169 research outputs found

    Republican registry of primary immune deficiencies in the chuvash republic and description of postvaccinal immunity disorders in a pregnant patient with common variable immune deficiency

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    In recent years, primary immunodeficiencies have turned from the class of rare diseases to the category of more common disorders which may be encountered by doctors of any clinical discipline. The first case of primary immunodeficiency disorder (PID) in Chuvashia was detected in 1993. Since that time, the Department of Internal Diseases with the Course of Clinical Immunology at the I. Ulyanov Chuvash State University registered all the cases of PID diagnosed in the region, introducing them into the Republican Registry of PID. The study was aimed for searching epidemiological indexes, clinical and laboratory manifestations of PID in Chuvash region. The study was based on the patient data obtained by retrospective analysis of 85 case histories of PID patients, treated at different departments of the Republican Clinical Hospital, and the City Chuvash Pediatric Clinical Hospital of Public Health Ministry in 2000-2019, as well as on 49 outpatient records of the patients included into the Regional PID Registry. Various forms of PIDs were diagnosed according to the criteria developed by the European Society for Immunodeficiency and the Pan-American Group on Immunodeficiency (1999). The results of this study showed that the incidence of PID in the Chuivash Region is 3.4:100,000. The incidence of common variable immune deficiency (CVID), the most common form of PID in the region, was 1.58 per 100,000 population. The average age at the time of CVID diagnosis in Chuvash patients was 30.4±16.1 years, and the age of CVID debut was 11.3±15.0 years. The delay in proper diagnosis from the moment of clinical manifestation of CVID was, on average, 17.9 years in the region. At the time of CVID diagnosis, the patients showed marked decrease in the levels of 3 or 2 immunoglobulin classes (IgG and IgA), and T-helper cell contents (CD3+CD4+) in peripheral blood. Prevalence of selective IgA deficiency with сlinical symptoms was 0.83 per 100,000 population of the region, and the incidence of the asymptomatic form of this PID was 1 : 167. In patients with selective IgA deficiency, there were also disorders in the T cell system manifesting as decreased relative number of cytotoxic T-cells as well as elevated IgG and IgM levels. The age of diagnosis of X-linked agammaglobulinemia in the region was 3.5±3.0 years. In addition to disturbances of humoral adaptive immunity in children with this disease, a decrease in absolute T cell numbers was detected. In conclusion, the article describes disturbances of postvaccinal immunity in a pregnant patient with CVID, with asymptomatic clinical course, thus leading to false interpretation of the serological markers of TORCH infections and wrong strategy of pregnancy management

    Course of COVID-19 in Patients with Inflammatory Bowel Disease: Regional Experience

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    Aim: to study the course of COVID-19 in patients with inflammatory bowel diseases (IBD) using the example of the region of the Republic of Tatarstan.Material and methods. The study included 101 patients diagnosed with IBD and COVID-19, who were observed in two infectious diseases hospitals in Kazan (Republican Clinical Hospital of the Ministry of Health of the Republic of Tatarstan and City Clinical Hospital No. 7) and on an outpatient basis from April 2020 to March 2022. All patients underwent physical examination, laboratory and instrumental diagnostic methods, including a PCR test for SARSCoV-2. Chest computed tomography was performed in patients with clinical signs of moderate to severe COVID-19.Results. Ulcerative colitis (UC) was diagnosed in 60 (59.4 %) patients, Crohn's disease (CD) β€” in 41 (40.6 %) patients. The mean age of the patients was 41.0 Β± 14.7 years, of which 59 (58.4 %) were men and 42 (41.6 %) were women. A comparative analysis of patients with and without IBD and CT-verified lung disease was carried out. It was found that the development of viral pneumonia was influenced by age over 55 years (39.2 Β± 9.7 vs. 46.3 Β± 10.6, p < 0.05), increased Body Mass Index (BMI) (23.1 Β± 5.35 vs. 30.25 Β± 6.17, p < 0.05), hypertension (6 (8.3 %) vs. 8 (27.6 %), p < 0.05), diabetes mellitus (2 (2.7 %) vs. 5 (17.2 %), p < 0.05), the use of corticosteroids in the treatment of IBD (8 (11.1 %) vs. 10 (34.5 %), p < 0.05). In a comparative analysis of patients with IBD and COVID-19 from the SECURE-IBD database and own data, it was found that the average age of patients was comparable (42.7 vs 41.0). At the same time, in our group of male patients, there were slightly more people with DM, increased BMI, and an active course of IBD. The proportion of hospitalized patients was higher. In our cohort, there were fewer patients receiving biological therapy, but more patients on 5-aminosalicylic acid (5-ASA) and systemic corticosteroids. At the same time, lethal outcomes were comparable.Conclusion. In patients with IBD, the development of viral pneumonia was influenced by known risk factors for COVID-19: age over 55 years (p < 0.05, odds ratio (OR) 3.153), increased BMI (p < 0.05, OR 1.667), hypertensionΒ  (p < 0.05, OR 2.724), diabetes (p < 0.05, OR 1.489), as well as the use of systemic corticosteroids (p < 0.05, OR 1.5)

    Defensin-like peptides in wheat analyzed by whole-transcriptome sequencing: a focus on structural diversity and role in induced resistance

