3 research outputs found
ΠΠ»ΠΈΠ½ΠΈΠΊΠΎ-ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠ²Π»Π΅Π½ΠΈΠΉ ΠΏΠ°ΠΏΠΈΠ»Π»ΠΎΠΌΠ°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΡΠ°ΠΊΠ° ΡΠ΅ΠΉΠΊΠΈ ΠΌΠ°ΡΠΊΠΈ ΠΈ Π°Π½ΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΡΡ (Π²Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ ) Π±ΠΎΡΠΎΠ΄Π°Π²ΠΎΠΊ
Background: Cervical cancer and genital warts (GWs) are some of the most common manifestations of human papillomavirus infection (HPV). These lesions cause significant damage to the reproductive health of the population, which leads to increased attention to the prevention of HPV infection among various population groups.
Aims: To determine the clinical and epidemiological features of the HPV manifestations by the example of cervical cancer and genital warts.
Methods: A retrospective analysis of anamnestic information of 115 women with an established diagnosis of cervical cancer and 177 patients with an established diagnosis of GWs was performed. The clinical and epidemiological characteristics of patients with diagnoses of GWs and cervical cancer were based on the development of outpatient admission cards and inpatient histories, as well as test data for HPV.
Results: HPV 16 was the most common HPV type among patients with GWs and cervical cancer β it was detected in 37.6% of cases. Also the most frequently encountered: HPV 6/18/11/31/51/52. In 43.2% cases of HPV detection, two or more types were detected at once, the most common combinations: HPV16 and HPV18, HPV6 and HPV16, HPV6 and HPV11. Analysis of the frequency of screening for cervical cancer and visits to the gynecologist for 5 years before establishing the diagnosis showed that among those who did not screen for cervical cancer, the risk of diagnosing stage IIIV was 5.2 times higher than among individuals who underwent cervical screening 2 years ago, or once a year for the last five years. Among patients with GWs who had 2 or more sexual partners for 1 year, 13.5% of patients regularly used barrier contraception methods (condoms) during sexual contact, not regularly β 61.5%, did not use them at all β 25.0%.
Conclusions: Identifying the clinical and epidemiological features of HPV infection should contribute to the development of new and optimize existing prevention programs for a wide range of HPV-associated diseases.ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅. Π Π°ΠΊ ΡΠ΅ΠΉΠΊΠΈ ΠΌΠ°ΡΠΊΠΈ (Π Π¨Π) ΠΈ Π°Π½ΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΡΠ΅ (Π²Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅) Π±ΠΎΡΠΎΠ΄Π°Π²ΠΊΠΈ ΡΠ²Π»ΡΡΡΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΡΠΌΠΈ ΠΏΡΠΎΡΠ²Π»Π΅Π½ΠΈΡΠΌΠΈ ΠΏΠ°ΠΏΠΈΠ»Π»ΠΎΠΌΠ°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ. ΠΠ°Π½Π½ΡΠ΅ ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΡ Π½Π°Π½ΠΎΡΡΡ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ ΡΡΠ΅ΡΠ± ΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΠΌΡ Π·Π΄ΠΎΡΠΎΠ²ΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΡΡΠΎ ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»ΠΈΠ²Π°Π΅Ρ ΠΏΠΎΠ²ΡΡΠ΅Π½Π½ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΊ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠΈ ΠΏΠ°ΠΏΠΈΠ»Π»ΠΎΠΌΠ°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΡΡΠ΅Π΄ΠΈ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π³ΡΡΠΏΠΏ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ.
Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΠΊΠ»ΠΈΠ½ΠΈΠΊΠΎ-ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΏΠ°ΠΏΠΈΠ»Π»ΠΎΠΌΠ°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ ΡΠ°ΠΊΠ° ΡΠ΅ΠΉΠΊΠΈ ΠΌΠ°ΡΠΊΠΈ ΠΈ Π°Π½ΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΡΡ
(Π²Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ
) Π±ΠΎΡΠΎΠ΄Π°Π²ΠΎΠΊ.
