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Oncology Letters logoLink to Oncology Letters
. 2017 Jul 17;14(3):3401–3414. doi: 10.3892/ol.2017.6590

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

Monika Englert-Golon 1,*, Bartosz Burchardt 1,2,*,, Bartlomiej Budny 3, Szymon Dębicki 3, Blanka Majchrzycka 3, Elzbieta Wrotkowska 3, Piotr Jasiński 4, Katarzyna Ziemnicka 3, Radosław Słopień 5, Marek Ruchała 3, Stefan Sajdak 1,
PMCID: PMC5588060  PMID: 28927094

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.

Keywords: ovarian adenocarcinoma, point gene mutations, efficacy of the treatment, microarrays

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.

No. Sample Type Chrom. Cytoband Genomic location start Genomic location end Size (Kbp) Gene count
  1 1_189975.OSCHP LOH 1 p21.3 115837919 96311795 19526.124 161
  2 4_208156_15.OSCHP LOH 1 p31.3 89473522 68095206 21378.316 96
  3 3_8376_10.OSCHP LOH 1 p36.23 33275981 7892870 25383.111 392
  4 3_8376_10.OSCHP LOH 1 p36.33 4738355 754191 3984.164 97
  5 1_189975.OSCHP LOH 1 p36.33 33760197 754191 33006.006 524
  6 3_8376_10.OSCHP LOH 1 q23.3 180377339 163377535 16999.804 144
  7 3_8376_10.OSCHP LOH 1 q31.2 197574134 191510124 6064.01 24
  8 2_203344_15.OSCHP LOH 1 q32.1 216605071 200649365 15955.706 180
  9 2_203344_15.OSCHP LOH 1 q43 249212878 237257823 11955.055 102
  10 3_8376_10.OSCHP LOH 2 p21 90245035 42993165 47251.87 302
  11 3_8376_10.OSCHP LOH 2 p25.3 39767074 21493 39745.581 250
  12 2_203344_15.OSCHP LOH 2 q11.2 112928815 101831270 11097.545 79
  13 1_189975.OSCHP LOH 2 q13 141463604 114138191 27325.413 127
  14 2_203344_15.OSCHP LOH 2 q36.1 228157661 224463413 3694.248 18
  15 3_8376_10.OSCHP LOH 2 q36.3 243052331 230641762 12410.569 154
  16 2_203344_15.OSCHP LOH 2 q36.3 243052331 230903874 12148.457 152
  17 3_8376_10.OSCHP LOH 3 p21.31 51927415 46001062 5926.353 143
  18 4_208156_15.OSCHP LOH 3 p21.31 53323914 50248426 3075.488 82
  19 3_8376_10.OSCHP LOH 3 p26.3 11539955 63410 11476.545 69
  20 4_208156_15.OSCHP LOH 3 p26.3 49346130 63410 49282.72 368
  21 4_208156_15.OSCHP LOH 3 q22.3 164972840 138296967 26675.873 147
  22 3_8376_10.OSCHP LOH 3 q25.32 168219437 157426328 10793.109 39
  23 3_8376_10.OSCHP LOH 3 q27.1 197852564 184416008 13436.556 129
  24 3_8376_10.OSCHP LOH 4 p15.1 35668267 29950964 5717.303 1
  25 2_203344_15.OSCHP LOH 4 p16.3 8060637 71565 7989.072 107
  26 1_189975.OSCHP LOH 4 p16.3 49092454 71565 49020.889 278
  27 1_189975.OSCHP LOH 4 q11 190915650 52684890 138230.76 611
  28 2_203344_15.OSCHP LOH 4 q11 190915650 52684890 138230.76 611
  29 3_8376_10.OSCHP LOH 4 q22.3 114068306 97748435 16319.871 90
  30 4_208156_15.OSCHP LOH 4 q24 190915650 103271887 87643.763 337
  31 3_8376_10.OSCHP LOH 4 q26 177478156 119815943 57662.213 207
  32 4_208156_15.OSCHP LOH 5 p14.1 33066481 28142098 4924.383 12
  33 3_8376_10.OSCHP LOH 5 q11.1 68828372 49441965 19386.407 87
  34 4_208156_15.OSCHP LOH 5 q11.2 68828372 51164114 17664.258 83
  35 1_189975.OSCHP LOH 5 q11.2 68828372 52864364 15964.008 77
  36 2_203344_15.OSCHP LOH 5 q11.2 68828372 55081693 13746.679 56
  37 3_8376_10.OSCHP LOH 5 q13.2 90049057 70306677 19742.38 109
  38 2_203344_15.OSCHP LOH 5 q13.2 119919958 70306677 49613.281 206
  39 1_189975.OSCHP LOH 5 q13.2 180698312 70306677 110391.635 749
  40 4_208156_15.OSCHP LOH 5 q13.2 180698312 70306677 110391.635 749
  41 3_8376_10.OSCHP LOH 5 q21.1 106861975 101206368 5655.607 9
  42 3_8376_10.OSCHP LOH 5 q21.3 114957561 107853410 7104.151 33
  43 3_8376_10.OSCHP LOH 5 q22.3 121539398 115180415 6358.983 20