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    Antimicrobial peptides (AMPs) are the main components of the plant innate immune system. Defensins represent the most important AMP family involved in defense and non-defense functions. In this work, global RNA sequencing and de novo transcriptome assembly were performed to explore the diversity of defensin-like (DEFL) genes in the wheat Triticum kiharae and to study their role in induced resistance (IR) mediated by the elicitor metabolites of a non-pathogenic strain FS-94 of Fusarium sambucinum. Using a combination of two pipelines for DEFL mining in transcriptome data sets, as many as 143 DEFL genes were identified in T. kiharae, the vast majority of them represent novel genes. According to the number of cysteine residues and the cysteine motif, wheat DEFLs were classified into ten groups. Classical defensins with a characteristic 8-Cys motif assigned to group 1 DEFLs represent the most abundant group comprising 52 family members. DEFLs with a characteristic 4-Cys motif CX{3,5}CX{8,17}CX{4,6}C named group 4 DEFLs previously found only in legumes were discovered in wheat. Within DEFL groups, subgroups of similar sequences originated by duplication events were isolated. Variation among DEFLs within subgroups is due to amino acid substitutions and insertions/deletions of amino acid sequences. To identify IR-related DEFL genes, transcriptional changes in DEFL gene expression during elicitor-mediated IR were monitored. Transcriptional diversity of DEFL genes in wheat seedlings in response to the fungus Fusarium oxysporum, FS-94 elicitors, and the combination of both (elicitors + fungus) was demonstrated, with specific sets of up- and down-regulated DEFL genes. DEFL expression profiling allowed us to gain insight into the mode of action of the elicitors from F. sambucinum. We discovered that the elicitors up-regulated a set of 24 DEFL genes. After challenge inoculation with F. oxysporum, another set of 22 DEFLs showed enhanced expression in IR-displaying seedlings. These DEFLs, in concert with other defense molecules, are suggested to determine enhanced resistance of elicitor-pretreated wheat seedlings. In addition to providing a better understanding of the mode of action of the elicitors from FS-94 in controlling diseases, up-regulated IR-specific DEFL genes represent novel candidates for genetic transformation of plants and development of pathogen-resistantΒ crops

    Insights into substrate stabilization from snapshots of the peptidyl transferase center of the intact 70S ribosome

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    Protein synthesis is catalyzed in the peptidyl transferase center (PTC), located in the large (50S) subunit of the ribosome. No high-resolution structure of the intact ribosome has contained a complete active site including both A- and P-site tRNAs. In addition, although past structures of the 50S subunit have found no ordered proteins at the PTC, biochemical evidence suggests that specific proteins are capable of interacting with the 3β€² ends of tRNA ligands. Here we present structures, at 3.6-Γ… and 3.5-Γ… resolution respectively, of the 70S ribosome in complex with A- and P-site tRNAs that mimic pre- and post-peptidyl-transfer states. These structures demonstrate that the PTC is very similar between the 50S subunit and the intact ribosome. They also reveal interactions between the ribosomal proteins L16 and L27 and the tRNA substrates, helping to elucidate the role of these proteins in peptidyl transfer

    Down-regulation of TM4SF is associated with the metastatic potential of gastric carcinoma TM4SF members in gastric carcinoma

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    <p>Abstract</p> <p>Background</p> <p>The aim of this study was to clarify the clinical significance of TM4SF members CD9, CD63 and CD82 in human gastric carcinoma.</p> <p>Methods</p> <p>By employing RT-PCR and immunohistochemistry, we studied the expression of CD9, CD63 and CD82 in 49 paired tissue specimens of normal gastric mucosa and carcinoma. All tissues were obtained from patients who underwent curative surgery.</p> <p>Results</p> <p>All normal gastric epithelium and gastric ulcer tissues strongly expressed transcripts and proteins of CD9, CD63 and CD82 as compared with corresponding controls. We found a significant correlation between CD63 mRNA level and different pM statuses (P = 0.036). Carcinomas in M0 stage revealed a stronger expression of CD63 than carcinomas in M1 stage. Expression of CD9 protein was found significantly stronger in pN0, pM0 than in advanced pN stages (P = 0.03), pM1 (P = 0.013), respectively. We found the relationship between CD63 expression, gender (p = 0.09) and nodal status (p = 0.028), respectively. Additionally, advanced and metastasized tumor tissues revealed significantly down-regulated CD82 protein expression (p = 0.033 and p = 0, respectively), which correlated with the tumor pTNM stage (p = 0.001).</p> <p>Conclusion</p> <p>The reduction of CD9, CD63 and CD82 expression are indicators for the metastatic potential of gastric carcinoma cells. Unlike their expression in other tumor types, the constitutive expression of CD63 may indicate that this factor does play a direct role in human gastric carcinogenesis.</p

