Genetic, clinic and histopathologic characterization of BRCA-associated hereditary breast and ovarian cancer in southwestern Finland

Pallonen, Terhi Aino-Sofia; Lempiäinen, Salla; Joutsiniemi, Titta; Aaltonen, Riitta; Pohjola, Pia; Kankuri-Tammilehto, Minna

doi:10.1038/s41598-022-10519-y

Cited by 4 publications

(6 citation statements)

References 48 publications

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“…In addition, two patients (2/612, 0.3%) in the familial series had the RAD51C exons 1–7 duplication ( Table 1 ). BRCA1 exon 13 and RAD51C exons 1–7 duplications have previously been reported in Finnish BC patients [ 47 , 48 ], while the CHEK2 deletion has not, to our knowledge. Out of all the carriers of any pathogenic or likely-pathogenic variant, 3/134 (2.2%) had a CNV in the unselected patient group and 2/90 (2.2%) in the familial patient group.…”

Section: Resultsmentioning

confidence: 78%

“…In more detail, 8/1356 (0.6%) patients had a BRCA1 and 16/1356 (1.2%) had a BRCA2 variant. Six of the BRCA1 and four of the BRCA2 variants have previously been detected in more than one Finnish BC family ( Supplementary Table S4 ) [ 23 , 24 , 25 , 45 , 46 , 47 , 48 ]. Here, these recurrent variants covered 6/8 (75.0%) of the pathogenic variation in BRCA1 and 11/16 (68.8%) in BRCA2 among the patients.…”

Section: Resultsmentioning

confidence: 99%

“…The frequencies are in line with other (population-based) studies [ 3 , 5 ]. Unlike in the moderate-risk genes, the pathogenic variant spectrum detected in the high-penetrance BRCA1/2 genes in the Finnish BC families is wide with multiple unique variants [ 25 , 48 ]. Nevertheless, strong founder variants have been identified in the BRCA1/2 genes, especially prominent in BRCA2 [ 23 , 25 , 48 , 51 , 52 ].…”

Section: Discussionmentioning

confidence: 99%

“…Unlike in the moderate-risk genes, the pathogenic variant spectrum detected in the high-penetrance BRCA1/2 genes in the Finnish BC families is wide with multiple unique variants [ 25 , 48 ]. Nevertheless, strong founder variants have been identified in the BRCA1/2 genes, especially prominent in BRCA2 [ 23 , 25 , 48 , 51 , 52 ]. Ten recurrent BRCA1/2 variants were detected in the unselected patients in the current study.…”

Section: Discussionmentioning

confidence: 99%

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Pathogenic Variant Spectrum in Breast Cancer Risk Genes in Finnish Patients

Nurmi

Suvanto

Dennis

et al. 2022

Cancers

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Recurrent pathogenic variants have been detected in several breast and ovarian cancer (BC/OC) risk genes in the Finnish population. We conducted a gene-panel sequencing and copy number variant (CNV) analysis to define a more comprehensive spectrum of pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, BARD1, RAD51C, RAD51D, BRIP1, and FANCM genes in Finnish BC patients. The combined frequency of pathogenic variants in the BRCA1/2 genes was 1.8% in 1356 unselected patients, whereas variants in the other genes were detected altogether in 8.3% of 1356 unselected patients and in 12.9% of 699 familial patients. CNVs were detected in 0.3% of both 1137 unselected and 612 familial patients. A few variants covered most of the pathogenic burden in the studied genes. Of the BRCA1/2 carriers, 70.8% had 1 of 10 recurrent variants. In the other genes combined, 92.1% of the carrier patients had at least 1 of 11 recurrent variants. In particular, PALB2 c.1592delT and CHEK2 c.1100delC accounted for 88.9% and 82.9%, respectively, of the pathogenic variation in each gene. Our results highlight the importance of founder variants in the BC risk genes in the Finnish population and could be used in the designing of population screening for the risk variants.

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Section: Resultsmentioning

confidence: 78%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Pathogenic Variant Spectrum in Breast Cancer Risk Genes in Finnish Patients

Nurmi

Suvanto

Dennis

et al. 2022

Cancers

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“…Развитие и прогрессирование РЯ связано с сочетанием генетических и эпигенетических изменений. Генетические мутации, такие как мутации в генах BRCA1 и BRCA2, связаны с повышенным риском развития РЯ [9]. К эпигенетическим механизмам относятся модификации ДНК и гистонов, которые могут влиять на экспрессию генов, а также воздействие длинных некодирующих РНК (днРНК) [10].…”

Section: Introductionunclassified

Aberrant expression of a long non-coding RNAs group in ovarian cancer

Лукина,

Пронина,

Бурдённый

et al. 2023

Zhurnal «Patologicheskaia Fiziologiia I Eksperimental`naia Terapiia»

