
TP53:p.R248W:c.742C>TMissensep.R248Wc.742C>TCOSM10656
TP53:p.G245S/C:c.733G>A/TMissense p.G245S||p.G245C c.733G>A||c.733G>T COSM6932||COSM11081
TP53:p.Y220C:c.659A>GMissensep.Y220Cc.659A>GCOSM10758
TP53:p.R213*:c.637C>TNonsensep.R213*c.637C>TCOSM10654
TP53:p.R196*:c.586C>TNonsensep.R196*c.586C>TCOSM10705
TP53:p.H179R:c.536A>GMissensep.H179Rc.536A>GCOSM10889
TP53:p.C176F:c.527G>TMissensep.C176Fc.527G>TCOSM10645
TP53:p.R175H:c.524G>AMissensep.R175Hc.524G>ACOSM10648
TP53:p.Y163C:c.488A>GMissensep.Y163Cc.488A>GCOSM10808
TP53:p.V157F:c.469G>TMissensep.V157Fc.469G>TCOSM10670

Discussion

Ovarian cancer has the highest mortality rate among reproductive cancers and currently ranks as the fifth leading cause of cancer-associated mortalities among women. Despite the improvements achieved in ovarian cancer therapy over previous decades, the overall 5-year survival rate remains <50% (15). Therefore, novel agents are necessary to improve the outcomes for ovarian cancer patients. In addition, it is important to understand and define the patients that are likely to be sensitive to treatment and have resistant disease. Ovarian cancer is a lethal gynecological disease that is characterized by peritoneal metastasis and increased resistance to conventional chemotherapies (16). This increased resistance and the ability of the cancer to spread is often attributed to the formation of multicellular aggregates or spheroids in the peritoneal cavity, which seed to abdominal surfaces and organs (17). Since the presence of metastatic implants is a predictor of poor survival, a better understanding of how spheroids form is critical to improving patient outcome, and may result in the identification of novel therapeutic targets (16). The most widely used tumor marker in ovarian cancer, often considered the ‘gold standard’, is CA125, which is elevated in 80% of epithelial ovarian cancers (EOCs) (18). CA125 is elevated in 50–60% of patients with stage I EOC and 75–90% of patients with advanced stage EOC (19). The sensitivity of CA125 to identify early stage disease is limited as a screening tool (20). Reliable clinical evidence demonstrates that human epididymis protein (HE4), used alone or in combination with CA125, substantially improves the accuracy of screening and/or disease monitoring (21). HE4, found primarily in the epithelia of normal genital tissues is elevated in EOC (22). HE4 has greater specificity in the premenopausal age group than CA125, since it does not appear to be expressed at high levels in benign conditions (2325). The strongest risk factor of developing ovarian cancer is a family history of breast and ovarian cancer. It is known that ~15% of ovarian cancer patients in the Polish population carry mutations in the BRCA1 and BRCA2 genes (26). A small number of cases are also associated with Lynch syndrome and mutations in hMLH1, hMSH2, hMSH6, PMS1 and PMS2 in mismatch repair genes (27). Chemotherapy resistance is a common problem faced by patients diagnosed with EOC (28,29). Currently there are no specific or sensitive clinical biomarkers that may be implemented to identify chemotherapy resistance and provide insight into prognosis. Resistance of tumors to chemotherapeutic drugs remains a major clinical challenge for ovarian cancer treatment. The limitations of clinical chemotherapy have been ascribed primarily to mechanisms that mediate drug resistance at the cellular level (30). Previous studies suggest that tumor cells have the ability to regulate genes that help to export, decrease uptake, or increase the metabolism of chemotherapeutic drugs. Newer data also suggest that interactions between tumor cells and the surrounding microenvironment allow for increased resistance of tumor cells to chemotherapy (31). It has been observed that although 40–60% of patients achieve a complete clinical response to first-line chemotherapy treatment ~50% of these patients relapse within 5 years and only 10–15% of patients presenting with advanced stage disease achieve long-term remission (32). It is hypothesized that the high relapse rate is, at least in part, due to resistance to chemotherapy, which may be inherent or acquired by altered gene expression. The patient response to chemotherapy for ovarian cancer is extremely heterogeneous and there are currently no tools to aid the prediction of sensitivity or resistance to chemotherapy and allow treatment stratification (8). Such a tool may markedly improve patient survival by identifying the most appropriate treatment on a patient-specific basis. A clinically applicable gene signature capable of predicting patient response to chemotherapy has not yet been identified. Research into a predictive model, as opposed to a prognostic model, may be highly beneficial and aid the identification of the most suitable treatment for patients. Although it has not yet been accomplished, progress within the field suggests that the development of a predictive model is possible (8). There is considerable variability between the approaches and success of existing studies in the literature, and there have been high levels of variation in the explanatory genes identified (13). The present study hypothesizes that, if more attention is paid to selecting the patients included, to control for treatment history, these gene signatures may be simplified and models that are able to predict the response to treatment may be developed.