    CXCR4/CXCL12 expression and signalling in kidney cancer

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    CXCL12 (SDF-1), a CXC-chemokine, and its specific receptor, CXCR4, have recently been shown to be involved in tumourgenesis, proliferation and angiogenesis. Therefore, we analysed CXCL12Ξ±/CXCR4 expression and function in four human kidney cancer cell lines (A-498, CAKI-1, CAKI-2, HA-7), 10 freshly harvested human tumour samples and corresponding normal kidney tissue. While none of the analysed tumour cell lines expressed CXCL12Ξ±, A-498 cells were found to express CXCR4. More importantly, real-time RT–PCR analysis of 10 tumour samples and respective adjacent normal kidney tissue disclosed a distinct and divergent downregulation of CXCL12Ξ± and upregulation of CXCR4 in primary tumour tissue. To prove that the CXCR4 protein is functionally active, rhCXCL12Ξ± was investigated for its ability to induce changes of intracellular calcium levels in A-498 cells. Moreover, we used cDNA expression arrays to evaluate the biological influence of CXCL12Ξ±. Comparing gene expression profiles in rhCXCL12Ξ± stimulated vs unstimulated A-498 kidney cancer cells revealed specific regulation of 31 out of 1176 genes tested on a selected human cancer array, with a prominent stimulation of genes involved in cell-cycle regulation and apoptosis. The genetic changes reported here should provide new insights into the developmental paths leading to tumour progression and may also aid the design of new approaches to therapeutic intervention

    ΠΠ˜Π—ΠšΠžΠ”Π˜Π€Π€Π•Π Π•ΠΠ¦Π˜Π ΠžΠ’ΠΠΠΠ«Π• ΠΠ•Π™Π ΠžΠ­ΠΠ”ΠžΠšΠ Π˜ΠΠΠ«Π• ΠΠžΠ’ΠžΠžΠ‘Π ΠΠ—ΠžΠ’ΠΠΠ˜Π― Π–Π•Π›Π£Π”ΠžΠ§ΠΠž-ΠšΠ˜Π¨Π•Π§ΠΠžΠ“Πž ВРАКВА И ΠŸΠžΠ”Π–Π•Π›Π£Π”ΠžΠ§ΠΠžΠ™ Π–Π•Π›Π•Π—Π«. ΠžΠ‘ΠžΠ‘Π•ΠΠΠžΠ‘Π’Π˜ Π‘ΠžΠ’Π Π•ΠœΠ•ΠΠΠžΠ™ ΠšΠ›ΠΠ‘Π‘Π˜Π€Π˜ΠšΠΠ¦Π˜Π˜, Π”Π˜ΠΠ“ΠΠžΠ‘Π’Π˜ΠšΠ˜ И Π›Π•Π§Π•ΠΠ˜Π―