  44 2_203344_15.OSCHP LOH 5 q23.2 124880865 121481182 3399.683 11
  45 3_8376_10.OSCHP LOH 5 q23.3 132783187 129632862 3150.325 34
  46 2_203344_15.OSCHP LOH 5 q31.1 136935228 133568504 3366.724 33
  47 3_8376_10.OSCHP LOH 5 q31.2 142559092 138965375 3593.717 106
  48 2_203344_15.OSCHP LOH 5 q32 150654481 147480079 3174.402 48
  49 2_203344_15.OSCHP LOH 5 q33.1 154336832 150789050 3547.782 21
  50 3_8376_10.OSCHP LOH 5 q33.1 176675423 151738611 24936.812 137
  51 2_203344_15.OSCHP LOH 5 q33.2 180698312 155277214 25421.098 200
  52 2_203344_15.OSCHP LOH 6 p25.3 21704602 204908 21499.694 116
  53 1_189975.OSCHP LOH 6 p25.3 58770502 204908 58565.594 708
  54 3_8376_10.OSCHP LOH 6 q11.1 69746054 61886392 7859.662 8
  55 1_189975.OSCHP LOH 6 q11.1 170913051 61886392 109026.659 512
  56 2_203344_15.OSCHP LOH 6 q22.32 170913051 126471760 44441.291 261
  57 3_8376_10.OSCHP LOH 6 q23.3 170913051 135739354 35173.697 205
  58 4_208156_15.OSCHP LOH 6 q23.3 170913051 138266430 32646.621 189
  59 3_8376_10.OSCHP LOH 7 p15.3 35873540 21882560 13990.98 118
  60 4_208156_15.OSCHP LOH 7 p22.3 50700153 41420 50658.733 348
  61 1_189975.OSCHP LOH 8 p23.1 26419805 8094762 18325.043 147
  62 4_208156_15.OSCHP LOH 8 p23.1 27024823 8094762 18930.061 148
  63 3_8376_10.OSCHP LOH 8 p23.1 30191040 8094762 22096.278 182
  64 1_189975.OSCHP LOH 8 p23.3 7004147 172416 6831.731 36
  65 3_8376_10.OSCHP LOH 8 p23.3 7004147 172416 6831.731 36
  66 4_208156_15.OSCHP LOH 8 p23.3 7004147 172416 6831.731 36
  67 4_208156_15.OSCHP LOH 8 q11.21 53114569 49845207 3269.362 5
  68 4_208156_15.OSCHP LOH 8 q12.1 117682009 59515755 58166.254 254
  69 2_203344_15.OSCHP LOH 8 q12.3 66046002 62996038 3049.964 12
  70 1_189975.OSCHP LOH 8 q13.3 111154532 71428716 39725.816 192
  71 3_8376_10.OSCHP LOH 8 q24.22 140789847 134986490 5803.357 10
  72 2_203344_15.OSCHP LOH 9 p22.3 24559653 14364589 10195.064 59
  73 1_189975.OSCHP LOH 9 p24.3 33434153 204737 33229.416 138
  74 4_208156_15.OSCHP LOH 9 q21.11 78561334 70984371 7576.963 37
  75 1_189975.OSCHP LOH 9 q21.12 141054761 73134143 67920.618 659
  76 3_8376_10.OSCHP LOH 9 q21.13 99234997 74937502 24297.495 145
  77 2_203344_15.OSCHP LOH 9 q21.13 93599890 79064623 14535.267 67
  78 3_8376_10.OSCHP LOH 9 q31.1 136241639 107839840 28401.799 301
  79 4_208156_15.OSCHP LOH 9 q33.2 141054761 125422864 15631.897 316
  80 1_189975.OSCHP LOH 10 p15.3 32764613 126069 32638.544 188
  81 1_189975.OSCHP LOH 10 q23.1 135434303 82575777 52858.526 437
  82 4_208156_15.OSCHP LOH 10 q23.1 135434303 82843903 52590.4 437
  83 3_8376_10.OSCHP LOH 10 q23.1 114381720 87268004 27113.716 267
  84 3_8376_10.OSCHP LOH 11 p11.2 51575951 46089775 5486.176 59
  85 1_189975.OSCHP LOH 11 p11.2 51575951 48040260 3535.691 18
  86 1_189975.OSCHP LOH 11 p15.5 3789206 192763 3596.443 112
  87 4_208156_15.OSCHP LOH 11 p15.5 27025877 192763 26833.114 361
  88 3_8376_10.OSCHP LOH 11 p15.5 38786252 192763 38593.489 422
  89 4_208156_15.OSCHP LOH 11 q12.2 63386750 60212296 3174.454 108
  90 1_189975.OSCHP LOH 11 q13.4 80566396 70719896 9846.5 108
  91 4_208156_15.OSCHP LOH 11 q14.1 134938847 82560444 52378.403 405
  92 3_8376_10.OSCHP LOH 11 q14.1 93535839 84664703 8871.136 56
  93 3_8376_10.OSCHP LOH 11 q22.1 118473385 99519603 18953.782 155
  94 1_189975.OSCHP LOH 11 q22.3 116216759 108306235 7910.524 62
  95 1_189975.OSCHP LOH 12 p13.33 12919325 189399 12729.926 215
  96 3_8376_10.OSCHP LOH 12 q13.13 133818115 52051129 81766.986 724
  97 2_203344_15.OSCHP LOH 12 q14.1 62234495 59059674 3174.821 3