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Актуальность. Рак яичников (РЯ) представляет собой группу агрессивных гетерогенных злокачественных опухолей, характеризующихся быстрой прогрессией, низким диагностическим потенциалом, высокой частотой неблагоприятных исходов и высоким потенциалом метастазирования. В последнее время все большую актуальность приобретают исследования длинных некодирующих РНК (днРНК, lncRNAs), которые не обладают способностью кодировать белки. Для днРНК характерна высокая тканеспецифичность экспрессии, они участвуют в регуляции различных сигнальных путей в клетках, демонстрируя большой прогностический потенциал при онкозаболеваниях. Цель исследования – выявление аберрантно экспрессируемых длинных некодирующих РНК в образцах опухолей больных РЯ и связи уровней экспрессии с патофизиологическими характеристиками опухолей. Методика. Образцы опухолей РЯ собраны и клинически охарактеризованы в ФГБУ «НМИЦ онкологии им. Н.Н. Блохина». Высокомолекулярную РНК выделяли из ткани стандартным методом. Анализ уровня экспрессии днРНК HOTAIR, MALAT1 и TINCR проводился с использованием ПЦР в реальном времени готовой реакционной смесью qPCRmix-HS SYBR («Евроген»). Статистический анализ уровней экспрессии выполнен в программной среде R с применением непараметрического U теста Манна–Уитни. Корреляционный анализ выполняли с использованием метода ранговой корреляции Спирмена и рассчитывали уровень его значимости. Различия считали статистически значимыми при р < 0.05. Дополнительно были проанализированы данные по экспрессии днРНК при РЯ по базе данных GEPIA (http://gepia.cancer-pku.cn/). Результаты. Анализ уровня экспрессии днРНК показал значимое (p≤0.05) снижение уровня экспрессии днРНК HOTAIR, MALAT1. При анализе образцов с учётом патофизиологических характеристик опухоли было показано, что снижение уровня экспрессии HOTAIR ассоциировано с III/IV стадией опухолевого процесса. Для днРНК MALAT1 и TINCR показана значимая корреляция низкого уровня экспрессии с развитием эндометриоидного подтипа РЯ. Заключение. Представленные данные способствуют более глубокому пониманию механизмов развития РЯ и могут быть использованы при диагностике, прогнозе и выборе тактики лечения данной патологии. Background.Ovarian cancer (OC) is a group of aggressive heterogeneous malignant tumors characterized by rapid progression, low diagnostic potential, high incidence of adverse outcomes, and high potential for metastasis. Recently, studies of long non-coding RNAs (lncRNAs), which, with rare exceptions, do not have the ability to encode proteins, have become increasingly important. LncRNAs are characterized by high tissue-specific expression and they are involved in the regulation of various signaling pathways in cells and demonstrate a great prognostic potential in cancer. Aim. Detection of aberrantly expressed long non-coding RNAs in tumor samples from OC patients and association of expression levels with pathophysiological characteristics of tumors. Methods. Samples of OC tumors were collected and clinically characterized at the N.N. Blokhin Research Institute of Clinical Oncology. High molecular weight RNA was isolated from tissue by a standard method. Analysis of the expression levels of HOTAIR, MALAT1, and TINCR lncRNA was carried out using real-time PCR and a qPCRmix-HS SYBR ready-made reaction mixture (Evrogen). Statistical analysis of expression levels was performed in the R software environment using the nonparametric Mann-Whitney U test. Correlation analysis was performed using Spearman’s rank correlation, and its significance level was calculated. Differences were considered significant at p<0.05. Additionally, expression levels of these lncRNAs in OC were analyzed using the GEPIA database (http://gepia.cancer-pku.cn/). Results. The expression levels of the HOTAIR and MALAT1 lncRNA genes were significantly decreased (p≤0.05). Analysis of the samples with the account of the tumor pathophysiological characteristics showed that the decrease in the level of HOTAIR expression was associated with stage III/IV of the tumor process. For MALAT1 and TINCR lncRNAs, low expression levels significantly correlated with the development of the endometrioid subtype of OC. Conclusion. The results of the study allow a better insight into the mechanisms of OC development and can be used for diagnosis, prognosis and selection of therapeutic tactics in this pathology.

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Temporal convolutional network for a Fast DNA mutation detection in breast cancer data

et al. 2023

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Early detection of breast cancer can be achieved through mutation detection in DNA sequences, which can be acquired through patient blood samples. Mutation detection can be performed using alignment and machine learning techniques. However, alignment techniques require reference sequences, and machine learning techniques still cannot predict index mutation and require supporting tools. Therefore, in this research, a Temporal Convolutional Network (TCN) model was proposed to detect the type and index mutation faster and without reference sequences and supporting tools. The architecture of the proposed TCN model is specifically designed for sequential labeling tasks on DNA sequence data. This allows for the detection of the mutation type of each nucleotide in the sequence, and if the nucleotide has a mutation, the index mutation can be obtained. The proposed model also uses 2-mers and 3-mers mapping techniques to improve detection performance. Based on the tests that have been carried out, the proposed TCN model can achieve the highest F1-score of 0.9443 for COSMIC dataset and 0.9629 for RSCM dataset, Additionally, the proposed TCN model can detect index mutation six times faster than BiLSTM model. Furthermore, the proposed model can detect type and index mutations based on the patient’s DNA sequence, without the need for reference sequences or other additional tools.

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Genetic, clinic and histopathologic characterization of BRCA-associated hereditary breast and ovarian cancer in southwestern Finland

Cited by 4 publications

References 48 publications

Pathogenic Variant Spectrum in Breast Cancer Risk Genes in Finnish Patients

Pathogenic Variant Spectrum in Breast Cancer Risk Genes in Finnish Patients

Aberrant expression of a long non-coding RNAs group in ovarian cancer

Temporal convolutional network for a Fast DNA mutation detection in breast cancer data

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