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    Poorly differentiated gastroenteropancreatic neuroendocrine neoplasms (GEP NENs) are rare malignancies, most of which are characterized by aggressiveness, a tendency to rapid metastasis and an unfavorable prognosis even when localized. In 2017 World Health Organization (WHO) updated classification of GEP NENs and recognized the category of well-differentiated pancreatic NET G3, associated with Ki‑67 index usually over 20%. The upper level of Ki‑67 is not defined. Usually it is 55%. Highgrade poorly differentiated pancreatic NENs are defined as pancreatic neuroendocrine carcinomas (panNECs). Although the NET G3 category is recognized for pancreatic neuroendocrine neoplasms only, many specialists consider it reasonable to apply this term to all well-differentiated GEP NETs with Ki‑67 index in the 20 to 55 percent range. Clinical behavior and therapeutic approaches for advanced GEP NECs and NETs G3 are different. Standard palliative chemotherapy for GEP NECs consists of cisplatin or carboplatin combined with etoposide. The second-line regimens include irinotecan-, oxaliplatin, fluoropyrimidine- and temozolomide-based regimens. Temozolomide-based chemotherapy regimens, as well as targeted therapy are more preferable as first line therapy for patients with NETs G3. The platinum-based chemotherapy regimens are considered at the time of disease progression. Further clinical studies with the inclusion of much more patients will determine the optimal treatment strategy for this category of patients.НизкодиффСрСнцированныС нСйроэндокринныС новообразования (НЭН) ΠΆΠ΅Π»ΡƒΠ΄ΠΎΡ‡Π½ΠΎ-ΠΊΠΈΡˆΠ΅Ρ‡Π½ΠΎΠ³ΠΎ Ρ‚Ρ€Π°ΠΊΡ‚Π° (Π–ΠšΠ’) ΠΈ ΠΏΠΎΠ΄ΠΆΠ΅Π»ΡƒΠ΄ΠΎΡ‡Π½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ‹ (ΠŸΠ–) – гСтСрогСнная Π³Ρ€ΡƒΠΏΠΏΠ° Ρ€Π΅Π΄ΠΊΠΈΡ… злокачСствСнных ΠΎΠΏΡƒΡ…ΠΎΠ»Π΅ΠΉ, Π±ΠΎΠ»ΡŒΡˆΠΈΠ½ΡΡ‚Π²ΠΎ ΠΈΠ· ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΡŽΡ‚ΡΡ агрСссивным Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ΠΌ, ΡΠΊΠ»ΠΎΠ½Π½ΠΎΡΡ‚ΡŒΡŽ ΠΊ быстрому ΠΌΠ΅Ρ‚Π°ΡΡ‚Π°Π·ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΡŽ ΠΈ нСблагоприятным ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΎΠΌ Π΄Π°ΠΆΠ΅ ΠΏΡ€ΠΈ Π»ΠΎΠΊΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½Π½Ρ‹Ρ… стадиях Π±ΠΎΠ»Π΅Π·Π½ΠΈ. Π’ 2017 Π³. ВсСмирная организация здравоохранСния (Π’ΠžΠ—) внСсла уточнСния Π² ΠΊΠ»Π°ΡΡΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ НЭН ΠΏΠΎΠ΄ΠΆΠ΅Π»ΡƒΠ΄ΠΎΡ‡Π½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ‹, Π²Ρ‹Π΄Π΅Π»ΠΈΠ² Π² ΡΠ°ΠΌΠΎΡΡ‚ΠΎΡΡ‚Π΅Π»ΡŒΠ½ΡƒΡŽ Π³Ρ€ΡƒΠΏΠΏΡƒ высокодиффСрСнцированныС панкрСатичСскиС НЭО G3 (панНЭО G3) с индСксом ΠΏΡ€ΠΎΠ»ΠΈΡ„Π΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠΉ активности Ki‑67&gt;20%. Π’Π΅Ρ€Ρ…Π½ΠΈΠΉ ΠΏΠΎΡ€ΠΎΠ³ΠΎΠ²Ρ‹ΠΉ ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ Ki‑67 Π² этой Π³Ρ€ΡƒΠΏΠΏΠ΅ Ρ‚ΠΎΡ‡Π½ΠΎ Π½Π΅ установлСн. ΠžΠ±Ρ‹Ρ‡Π½ΠΎ ΠΎΠ½ составляСт 55%. НизкодиффСрСнцированныС панкрСатичСскиС НЭН высокой стСпСни злокачСствСнности ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Ρ‹ Ρ‚Π΅Ρ€ΠΌΠΈΠ½ΠΎΠΌ «панкрСатичСский нСйроэндокринный Ρ€Π°ΠΊΒ» (панНЭР G3). НСсмотря Π½Π° Ρ‚ΠΎ Ρ‡Ρ‚ΠΎ катСгория НЭО G3 ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ принята Ρ‚ΠΎΠ»ΡŒΠΊΠΎ для панкрСатичСских НЭН, ΠΌΠ½ΠΎΠ³ΠΈΠ΅ спСциалисты ΠΏΠΎ Π»Π΅Ρ‡Π΅Π½ΠΈΡŽ НЭО ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΡŽΡ‚ этот Ρ‚Π΅Ρ€ΠΌΠΈΠ½ для всСх высокодиффСрСнцированных НЭО Π–ΠšΠ’ ΠΈ ΠŸΠ– с индСксом ΠΏΡ€ΠΎΠ»ΠΈΡ„Π΅Ρ€Π°Ρ†ΠΈΠΈ Ki‑67 Π² Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π΅ с 20 Π΄ΠΎ 55%. ΠšΠ»ΠΈΠ½ΠΈΡ‡Π΅ΡΠΊΠΎΠ΅ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΈ тСрапСвтичСскиС ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Ρ‹ ΠΏΡ€ΠΈ распространСнных НЭО G3 ΠΈ НЭР G3 Π–ΠšΠ’ ΠΈ ΠŸΠ– ΠΎΡ‚Π»ΠΈΡ‡Π°ΡŽΡ‚ΡΡ. Основой лСчСния НЭР являСтся химиотСрапия ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Ρ†ΠΈΠ΅ΠΉ цитостатичСских ΠΏΡ€Π΅ΠΏΠ°Ρ€Π°Ρ‚ΠΎΠ² этопозида ΠΈ ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄Π½Ρ‹Ρ… ΠΏΠ»Π°Ρ‚ΠΈΠ½Ρ‹. Π’ΠΎ Π²Ρ‚ΠΎΡ€ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ ΠΌΠΎΠ³ΡƒΡ‚ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒΡΡ Ρ€Π΅ΠΆΠΈΠΌΡ‹ Π½Π° основС ΠΈΡ€ΠΈΠ½ΠΎΡ‚Π΅ΠΊΠ°Π½Π°, оксалиплатина, Ρ„Ρ‚ΠΎΡ€ΠΏΠΈΡ€ΠΈΠΌΠΈΠ΄ΠΈΠ½ΠΎΠ², Ρ‚Π΅ΠΌΠΎΠ·ΠΎΠ»ΠΎΠΌΠΈΠ΄Π°. Π Π΅ΠΆΠΈΠΌΡ‹ Ρ…ΠΈΠΌΠΈΠΎΡ‚Π΅Ρ€Π°ΠΏΠΈΠΈ Π½Π° основС Ρ‚Π΅ΠΌΠΎΠ·ΠΎΠ»ΠΎΠΌΠΈΠ΄Π°, Π° Ρ‚Π°ΠΊΠΆΠ΅ таргСтная тСрапия ΡΠ²Π»ΡΡŽΡ‚ΡΡ Π±ΠΎΠ»Π΅Π΅ ΠΏΡ€Π΅Π΄ΠΏΠΎΡ‡Ρ‚ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌΠΈ Π² качСствС ΠΏΠ΅Ρ€Π²ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ для Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ… высокодиффСрСнцированными НЭО G3. ΠŸΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ платиносодСрТащих Ρ€Π΅ΠΆΠΈΠΌΠΎΠ² Ρ…ΠΈΠΌΠΈΠΎΡ‚Π΅Ρ€Π°ΠΏΠΈΠΈ ΠΎΠΏΡ€Π°Π²Π΄Π°Π½ΠΎ Π² случаС нСэффСктивности ΠΏΡ€Π΅Π΄ΡˆΠ΅ΡΡ‚Π²ΡƒΡŽΡ‰Π΅ΠΉ Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ. Π”Π°Π»ΡŒΠ½Π΅ΠΉΡˆΠΈΠ΅ клиничСскиС исслСдования с Π²ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅ΠΌ большСго количСства ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² позволят ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΠΈΡ‚ΡŒ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½ΡƒΡŽ Ρ‚Π°ΠΊΡ‚ΠΈΠΊΡƒ лСчСния этой ΠΊΠ°Ρ‚Π΅Π³ΠΎΡ€ΠΈΠΈ Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ…