  98 2_203344_15.OSCHP LOH 12 q21.33 133818115 89779996 44038.119 388
  99 4_208156_15.OSCHP LOH 12 q23.1 133818115 96564524 37253.591 340
100 3_8376_10.OSCHP LOH 13 q11 111956103 19084822 92871.281 429
101 2_203344_15.OSCHP LOH 13 q11 115103150 19084822 96018.328 460
102 4_208156_15.OSCHP LOH 13 q11 115103150 19084822 96018.328 460
103 3_8376_10.OSCHP LOH 14 q11.2 35930195 23299134 12631.061 116
104 4_208156_15.OSCHP LOH 14 q23.1 107282024 60071277 47210.747 465
105 1_189975.OSCHP LOH 14 q23.1 99873891 60436201 39437.69 283
106 3_8376_10.OSCHP LOH 14 q32.2 107282024 100785616 6496.408 170
107 1_189975.OSCHP LOH 15 q11.2 78938567 22752398 56186.169 617
108 3_8376_10.OSCHP LOH 15 q11.2 79548077 22752398 56795.679 624
109 4_208156_15.OSCHP LOH 15 q11.2 102397317 22752398 79644.919 807
110 2_203344_15.OSCHP LOH 15 q24.2 79167603 75948670 3218.933 42
111 2_203344_15.OSCHP LOH 16 p11.2 35271725 31842847 3428.878 16
112 3_8376_10.OSCHP LOH 16 p13.3 23792157 83886 23708.271 366
113 1_189975.OSCHP LOH 16 p13.3 35271725 83886 35187.839 535
114 1_189975.OSCHP LOH 16 q11.2 90158005 46461308 43696.697 420
115 3_8376_10.OSCHP LOH 16 q11.2 90158005 46461308 43696.697 420
116 1_189975.OSCHP LOH 17 p13.3 22217883 400958 21816.925 399
117 2_203344_15.OSCHP LOH 17 p13.3 22217883 400958 21816.925 399
118 3_8376_10.OSCHP LOH 17 p13.3 22217883 400958 21816.925 399
119 4_208156_15.OSCHP LOH 17 p13.3 22217883 400958 21816.925 399
120 1_189975.OSCHP LOH 17 q11.1 45863219 25326940 20536.279 472
121 2_203344_15.OSCHP LOH 17 q11.1 80263427 25326940 54936.487 952
122 3_8376_10.OSCHP LOH 17 q11.1 80263427 25326940 54936.487 952
123 4_208156_15.OSCHP LOH 17 q11.1 80263427 25326940 54936.487 952
124 1_189975.OSCHP LOH 17 q23.2 80263427 58390959 21872.468 320
125 2_203344_15.OSCHP LOH 18 p11.32 10493077 2063183 8429.894 44
126 4_208156_15.OSCHP LOH 18 q12.1 78007784 26057436 51950.348 215
127 2_203344_15.OSCHP LOH 18 q12.2 78007784 36335674 41672.11 172
128 3_8376_10.OSCHP LOH 18 q12.3 78007784 38349307 39658.477 169
129 1_189975.OSCHP LOH 18 q12.3 78007784 42908725 35099.059 162
130 1_189975.OSCHP LOH 19 p13.3 4448843 247231 4201.612 154
131 4_208156_15.OSCHP LOH 19 p13.3 6222353 247231 5975.122 196
132 3_8376_10.OSCHP LOH 19 p13.3 9033548 247231 8786.317 277
133 2_203344_15.OSCHP LOH 19 q13.11 59093239 35366074 23727.165 924
134 4_208156_15.OSCHP LOH 19 q13.2 56731955 42241444 14490.511 616
135 1_189975.OSCHP LOH 19 q13.32 59093239 46416646 12676.593 561
136 4_208156_15.OSCHP LOH 20 p13 16811434 69093 16742.341 139
137 1_189975.OSCHP LOH 20 q11.22 60126157 34313296 25812.861 250
138 2_203344_15.OSCHP LOH 20 q13.2 58259236 52721955 5537.281 49
139 3_8376_10.OSCHP LOH 20 q13.2 60139227 52771260 7367.967 57
140 1_189975.OSCHP LOH 21 q11.2 48097610 14344536 33753.074 295
141 1_189975.OSCHP LOH 22 q11.1 51213826 16054712 35159.114 549
142 4_208156_15.OSCHP LOH 22 q11.1 51213826 16054712 35159.114 549
143 3_8376_10.OSCHP LOH 22 q11.21 51213826 19939352 31274.474 492
144 2_203344_15.OSCHP LOH 22 q11.21 51213826 21028945 30184.881 467
145 1_189975.OSCHP LOH X p22.33 58412929 177941 58234.988 396
146 3_8376_10.OSCHP LOH X p22.33 58412929 177941 58234.988 396
147 2_203344_15.OSCHP LOH X q11.1 65127774 61732393 3395.381 12
148 3_8376_10.OSCHP LOH X q11.1 76001785 61732393 14269.392 102
149 1_189975.OSCHP LOH X q11.1 155219364 61732393 93486.971 623
150 4_208156_15.OSCHP LOH X q11.2 67429457 63554561 3874.896 12
151 3_8376_10.OSCHP LOH X q21.31 92806132 88265772 4540.36 3
152 3_8376_10.OSCHP LOH X q25 129607422 125678360 3929.062 18