Targeting molecular signatures, as well as signal transduction pathways for tumor sensitivity and resistance is essential for treatment and improving overall survival in patients with ovarian cancer (33). At present, an efficient molecular diagnostics for patients has not been established. The major goal of the present study was to reveal molecular hallmarks associated with, or even responsible for, the response of a patient to standard treatment. This knowledge facilitates the design and implementation of new therapies based on the genetic defect type. The identification of molecular signatures associated with chemo-response is a recent area of investigation. In ovarian adenocarcinoma, the OncoScan microarray technology has been performed to find genetic markers and locations that would be relevant in the prediction of response to chemotherapy. The OncoScan assay is efficient for the analysis of FFPE samples (14).

For the purposes of the present study, patients were divided into two categories, according to responsiveness to chemotherapy. In microarray analysis, the distribution of specific genetic factors between patients was compared. Significant variances in the occurrence of rearrangements were detected for both amplifications (gains) and deletions (losses). Deletions were more frequent in patients showing chemoresistance (14 losses) than in patients presenting with chemosensitivity (1 loss). However, none of the deletions were present in both patients in the same group. This discrepancy between the two patients in each cohort shows a high genetic heterogeneity of tumors. Detailed mapping data also revealed information on the LOH. The LOH phenomenon is of particular importance since it enables the tracing of loss of the normal alleles of tumor suppressor genes, to determine the tumor phenotype. Therefore, locations presenting high frequency of LOH are attractive candidates for harboring tumor suppressor mutations. In the present study, similar amounts of LOH were present in the two cohorts. In addition, the majority of the samples showed LOH at several loci. Numerous loci with LOH were common between the two cohorts. However, certain LOH were typical for patients with resistance to chemotherapy or patients presenting with chemosensitivity. Regions of typical LOH for chemosensitivity were located on chromosomes 4 (p16.3, q11) and 6 (p25.3) in the present study, whereas LOH associated with loci 3p21.3, 3p26.3, 6q23.3 and 11q14.1 were found exclusively in the chemoresistant cases.

The assessment of LOH in EOC focused on the role of genes located on the short arm of chromosome 3 (3p) in the development of disease. Deletions in regions 3p21.3 and 3p26.3 are common for such cases (34).

LOH in 6q23.3 affects the genes MYB, TNFAIP3 and ECT2 L. Only TNFAIP3 has been implicated in the inhibition of programmed cell death is and suggested to be a tumor suppressor gene (35). At present, the function the remaining genes is not associated with the pathogenesis of ovarian cancer. Furthermore, Shridhar et al (36) reported that deletion of the 6q23.3 region, which commonly presents LOH in ovarian cancer.

Notably, the commonly mutated genes for EOC, namely: CDH1; PRKN; BRCA1/2; and AKT1 were not identified in the present study. However, in patient 4, who showed chemotherapy resistance, a somatic PIK3CA mutation was identified. Mutation in this gene has been previously associated with ovarian cancer (37). Certain studies have confirmed that the PIK3CA/Akt/mammalian target of rapamycin pathway is commonly dysregulated in ovarian cancers (38,39).

Chemotherapy response in ovarian cancer is a complex and unpredictable process that determines the course of the disease. In the present study, genetic regions associated with ovarian cancer that may play an important role in the context of treatment response were identified. However, additional studies on a larger cohort of patients are required, in order to reveal crucial pathways and molecular determinants that directly influence the disease course and its aggressiveness.

Acknowledgements

This study was supported by the Polish Ministry of Science and Education (grant no. 789/FNiTP/162/2013).

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September 2017
Volume 14 Issue 3

Print ISSN: 1792-1074
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APA
Englert‑Golon, M., Burchardt, B., Budny, B., Dębicki, S., Majchrzycka, B., Wrotkowska, E. ... Sajdak, S. (2017). Genomic markers of ovarian adenocarcinoma and its relevancy to the effectiveness of chemotherapy. Oncology Letters, 14, 3401-3414. https://doi.org/10.3892/ol.2017.6590
MLA
Englert‑Golon, M., Burchardt, B., Budny, B., Dębicki, S., Majchrzycka, B., Wrotkowska, E., Jasiński, P., Ziemnicka, K., Słopień, R., Ruchała, M., Sajdak, S."Genomic markers of ovarian adenocarcinoma and its relevancy to the effectiveness of chemotherapy". Oncology Letters 14.3 (2017): 3401-3414.
Chicago
Englert‑Golon, M., Burchardt, B., Budny, B., Dębicki, S., Majchrzycka, B., Wrotkowska, E., Jasiński, P., Ziemnicka, K., Słopień, R., Ruchała, M., Sajdak, S."Genomic markers of ovarian adenocarcinoma and its relevancy to the effectiveness of chemotherapy". Oncology Letters 14, no. 3 (2017): 3401-3414. https://doi.org/10.3892/ol.2017.6590