ΠΠ΅ΡΠΎΠ΄Ρ. ΠΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ ΡΠ΅ΡΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅; ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ»ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ Ρ Π΄ΠΈΠ°Π³Π½ΠΎΠ·Π°ΠΌΠΈ Π Π¨Π ΠΈ Π°Π½ΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΡΡ
(Π²Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ
) Π±ΠΎΡΠΎΠ΄Π°Π²ΠΎΠΊ, ΠΎΠ±ΡΠ°ΡΠΈΠ²ΡΠΈΠ΅ΡΡ Π·Π° ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠΎΡΡΡ Π² ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 2015 ΠΏΠΎ 2018 Π³. ΠΠ°Π½Π½ΡΠ΅ ΠΏΠΎΠ»ΡΡΠ΅Π½Ρ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ±ΠΎΡΠ° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈΠ· ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΊΠ°ΡΡ ΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ½ΠΎΠ³ΠΎ Π±ΠΎΠ»ΡΠ½ΠΎΠ³ΠΎ (ΡΠΎΡΠΌΠ° 003/Ρ) ΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΊΠ°ΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°, ΠΏΠΎΠ»ΡΡΠ°ΡΡΠ΅Π³ΠΎ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΡΡ ΠΏΠΎΠΌΠΎΡΡ Π² Π°ΠΌΠ±ΡΠ»Π°ΡΠΎΡΠ½ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΡΡ
(ΡΠΎΡΠΌΠ° 025/Ρ). ΠΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π° β Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ.
Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π ΡΠ°ΠΌΠΊΠ°Ρ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ»ΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ 292 ΠΊΠ°ΡΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΠΎΠ±ΡΠ°ΡΠΈΠ²ΡΠΈΡ
ΡΡ Π·Π° ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠΎΡΡΡ. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ°ΡΡΠΎ β Π² 37,6% ΡΠ»ΡΡΠ°Π΅Π² β Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π°Π½ΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΡΠΌΠΈ Π±ΠΎΡΠΎΠ΄Π°Π²ΠΊΠ°ΠΌΠΈ ΠΈ Π Π¨Π ΠΏΡΠΈ Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΠΎΠΌ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π²ΡΡΠ²Π»ΡΠ»ΡΡ Π²ΠΈΡΡΡ ΠΏΠ°ΠΏΠΈΠ»Π»ΠΎΠΌΡ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° (ΠΠΠ§) 16-Π³ΠΎ ΡΠΈΠΏΠ°. Π’Π°ΠΊΠΆΠ΅ ΡΠ°ΡΡΠΎ Π²ΡΡΡΠ΅ΡΠ°Π»ΠΈΡΡ ΠΠΠ§ 6/18/11/31/51/52. Π 43,2% ΡΠ»ΡΡΠ°Π΅Π² ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈΡΡ ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ Π΄Π²Π° ΠΈ Π±ΠΎΠ»Π΅Π΅ ΡΠΈΠΏΠΎΠ² ΠΠΠ§, ΠΏΡΠΈ ΡΡΠΎΠΌ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ°ΡΡΡΠΌΠΈ ΡΠΎΡΠ΅ΡΠ°Π½ΠΈΡΠΌΠΈ Π±ΡΠ»ΠΈ ΠΠΠ§16 ΠΈ ΠΠΠ§18, ΠΠΠ§6 ΠΈ ΠΠΠ§16, ΠΠΠ§6 ΠΈ ΠΠΠ§11. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠ°ΡΡΠΎΡΡ ΡΠΊΡΠΈΠ½ΠΈΠ½Π³Π° Π½Π° Π Π¨Π ΠΈ ΠΏΠΎΡΠ΅ΡΠ΅Π½ΠΈΡ Π²ΡΠ°ΡΠ°-Π³ΠΈΠ½Π΅ΠΊΠΎΠ»ΠΎΠ³Π° Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 5 Π»Π΅Ρ Π΄ΠΎ ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΡ Π΄ΠΈΠ°Π³Π½ΠΎΠ·Π° ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ ΡΡΠ΅Π΄ΠΈ Π»ΠΈΡ, Π½Π΅ ΠΏΡΠΎΡ
ΠΎΠ΄ΠΈΠ²ΡΠΈΡ
ΡΠΊΡΠΈΠ½ΠΈΠ½Π³ Π½Π° Π Π¨Π, ΠΈΠ»ΠΈ ΠΏΡΠΎΡΠ΅Π΄ΡΠΈΡ
Π΅Π³ΠΎ ΠΏΡΠΈ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΈΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ, ΡΠΈΡΠΊ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ Π΄ΠΈΠ°Π³Π½ΠΎΠ·Π° Π½Π° IIIV ΡΡΠ°Π΄ΠΈΠΈ Π±ΡΠ» Π² 5,2 ΡΠ°Π·Π° Π²ΡΡΠ΅, ΡΠ΅ΠΌ ΡΡΠ΅Π΄ΠΈ Π»ΠΈΡ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΏΡΠΎΡ
ΠΎΠ΄ΠΈΠ»ΠΈ ΡΠ΅ΡΠ²ΠΈΠΊΠ°Π»ΡΠ½ΡΠΉ ΡΠΊΡΠΈΠ½ΠΈΠ½Π³ 2 Π³ΠΎΠ΄Π° Π½Π°Π·Π°Π΄ ΠΈΠ»ΠΈ 1 ΡΠ°Π· Π² Π³ΠΎΠ΄ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΡ
5 Π»Π΅Ρ. Π‘ΡΠ΅Π΄ΠΈ Π²ΡΠ΅Ρ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ Π°Π½ΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΡΠΌΠΈ Π±ΠΎΡΠΎΠ΄Π°Π²ΠΊΠ°ΠΌΠΈ, ΠΈΠΌΠ΅Π²ΡΠΈΡ
ΠΏΠΎ Π΄Π²Π° ΠΈ Π±ΠΎΠ»Π΅Π΅ ΠΏΠΎΠ»ΠΎΠ²ΡΡ