LOH, loss of heterozygosity; Chrom., chromosome

Figure 1.

Figure 1.

Loss of heterozygosity regions identified in all examined patients. Bars next to the ideogram indicate patients 1–4.

Table II.

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

No. Type Segment Chrom. Genomic location start Genomic location end Size (Kbp) Cancer genes
1 loh LOH_2_15.OSCHP   4 52684890 97836479 45151.589 FIP1L1, CHIC2, PDGFRA, KIT, KDR
2 loh LOH_2_15.OSCHP   6     204908 21704602 21499.694 IRF4, DEK,
3 loh LOH_2_15.OSCHP   9 14364589 24559653 10195.064 NFIB, MLLT3, CDKN2A
4 loh LOH_2_15.OSCHP 16 31842847 35271725 3428.878
5 loss Loss1.5_2_15.OSCHP   8 89900441 95759698 5859.257

LOH, loss of heterozygosity; Chrom., chromosome.

Figure 2.

Figure 2.

A karyogram showing the chromosomal alterations identified in patients 1 and 2, who showed chemosensitivity.

Table III.

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

No. Type Segment Chrom. Genomic location start Genomic location end Size Genes
  1 loh LOH_3_10.OSCHP 3 63410 11539955 11476.545 SRGAP3, FANCD2, VHL
  2 loh LOH_3_10.OSCHP 3 46001062 51927415 5926.353 SETD2
  3 loh LOH_3_10.OSCHP 3 157426328 168219437 10793.109 MLF1
  4 loss Loss1.0_4_15.OSCHP 4 104892789 126864721 21971.932 TET2, IL2
  5 loss Loss1.0_4_15.OSCHP 4 160026316 190915650 30889.334
  6 loss Loss1.0_4_15.OSCHP 5 51505664 113875957 62370.293 IL6ST, PIK3R1, APC
  7 loh LOH_3_10.OSCHP 7 21882560 35873540 13990.98 HNRN, PA2B1, HOXA9, HOXA11, HOXA13, JAZF1
  8 loss Loss1.3_3_10.OSCHP 7 23008207 27115718 4107.511
  9 loss Loss1.7_3_10.OSCHP 7 27127230 32219657 5092.427
10 loss Loss1.3_3_10.OSCHP 7 32240424 32817742 577.318
11 loss Loss1.0_4_15.OSCHP 8 172416 26170975 25998.559 PCM1
12 loss Loss1.5_4_15.OSCHP 9 126044009 136147702 10103.693 SET, FNBP1, ABL1, NUP214, TSC1, RALGDS
13 loss LOH_3_8376_10.OSCHP 10 87268004 114381720 27113.716 BMPR1A, PTEN, TLX1, NFKB2, SUFU, NT5C2, VTI1A, TCF7L2, FGFR2
14 loh LOH_4_15.OSCHP 11 192763 27025877 26833.114 HRAS, CARS, NUP98, LMO1, FANCF
15 loh LOH_3_10.OSCHP 11 84664703 93535839 8871.136 PICALM
16 loss LOH_3_8376_10.OSCHP 14 100785616 107282024 6496.408
17 loss Loss1.3_3_10.OSCHP 15 71156952 79214215 8057.263 PML
18 loss Loss1.5_4_15.OSCHP 16 18069547 19266457 1196.91
19 loss Loss1.0_4_15.OSCHP 19 247231 5655792 5408.561 FSTL3, STK11, TCF3, GNA11, MAP2K2, SH3GL1, MLLT1
20 loss Loss1.7_3_10.OSCHP 19 1550649 8086055 6535.406

LOH, loss of heterozygosity; Chrom., chromosome.

Figure 3.

Figure 3.

A karyogram showing the chromosomal regions with chromosomal alterations identified in patients 3 and 4, who showed chemoresistance.

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.