    KAI1 suppresses HIF-1Ξ± and VEGF expression by blocking CDCP1-enhanced Src activation in prostate cancer

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    <p>Abstract</p> <p>Background</p> <p>KAI1 was initially identified as a metastasis-suppressor gene in prostate cancer. It is a member of the tetraspan transmembrane superfamily (TM4SF) of membrane glycoproteins. As part of a tetraspanin-enriched microdomain (TEM), KAI1 inhibits tumor metastasis by negative regulation of Src. However, the underlying regulatory mechanism has not yet been fully elucidated. CUB-domain-containing protein 1 (CDCP1), which was previously known as tetraspanin-interacting protein in TEM, promoted metastasis via enhancement of Src activity. To better understand how KAI1 is involved in the negative regulation of Src, we here examined the function of KAI1 in CDCP1-mediated Src kinase activation and the consequences of this process, focusing on HIF-1 Ξ± and VEGF expression.</p> <p>Methods</p> <p>We used the human prostate cancer cell line PC3 which was devoid of KAI1 expression. Vector-transfected cells (PC3-GFP clone #8) and KAI1-expressing PC3 clones (PC3-KAI1 clone #5 and #6) were picked after stable transfection with KAI1 cDNA and selection in 800 <it>ΞΌ</it>g/ml G418. Protein levels were assessed by immunoblotting and VEGF reporter gene activity was measured by assaying luciferase activitiy. We followed tumor growth <it>in vivo </it>and immunohistochemistry was performed for detection of HIF-1, CDCP1, and VHL protein level.</p> <p>Results</p> <p>We demonstrated that Hypoxia-inducible factor 1Ξ± (HIF-1Ξ±) and VEGF expression were significantly inhibited by restoration of KAI1 in PC3 cells. In response to KAI1 expression, CDCP1-enhanced Src activation was down-regulated and the level of von Hippel-Lindau (VHL) protein was significantly increased. In an <it>in vivo </it>xenograft model, KAI1 inhibited the expression of CDCP1 and HIF-1Ξ±.</p> <p>Conclusions</p> <p>These novel observations may indicate that KAI1 exerts profound metastasis-suppressor activity in the tumor malignancy process via inhibition of CDCP1-mediated Src activation, followed by VHL-induced HIF-1Ξ± degradation and, ultimately, decreased VEGF expression.</p

    Π˜ΠΌΠΌΡƒΠ½ΠΎΠ»ΠΎΠ³ΠΈΡ‡Π΅ΡΠΊΠΈΠ΅ ΠΌΠ°Ρ€ΠΊΠ΅Ρ€Ρ‹ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·Π° ΠΎΡ‚Π²Π΅Ρ‚Π° Π½Π° ΠΈΠΌΠΌΡƒΠ½ΠΎΡ‚Π΅Ρ€Π°ΠΏΠΈΡŽ ΠΏΡ€ΠΈ Π½Π΅ΠΌΠ΅Π»ΠΊΠΎΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½ΠΎΠΌ Ρ€Π°ΠΊΠ΅ Π»Π΅Π³ΠΊΠΎΠ³ΠΎ