ΠΏΠ°ΡΡΠ½Π΅ΡΠ° Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 1 Π³ΠΎΠ΄Π°, ΠΎ ΡΠ΅Π³ΡΠ»ΡΡΠ½ΠΎΠΌ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π±Π°ΡΡΠ΅ΡΠ½ΠΎΠΉ ΠΊΠΎΠ½ΡΡΠ°ΡΠ΅ΠΏΡΠΈΠΈ (ΠΏΡΠ΅Π·Π΅ΡΠ²Π°ΡΠΈΠ²ΠΎΠ²) ΠΏΡΠΈ ΠΏΠΎΠ»ΠΎΠ²ΠΎΠΌ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ΅ ΡΠΎΠΎΠ±ΡΠΈΠ»ΠΈ 13,5%, ΠΎ Π½Π΅ΡΠ΅Π³ΡΠ»ΡΡΠ½ΠΎΠΌ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ β 61,5%; 25,0% ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Π²ΠΎΠΎΠ±ΡΠ΅ Π½Π΅ Π·Π°Π΄ΡΠΌΡΠ²Π°Π»ΠΈΡΡ ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π°Ρ
ΠΏΡΠ΅Π΄ΠΎΡ
ΡΠ°Π½Π΅Π½ΠΈΡ.
ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΠΊΠ»ΠΈΠ½ΠΈΠΊΠΎ-ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΏΠ°ΠΏΠΈΠ»Π»ΠΎΠΌΠ°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΠΎΠ²Π°ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ Π½ΠΎΠ²ΡΡ
ΠΈ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΡ
ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΡΠΈΡΠΎΠΊΠΎΠ³ΠΎ ΡΠΏΠ΅ΠΊΡΡΠ° ΠΠΠ§-Π°ΡΡΠΎΡΠΈΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ
Systemic Essential Metal and Metalloid Levels in Patients with Benign Breast Disease and Breast Cancer
The objective of the present study is evaluation of serum and hair levels of essential metals and metalloids in women with benign breast disease and breast cancer in order to define similar and distinct patterns that may mediate the link between these pathologies. A total of 310 adult women aged 20β80Β years old were enrolled in the present study. Of those, 103 patients had benign (fibrocystic) breast disease, 107 patients had breast cancer (stage II), and 100 women were healthy and with absence of breast pathology. Trace metal and metalloid levels in hair and serum were evaluated by inductively coupled argon plasma mass-spectrometry (ICP-MS). The data demonstrate that breast cancer patients were characterized by significantly higher hair Cr and V levels, as well as reduced Cu and Mn content as compared to both benign breast disease patients and controls. In contrast, serum Cu levels in women with breast cancer exceeded those in the controls and benign breast disease cases. Patients with both benign and malignant breast tumors were characterized by lower serum Mn levels as compared to the control values. Serum Cu/Zn and especially Cu/Mn were found to be significantly increased in cancer patients. Significantly reduced hair and serum Se levels were noted only in women with fibrocystic disease. Based on the analysis of two biosamples, it is proposed that malignant breast tumor development is associated with the reduction of systemic Mn and Zn levels, and a concomitant elevation of Cu concentrations. Β© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature
Genome-wide methylotyping resolves breast cancer epigenetic heterogeneity and suggests novel therapeutic perspectives
Aim: To provide a breast cancer (BC) methylotype classification by genome-wide CpG islands bisulfite DNA sequencing. Materials & methods: XmaI-reduced representation bisulfite sequencing DNA methylation sequencing method was used to profile DNA methylation of 110 BC samples and 6 normal breast samples. Intrinsic DNA methylation BC subtypes were elicited by unsupervised hierarchical cluster analysis, and cluster-specific differentially methylated genes were identified. Results & conclusion: Overall, six distinct BC methylotypes were identified. BC cell lines constitute a separate group extremely highly methylated at the CpG islands. In turn, primary BC samples segregate into two major subtypes, highly and moderately methylated. Highly and moderately methylated superclusters, each incorporate three distinct epigenomic BC clusters with specific features, suggesting novel perspectives for personalized therapy. Β© 2019 Alexander Tanas et al