Mutation Type AA change CDS change Cosmic ID
NRAS:p.Q61R:c.182A>G Missense p.Q61R c.182A>G COSM584
NRAS:p.Q61L:c.182A>T Missense p.Q61L c.182A>T COSM583
NRAS:p.Q61K:c.181C>A Missense p.Q61K c.181C>A COSM580
NRAS:p.G12V:c.35G>T Missense p.G12V c.35G>T COSM566
NRAS:p.G12D:c.35G>A Missense p.G12D c.35G>A COSM564
NRAS:p.G12S/C:c.34G>A/T Missense p.G12S||p.G12C c.34G>A||c.34G>T COSM563||COSM562
IDH1:p.R132H:c.395G>A Missense p.R132H c.395G>A COSM28746
PIK3CA:p.E542K:c.1624G>A Missense p.E542K c.1624G>A COSM760
PIK3CA:p.E545K:c.1633G>A Missense p.E545K c.1633G>A COSM763
PIK3CA:p.Q546K:c.1636C>A Missense p.Q546K c.1636C>A COSM766
PIK3CA:p.H1047R:c.3140A>G Missense p.H1047R c.3140A>G COSM775
PIK3CA:p.H1047L:c.3140A>T Missense p.H1047L c.3140A>T COSM776
EGFR:p.G719S:c.2155G>A Missense p.G719S c.2155G>A COSM6252
EGFR:p.G719C:c.2155G>T Missense p.G719C c.2155G>T COSM6253
EGFR:p.G719A:c.2156G>C Missense p.G719A c.2156G>C COSM6239
EGFR:p.E746_A750del:c.2235_2249del15 In-frame p.E746_A750delELREA c.2235_2249del15 COSM6223
EGFR:p.E746_A750del:c.2236_2250del15 In-frame p.E746_A750delELREA c.2236_2250del15 COSM6225
EGFR:p.E746_T751>A:c.2237_2251del15 Deletion In-frame p.E746_T751>A c.2237_2251del15 COSM12678
EGFR:p.L747_E749P/del:c.2239_2248>C/G Various p.L747_A750>P||p.L747_E749delLRE c.2239_2248TTAAGAGAAG >C||c.2239_2247 delTTAAGAGAA COSM12 382||COSM6218
EGFR:p.L747_T751del:c.2240_2254del15 In-Frame p.L747_T751delLREAT c.2240_2254del15 COSM12369
EGFR:p.L747_P753>S:c.2240_2257del18 Deletion In-frame p.L747_P753>S c.2240_2257del18 COSM12370
EGFR:p.V769_D770insASV:c.2307_2308ins9 In-frame p.V769_D770insASV c.2307_2308ins GCCAGCGTG COSM12376
EGFR:p.D770_N771insSVD:c.2311_2312ins9 In-frame p.D770_N771insSVD c.2311_2312ins GCGTGGACA COSM13428
EGFR:p.H773_V774insNPH:c.2319_2320ins9 In-frame p.H773_V774insNPH c.2319_2320ins AACCCCCAC COSM12381
EGFR:p.T790M:c.2369C>T Missense p.T790M c.2369C>T COSM6240
EGFR:p.L858R:c.2573T>G Missense p.L858R c.2573T>G COSM6224
EGFR:p.L861Q:c.2582T>A Missense p.L861Q c.2582T>A COSM6213
BRAF:p.V600K:c.1798_1799GT>AA Missense p.V600K c.1798_1799GT>AA COSM473
BRAF:p.V600E:c.1799T>A Missense p.V600E c.1799T>A COSM476
BRAF:p.G469E:c.1406G>A Missense p.G469E c.1406G>A COSM461
BRAF:p.G469A:c.1406G>C Missense p.G469A c.1406G>C COSM460
PTEN:p.R130G:c.388C>G Missense p.R130G c.388C>G COSM5219
PTEN:p.R130*:c.388C>T Nonsense p.R130* c.388C>T COSM5152
PTEN:p.R130Q/fs*4:c.389G>A/delG Various p.R130Q||p.R130fs*4 c.389G>A||c.389delG COSM5033||COSM5817
PTEN:p.R159S:c.477G>T Missense p.R159S c.477G>T COSM5287
PTEN:p.R233*:c.697C>T Nonsense p.R233* c.697C>T COSM5154
PTEN:p.P248fs*5:c.741_742insA Frame-Shift p.P248fs*5 c.741_742insA COSM4986
PTEN:p.K267fs*9:c.800delA Frame-Shift p.K267fs*9 c.800delA COSM5809
KRAS:p.A146P:c.436G>C Missense p.A146P c.436G>C COSM19905
KRAS:p.Q61H:c.183A>T Missense p.Q61H c.183A>T COSM555
KRAS:p.Q61H:c.183A>C Missense p.Q61H c.183A>C COSM554
KRAS:p.Q61K/K:c.180_181TC>TA/AA Missense p.Q61K c.181C>A||c. 180_181TC>AA COSM549||COSM87298
KRAS:p.G13D:c.38G>A Missense p.G13D c.38G>A COSM532
KRAS:p.G12D/V:c.35G>A/T Missense p.G12D||p.G12V c.35G>A||c.35G>T COSM521||COSM520
KRAS:p.G12A:c.35G>C Missense p.G12A c.35G>C COSM522
KRAS:p.G12C/S:c.34G>T/A Missense p.G12C||p.G12S c.34G>T||c.34G>A COSM516||COSM517
IDH2:p.R172K:c.515G>A Missense p.R172K c.515G>A COSM33733
IDH2:p.R140Q:c.419G>A Missense p.R140Q c.419G>A COSM41590
TP53:p.R306*:c.916C>T Nonsense p.R306* c.916C>T COSM10663
TP53:p.R282W:c.844C>T Missense p.R282W c.844C>T COSM10704
TP53:p.R273H/L:c.818G>A/T Missense p.R273H||p.R273L c.818G>A||c.818G>T COSM10660||COSM10779
TP53:p.R273C/S:c.817C>T/A Missense p.R273C||p.R273S c.817C>T||c.817C>A COSM10659||COSM43909
TP53:p.R249S:c.747G>T Missense p.R249S c.747G>T COSM10817
TP53:p.R248Q/L:c.743G>A/T Missense p.R248Q||p.R248L c.743G>A||c.743G>T COSM10662||COSM6549
TP53:p.R248W:c.742C>T Missense p.R248W c.742C>T COSM10656
TP53:p.G245S/C:c.733G>A/T Missense p.G245S||p.G245C c.733G>A||c.733G>T COSM6932||COSM11081
TP53:p.Y220C:c.659A>G Missense p.Y220C c.659A>G COSM10758
TP53:p.R213*:c.637C>T Nonsense p.R213* c.637C>T COSM10654
TP53:p.R196*:c.586C>T Nonsense p.R196* c.586C>T COSM10705
TP53:p.H179R:c.536A>G Missense p.H179R c.536A>G COSM10889
TP53:p.C176F:c.527G>T Missense p.C176F c.527G>T COSM10645
TP53:p.R175H:c.524G>A Missense p.R175H c.524G>A COSM10648
TP53:p.Y163C:c.488A>G Missense p.Y163C c.488A>G COSM10808
TP53:p.V157F:c.469G>T Missense p.V157F c.469G>T COSM10670