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    Itroduction. Immune checkpoint inhibitors have become the standard of care for patients with advanced non-small cell lung cancer. However, despite the determination of programmed death-ligand 1 expression in clinical practice, which determines the effectiveness of therapy, up to 80 % of patients with non-small cell lung cancer do not respond to treatment.The study objective – investigation of the prognostic role of clinical and immunological markers during immune checkpoint inhibitor monotherapy in β‰₯2 lines in patients with advanced non-small cell lung cancer.Materials and methods. The study included 45 patients with advanced non-small cell lung cancer receiving programmed cell death 1 / programmed death-ligand 1 inhibitors in monotherapy in 2 and subsequent lines (Group 1), as well as 30 patients with advanced non-small cell lung cancer receiving first-line chemotherapy (Group 2). All patients from 2 groups did not have autoimmune diseases before starting treatment. The determination of autoantibodies, Ξ²-2-microglobulin, neopterin, interleukin 6, interleukin 18 and the allelic variant of HLA-DRB1 in patients in the Group 1 was carried out 2 months after the start of therapy, and in the Group 2 – before the start of the next chemotherapy cycle.Results. In Group 1, the presence of EGFR / ALK mutations is an independent predictor of shorter progression-free survival (p = 0.018). Also, in the univariate analysis, neutrophil-lymphocyte ratio &lt;5 before immune checkpoint inhibitors (p = 0.009) and the appearance of immune-related adverse events (p = 0.038) are associated with long-term progressionfree survival. In Group 1, Ξ²-2-microglobulin was lower in patients with a response duration of β‰₯6 months than with a progression &lt;6 months: 1.7 mg / L and 2.9 mg / L, respectively (p &lt;0.0001). Patients receiving immune checkpoint inhibitors with a Ξ²-2-microglobulin level β‰₯2.5 mg / L have a shorter progression-free survival than patients with a marker value &lt;2.5 mg / L: 168 days and the value is not reached, respectively (p = 0.017). In response duration β‰₯6 months neopterin value was lower than in disease progression: 8.6 nmol / l and 13.4 nmol / L, respectively (p &lt;0,0001). Progression-free survival was lower in patients with neopterin β‰₯12 nmol / L than patients with neopterin &lt;12 nmol / L: median was 164 days and the value was not reached, respectively (p = 0.0007). Based on the results of multivariate analysis, Ξ²-2-microglobulin β‰₯2.5 mg / L (p = 0.006) and neopterin β‰₯12 nmol / L (p = 0.027) were independent predictors of shorter progression-free survival. Low levels of interleukin 6 and interleukin 18, as well as antibodies to thyroperoxidase, are associated with a response of β‰₯6 months. HLA-DRB1*03 was associated with a duration of response of β‰₯6 months, as well as a longer progression-free survival compared with other allelic variants. The levels of Ξ²-2-microglobulin, neopterin, interleukin 6, interleukin 18 were higher in patients in Group 1 than in patients in Group 2 (p &lt;0.0001).Conclusion. Immunological markers can serve as promising prognosis markers in patients with advanced non-small cell lung cancer during immunotherapy.