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).

References

  • 1.Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. doi: 10.3322/caac.20107. [DOI] [PubMed] [Google Scholar]
  • 2.Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin. 2014;64:9–29. doi: 10.3322/caac.21208. [DOI] [PubMed] [Google Scholar]
  • 3.Potrykowska A, Strzelecki Z, Szymborski J, Witkowski J, editors. Rządowa Rada Ludnościowa. Warsaw: 2014. Cancer incidence and mortality versus the demographic situation of Poland; pp. 117–130. (In Polish) [Google Scholar]
  • 4.Paik ES, Lee YY, Lee EJ, Choi CH, Kim TJ, Lee JW, Bae DS, Kim BG. Survival analysis of revised 2013 FIGO staging classification of epithelial ovarian cancer and comparison with previous FIGO staging classification. Obstet Gynecol Sci. 2015;58:124–134. doi: 10.5468/ogs.2015.58.2.124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Suh DH, Kim TH, Kim JW, Kim SY, Kim HS, Lee TS, Chung HH, Kim YB, Park NH, Song YS. Improvements to the FIGO staging for ovarian cancer: Reconsideration of lymphatic spread and intraoperative tumor rupture. J Gynecol Oncol. 2013;24:352–358. doi: 10.3802/jgo.2013.24.4.352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.van der Burg ME, van Lent M, Buyse M, Kobierska A, Colombo N, Favalli G, Lacave AJ, Nardi M, Renard J, Pecorelli S. The effect of debulking surgery after induction chemotherapy on the prognosis in advanced epithelial ovarian cancer. Gynecological cancer cooperative group of the European Organization for research and treatment of cancer. N Engl J Med. 1995;332:629–634. doi: 10.1056/NEJM199503093321002. [DOI] [PubMed] [Google Scholar]
  • 7.Raja FA, Chopra N, Ledermann JA. Optimal first-line treatment in ovarian cancer. Ann Oncol. 2012;23:x118–x127. doi: 10.1093/annonc/mds315. (Suppl 10) [DOI] [PubMed] [Google Scholar]
  • 8.Lloyd KL, Cree IA, Savage RS. Prediction of resistance to chemotherapy in ovarian cancer: A systematic review. BMC Cancer. 2015;15:117. doi: 10.1186/s12885-015-1101-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Pliarchopoulou K, Pectasides D. Epithelial ovarian cancer: Focus on targeted therapy. Crit Rev Oncol Hematol. 2011;79:17–23. doi: 10.1016/j.critrevonc.2010.07.004. [DOI] [PubMed] [Google Scholar]
  • 10.Zhu LC, Gao J, Hu ZH, Schwab CL, Zhuang HY, Tan MZ, Yan LM, Liu JJ, Zhang DY, Lin B. Membranous expressions of Lewis y and CAM-DR-related markers are independent factors of chemotherapy resistance and poor prognosis in epithelial ovarian cancer. Am J Cancer Res. 2015;5:830–843. [PMC free article] [PubMed] [Google Scholar]
  • 11.Vinogradov S, Wei X. Cancer stem cells and drug resistance: The potential of nanomedicine. Nanomedicine (Lond) 2012;7:597–615. doi: 10.2217/nnm.12.22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Markman M, Bookman MA. Second-line treatment of ovarian cancer. Oncologist. 2000;5:26–35. doi: 10.1634/theoncologist.5-1-26. [DOI] [PubMed] [Google Scholar]
  • 13.Cooley M, Fang P, Fang F, Nephew KP, Chien J. Molecular determinants of chemotherapy resistance in ovarian cancer. Pharmacogenomics. 2015;16:1763–1767. doi: 10.2217/pgs.15.130. [DOI] [PubMed] [Google Scholar]
  • 14.Foster JM, Oumie A, Togneri FS, Vasques FR, Hau D, Taylor M, Tinkler-Hundal E, Southward K, Medlow P, McGreeghan-Crosby K, et al. Cross-laboratory validation of the OncoScan® FFPE Assay, a multiplex tool for whole genome tumour profiling. BMC Med Genomics. 2015;8:5. doi: 10.1186/s12920-015-0079-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Bast RC, Jr, Hennessy B, Mills GB. The biology of ovarian cancer: New opportunities for translation. Nat Rev Cancer. 2009;9:415–428. doi: 10.1038/nrc2644. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Musrap N, Tuccitto A, Karagiannis GS, Saraon P, Batruch I, Diamandis EP. Comparative proteomics of ovarian cancer aggregate formation reveals an increased expression of calcium-activated chloride channel regulator 1 (CLCA1) J Biol Chem. 2015;290:17218–17227. doi: 10.1074/jbc.M115.639773. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Burleson KM, Casey RC, Skubitz KM, Pambuccian SE, Oegema TR, Jr, Skubitz AP. Ovarian carcinoma ascites spheroids adhere to extracellular matrix components and mesothelial cell monolayers. Gynecol Oncol. 2004;93:170–181. doi: 10.1016/j.ygyno.2003.12.034. [DOI] [PubMed] [Google Scholar]
  • 18.Høgdall E. Cancer antigen 125 and prognosis. Curr Opin Obstet Gynecol. 2008;20:4–8. doi: 10.1097/GCO.0b013e3282f2b124. [DOI] [PubMed] [Google Scholar]
  • 19.Gadducci A, Cosio S, Fanucchi A, Negri S, Cristofani R, Genazzani AR. The predictive and prognostic value of serum CA 125 half-life during paclitaxel/platinum-based chemotherapy in patients with advanced ovarian carcinoma. Gynecol Oncol. 2004;93:131–136. doi: 10.1016/j.ygyno.2003.12.043. [DOI] [PubMed] [Google Scholar]
  • 20.Menon U, Skates SJ, Lewis S, Rosenthal AN, Rufford B, Sibley K, Macdonald N, Dawnay A, Jeyarajah A, Bast RC, Jr, et al. Prospective study using the risk of ovarian cancer algorithm to screen for ovarian cancer. J Clin Oncol. 2005;23:7919–7926. doi: 10.1200/JCO.2005.01.6642. [DOI] [PubMed] [Google Scholar]
  • 21.Hasanbegovic L, Alicelebic S, Sljivo N. Comparison of specific ovarian tumor markers by elecsys analyzer 2010. Acta Inform Med. 2015;23:86–89. doi: 10.5455/aim.2015.23.86-89. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Hellström I, Raycraft J, Hayden-Ledbetter M, Ledbetter JA, Schummer M, McIntosh M, Drescher C, Urban N, Hellström KE. The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma. Cancer Res. 2003;63:3695–3700. [PubMed] [Google Scholar]
  • 23.Moore RG, MacLaughlan S, Bast RC., Jr Current state of biomarker development for clinical application in epithelial ovarian cancer. Gynecol Oncol. 2010;116:240–245. doi: 10.1016/j.ygyno.2009.09.041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Huhtinen K, Suvitie P, Hiissa J, Junnila J, Huvila J, Kujari H, Setälä M, Härkki P, Jalkanen J, Fraser J, et al. Serum HE4 concentration differentiates malignant ovarian tumours from ovarian endometriotic cysts. Br J Cancer. 2009;100:1315–1319. doi: 10.1038/sj.bjc.6605011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Moore RG, Miller MC, Steinhoff MM, Skates SJ, Lu KH, Lambert-Messerlian G, Bast RC., Jr Serum HE4 levels are less frequently elevated than CA125 in women with benign gynecologic disorders. Am J Obstet Gynecol. 2012;206(351):e1–8. doi: 10.1016/j.ajog.2011.12.029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Górski B, Byrski T, Huzarski T, Jakubowska A, Menkiszak J, Gronwald J, Pluzańska A, Bebenek M, Fischer-Maliszewska L, Grzybowska E, et al. Founder mutations in the BRCA1 gene in Polish families with breast-ovarian cancer. Am J Hum Genet. 2000;66:1963–1968. doi: 10.1086/302922. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Herman JG, Umar A, Polyak K, Graff JR, Ahuja N, Issa JP, Markowitz S, Willson JK, Hamilton SR, Kinzler KW, et al. Incidence and functional consequences of hMLH1 promoter hypermethylation in colorectal carcinoma. Proc Natl Acad Sci USA. 1998;95:6870–6875. doi: 10.1073/pnas.95.12.6870. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Curia MC, Palmirotta R, Aceto G, Messerini L, Verì MC, Crognale S, Valanzano R, Ficari F, Fracasso P, Stigliano V, et al. Unbalanced germ-line expression of hMLH1 and hMSH2 alleles in hereditary nonpolyposis colorectal cancer. Cancer Res. 1999;59:3570–3575. [PubMed] [Google Scholar]