Π’Π²Π΅Π΄Π΅Π½ΠΈΠ΅. ВСрапия ΠΈΠ½Π³ΠΈΠ±ΠΈΡ‚ΠΎΡ€Π°ΠΌΠΈ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΈΠΌΠΌΡƒΠ½Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π° стала стандартом лСчСния ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с распространСнным Π½Π΅ΠΌΠ΅Π»ΠΊΠΎΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹ΠΌ Ρ€Π°ΠΊΠΎΠΌ Π»Π΅Π³ΠΊΠΎΠ³ΠΎ. Однако, нСсмотря Π½Π° выявлСниС Π² клиничСской ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΠ΅ экспрСссии Π»ΠΈΠ³Π°Π½Π΄Π° Ρ€Π΅Ρ†Π΅ΠΏΡ‚ΠΎΡ€Π° ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠΈΡ€ΡƒΠ΅ΠΌΠΎΠΉ ΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½ΠΎΠΉ Π³ΠΈΠ±Π΅Π»ΠΈ 1, ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡΡŽΡ‰Π΅ΠΉ ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ, Π΄ΠΎ 80 % ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с Π΄Π°Π½Π½ΠΎΠΉ ΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ Π½Π΅ ΠΎΡ‚Π²Π΅Ρ‡Π°ΡŽΡ‚ Π½Π° Π»Π΅Ρ‡Π΅Π½ΠΈΠ΅.ЦСль исслСдования – ΠΎΡ†Π΅Π½ΠΈΡ‚ΡŒ ΠΏΡ€ΠΎΠ³Π½ΠΎΡΡ‚ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ Ρ€ΠΎΠ»ΡŒ клиничСских ΠΈ иммунологичСских ΠΌΠ°Ρ€ΠΊΠ΅Ρ€ΠΎΠ² ΠΏΡ€ΠΈ использовании ΠΈΠ½Π³ΠΈΠ±ΠΈΡ‚ΠΎΡ€ΠΎΠ² ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΈΠΌΠΌΡƒΠ½Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π° Π² ΠΌΠΎΠ½ΠΎΡ€Π΅ΠΆΠΈΠΌΠ΅ Π² β‰₯2 линиях распространСнного Π½Π΅ΠΌΠ΅Π»ΠΊΠΎΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½ΠΎΠ³ΠΎ Ρ€Π°ΠΊΠ° Π»Π΅Π³ΠΊΠΎΠ³ΠΎ.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. В исслСдованиС Π²ΠΊΠ»ΡŽΡ‡Π΅Π½Ρ‹ 45 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с распространСнным Π½Π΅ΠΌΠ΅Π»ΠΊΠΎΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹ΠΌ Ρ€Π°ΠΊΠΎΠΌ Π»Π΅Π³ΠΊΠΎΠ³ΠΎ, ΠΏΠΎΠ»ΡƒΡ‡Π°Π²ΡˆΠΈΠ΅ ΠΈΠ½Π³ΠΈΠ±ΠΈΡ‚ΠΎΡ€Ρ‹ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΈΠΌΠΌΡƒΠ½Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π° (1-я Π³Ρ€ΡƒΠΏΠΏΠ°), Π° Ρ‚Π°ΠΊΠΆΠ΅ 30 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с Π΄Π°Π½Π½ΠΎΠΉ ΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΌ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π² 1-ΠΉ Π»ΠΈΠ½ΠΈΠΈ Ρ…ΠΈΠΌΠΈΠΎΡ‚Π΅Ρ€Π°ΠΏΠΈΡŽ (2-я Π³Ρ€ΡƒΠΏΠΏΠ°). Π£ всСх Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Π΄ΠΎ Π½Π°Ρ‡Π°Π»Π° лСчСния Π½Π΅ Π±Ρ‹Π»ΠΎ Π°ΡƒΡ‚ΠΎΠΈΠΌΠΌΡƒΠ½Π½Ρ‹Ρ… Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ. ΠžΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π°ΡƒΡ‚ΠΎΠ°Π½Ρ‚ΠΈΡ‚Π΅Π», Ξ²-2-ΠΌΠΈΠΊΡ€ΠΎΠ³Π»ΠΎΠ±ΡƒΠ»ΠΈΠ½Π°, Π½Π΅ΠΎΠΏΡ‚Π΅Ρ€ΠΈΠ½Π°, ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π° 6, ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π° 18 ΠΈ HLA-DRB1 Π² 1-ΠΉ Π³Ρ€ΡƒΠΏΠΏΠ΅ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ Ρ‡Π΅Ρ€Π΅Π· 2 мСс послС Π½Π°Ρ‡Π°Π»Π° Ρ‚Π΅Ρ€Π°ΠΏΠΈΠΈ, Π° Π²ΠΎ 2-ΠΉ – ΠΏΠ΅Ρ€Π΅Π΄ Π½Π°Ρ‡Π°Π»ΠΎΠΌ ΠΎΡ‡Π΅Ρ€Π΅Π΄Π½ΠΎΠ³ΠΎ Ρ†ΠΈΠΊΠ»Π° Ρ…ΠΈΠΌΠΈΠΎΡ‚Π΅Ρ€Π°ΠΏΠΈΠΈ.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π’Β 1‑й Π³Ρ€ΡƒΠΏΠΏΠ΅ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ ΠΌΡƒΡ‚Π°Ρ†ΠΈΠΉ EGFR / ALK являСтся нСзависимым ΠΏΡ€Π΅Π΄ΠΈΠΊΡ‚ΠΎΡ€ΠΎΠΌ Π½ΠΈΠ·ΠΊΠΈΡ… ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ выТиваСмости Π±Π΅Π· прогрСссирования (p = 0,018). Π’Β Ρ…ΠΎΠ΄Π΅ ΠΎΠ΄Π½ΠΎΡ„Π°ΠΊΡ‚ΠΎΡ€Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π±Ρ‹Π»ΠΎ выявлСно, Ρ‡Ρ‚ΠΎ Π½Π΅ΠΉΡ‚Ρ€ΠΎΡ„ΠΈΠ»ΡŒΠ½ΠΎΠ»ΠΈΠΌΡ„ΠΎΡ†ΠΈΡ‚Π°Ρ€Π½ΠΎΠ΅ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠ΅ Π΄ΠΎ Π½Π°Ρ‡Π°Π»Π° примСнСния ΠΈΠ½Π³ΠΈΠ±ΠΈΡ‚ΠΎΡ€ΠΎΠ² ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΈΠΌΠΌΡƒΠ½Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π° &lt;5 (p = 0,009) ΠΈ появлСниС иммуноопосрСдованных Π½Π΅ΠΆΠ΅Π»Π°Ρ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… явлСний (p = 0,038) связаны с высокими показатСлями выТиваСмости Π±Π΅Π· прогрСссирования. Π’Β 1-ΠΉ Π³Ρ€ΡƒΠΏΠΏΠ΅ ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ Ξ²-2-ΠΌΠΈΠΊΡ€ΠΎΠ³Π»ΠΎΠ±ΡƒΠ»ΠΈΠ½Π° Π±Ρ‹Π» Π½ΠΈΠΆΠ΅ ΠΏΡ€ΠΈ Π΄Π»ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΎΡ‚Π²Π΅Ρ‚Π° β‰₯6 мСс, Ρ‡Π΅ΠΌ ΠΏΡ€ΠΈ прогрСссировании &lt;6 мСс: 1,7 ΠΈ 2,9 ΠΌΠ³ / Π» соотвСтствСнно (p &lt;0,0001). Π£ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², ΠΏΠΎΠ»ΡƒΡ‡Π°Π²ΡˆΠΈΡ… ΠΈΠ½Π³ΠΈΠ±ΠΈΡ‚ΠΎΡ€Ρ‹ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΈΠΌΠΌΡƒΠ½Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π°, с ΡƒΡ€ΠΎΠ²Π½Π΅ΠΌ Ξ²-2-ΠΌΠΈΠΊΡ€ΠΎΠ³Π»ΠΎΠ±ΡƒΠ»ΠΈΠ½Π° β‰₯2,5 ΠΌΠ³ / Π» Π½Π°Π±Π»ΡŽΠ΄Π°ΡŽΡ‚ΡΡ Π±ΠΎΠ»Π΅Π΅ Π½ΠΈΠ·ΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ выТиваСмости Π±Π΅Π· прогрСссирования, Ρ‡Π΅ΠΌ Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² со Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ΠΌ этого ΠΌΠ°Ρ€ΠΊΠ΅Ρ€Π° &lt;2,5 ΠΌΠ³ / Π»: 168 Π΄Π½Π΅ΠΉ ΠΈ Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ Π½Π΅ достигнуто соотвСтствСнно (p = 0,017). ΠŸΡ€ΠΈ Π΄Π»ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΎΡ‚Π²Π΅Ρ‚Π° β‰₯6 мСс Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ Π½Π΅ΠΎΠΏΡ‚Π΅Ρ€ΠΈΠ½Π° оказалось Π½ΠΈΠΆΠ΅, Ρ‡Π΅ΠΌ ΠΏΡ€ΠΈ прогрСссировании заболСвания: 8,6 ΠΈ 13,4 нмоль / Π» соотвСтствСнно (p &lt;0,0001). ΠŸΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ выТиваСмости Π±Π΅Π· прогрСссирования Π±Ρ‹Π»ΠΈ Ρ…ΡƒΠΆΠ΅ Ρƒ Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ… с ΡƒΡ€ΠΎΠ²Π½Π΅ΠΌ Π½Π΅ΠΎΠΏΡ‚Π΅Ρ€ΠΈΠ½Π° β‰₯12 нмоль / Π», Ρ‡Π΅ΠΌ Ρƒ Π±ΠΎΠ»ΡŒΠ½Ρ‹Ρ… с ΡƒΡ€ΠΎΠ²Π½Π΅ΠΌ этого ΠΌΠ°Ρ€ΠΊΠ΅Ρ€Π° &lt;12 нмоль / Π» (ΠΌΠ΅Π΄ΠΈΠ°Π½Π° 164 дня ΠΈ Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ Π½Π΅ достигнуто соотвСтствСнно; p = 0,0007). По Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌ ΠΌΠ½ΠΎΠ³ΠΎΡ„Π°ΠΊΡ‚ΠΎΡ€Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Ξ²-2-ΠΌΠΈΠΊΡ€ΠΎΠ³Π»ΠΎΠ±ΡƒΠ»ΠΈΠ½ β‰₯2,5 ΠΌΠ³ / Π» (p = 0,006) ΠΈ Π½Π΅ΠΎΠΏΡ‚Π΅Ρ€ΠΈΠ½ β‰₯12 нмоль / Π» (p = 0,027) оказались нСзависимыми ΠΏΡ€Π΅Π΄ΠΈΠΊΡ‚ΠΎΡ€Π°ΠΌΠΈ Π±ΠΎΠ»Π΅Π΅ ΠΊΠΎΡ€ΠΎΡ‚ΠΊΠΎΠΉ выТиваСмости Π±Π΅Π· прогрСссирования. НизкиС ΡƒΡ€ΠΎΠ²Π½ΠΈ ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π° 6 ΠΈ ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π° 18, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π°Π½Ρ‚ΠΈΡ‚Π΅Π»Π° ΠΊ Ρ‚ΠΈΡ€Π΅ΠΎΠΈΠ΄Π½ΠΎΠΉ пСроксидазС связаны с ΠΎΡ‚Π²Π΅Ρ‚ΠΎΠΌ β‰₯6 мСс. Π“Π΅Π½ HLA-DRB1*03 ассоциирован с ΠΎΡ‚Π²Π΅Ρ‚ΠΎΠΌ β‰₯6 мСс, Π° Ρ‚Π°ΠΊΠΆΠ΅ с Π±ΠΎΠ»Π΅Π΅ высокими показатСлями выТиваСмости Π±Π΅Π· прогрСссирования ΠΏΠΎ ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с Π΄Ρ€ΡƒΠ³ΠΈΠΌΠΈ Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹ΠΌΠΈ Π²Π°Ρ€ΠΈΠ°Π½Ρ‚Π°ΠΌΠΈ. Π£Ρ€ΠΎΠ²Π½ΠΈ Ξ²-2-ΠΌΠΈΠΊΡ€ΠΎΠ³Π»ΠΎΠ±ΡƒΠ»ΠΈΠ½Π°, Π½Π΅ΠΎΠΏΡ‚Π΅Ρ€ΠΈΠ½Π°, ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π° 6 ΠΈ ΠΈΠ½Ρ‚Π΅Ρ€Π»Π΅ΠΉΠΊΠΈΠ½Π° 18 Π² 1-ΠΉ Π³Ρ€ΡƒΠΏΠΏΠ΅ ΠΏΠΎ ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ со 2-ΠΉ Π³Ρ€ΡƒΠΏΠΏΠΎΠΉ оказались Π²Ρ‹ΡˆΠ΅ (p &lt;0,0001).Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. Π˜ΠΌΠΌΡƒΠ½ΠΎΠ»ΠΎΠ³ΠΈΡ‡Π΅ΡΠΊΠΈΠ΅ ΠΌΠ°Ρ€ΠΊΠ΅Ρ€Ρ‹ ΠΌΠΎΠ³ΡƒΡ‚ ΡΠ»ΡƒΠΆΠΈΡ‚ΡŒ пСрспСктивными прогностичСскими Ρ„Π°ΠΊΡ‚ΠΎΡ€Π°ΠΌΠΈ Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с распространСнным Π½Π΅ΠΌΠ΅Π»ΠΊΠΎΠΊΠ»Π΅Ρ‚ΠΎΡ‡Π½Ρ‹ΠΌ Ρ€Π°ΠΊΠΎΠΌ Π»Π΅Π³ΠΊΠΎΠ³ΠΎ ΠΏΡ€ΠΈ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΈΠ½Π³ΠΈΠ±ΠΈΡ‚ΠΎΡ€ΠΎΠ² ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Ρ‹Ρ… Ρ‚ΠΎΡ‡Π΅ΠΊ ΠΈΠΌΠΌΡƒΠ½Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π²Π΅Ρ‚Π°
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