  • 29.Debniak T, Kurzawski G, Gorski B, Kladny J, Domagala W, Lubinski J. Value of pedigree/clinical data, immunohistochemistry and microsatellite instability analyses in reducing the cost of determining hMLH1 and hMSH2 gene mutations in patients with colorectal cancer. Eur J Cancer. 2000;36:49–54. doi: 10.1016/S0959-8049(99)00208-7. [DOI] [PubMed] [Google Scholar]
  • 30.Ali AY, Farrand L, Kim JY, Byun S, Suh JY, Lee HJ, Tsang BK. Molecular determinants of ovarian cancer chemoresistance: New insights into an old conundrum. Ann N Y Acad Sci. 2012;1271:58–67. doi: 10.1111/j.1749-6632.2012.06734.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Thibault B, Castells M, Delord JP, Couderc B. Ovarian cancer microenvironment: Implications for cancer dissemination and chemoresistance acquisition. Cancer Metastasis Rev. 2014;33:17–39. doi: 10.1007/s10555-013-9456-2. [DOI] [PubMed] [Google Scholar]
  • 32.Li M, Yin J, Mao N, Pan L. Upregulation of phosphorylated cofilin 1 correlates with taxol resistance in human ovarian cancer in vitro and in vivo. Oncol Rep. 2013;29:58–66. doi: 10.3892/or.2012.2078. [DOI] [PubMed] [Google Scholar]
  • 33.Mok SC, Bonome T, Vathipadiekal V, Bell A, Johnson ME, Wong KK, Park DC, Hao K, Yip DK, Donninger H, et al. A gene signature predictive for outcome in advanced ovarian cancer identifies a survival factor: Microfibril-associated glycoprotein 2. Cancer Cell. 2009;16:521–532. doi: 10.1016/j.ccr.2009.10.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Fullwood P, Marchini S, Rader JS, Martinez A, Macartney D, Broggini M, Morelli C, Barbanti-Brodano G, Maher ER, Latif F. Detailed genetic and physical mapping of tumor suppressor loci on chromosome 3p in ovarian cancer. Cancer Res. 1999;59:4662–4667. [PubMed] [Google Scholar]
  • 35.Chng HW, Camplejohn RS, Stone MG, Hart IR, Nicholson LJ. A new role for the anti-apoptotic gene A20 in angiogenesis. Exp Cell Res. 2006;312:2897–2907. doi: 10.1016/j.yexcr.2006.05.015. [DOI] [PubMed] [Google Scholar]
  • 36.Shridhar V, Staub J, Huntley B, Cliby W, Jenkins R, Pass HI, Hartmann L, Smith DI. A novel region of deletion on chromosome 6q23.3 spanning less than 500 Kb in high grade invasive epithelial ovarian cancer. Oncogene. 1999;18:3913–3918. doi: 10.1038/sj.onc.1202756. [DOI] [PubMed] [Google Scholar]
  • 37.Shayesteh L, Lu Y, Kuo WL, Baldocchi R, Godfrey T, Collins C, Pinkel D, Powell B, Mills GB, Gray JW. PIK3CA is implicated as an oncogene in ovarian cancer. Nat Genet. 1999;21:99–102. doi: 10.1038/5042. [DOI] [PubMed] [Google Scholar]
  • 38.Cheaib B, Auguste A, Leary A. The PI3K/Akt/mTOR pathway in ovarian cancer: Therapeutic opportunities and challenges. Chin J Cancer. 2015;34:4–16. doi: 10.5732/cjc.014.10289. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Friedlander ML, Russell K, Millis S, Gatalica Z, Bender R, Voss A. Molecular profiling of clear cell ovarian cancers: Identifying potential treatment targets for clinical trials. Int J Gynecol Cancer. 2016;26:648–654. doi: 10.1097/IGC.0000000000000677. [DOI] [PMC free article] [PubMed] [Google Scholar]

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