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Раковая наука и терапия

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Объем 9, Проблема 8 (2017)

Обзорная статья

Current Management Approaches of Chronic Myeloid Leukemia

Atalay Mulu Fentie, Minyahi Alebachew Woldu, Belete Ayalneh Worku

Chronic myeloid leukemia is a slowly progressive and clonal myeloproliferative disorder characterized by the presence of Philadelphia chromosome. Even if the global incidence is unknown, CML accounts for 15% to 20% cases of adult leukemia’s in USA and is predominantly the disease of adults. It has three phases reflecting the grade of malignancy; chronic phase, accelerated phase and blast crisis phase. Initial diagnosis and monitoring of treatment response is based on hematologic, cytogenetic and molecular assessments that need to be regularly checked. The treatment in each phase had undergone a profound progress over a relatively short period of time, starting with arsenic therapy, radiotherapy, allogeneic hematopoietic stem cell transplantation, recombinant interferon-alfa, busulfan, and hydroxyurea, and more recently with the tyrosine kinase inhibitors. Among tyrosine kinase inhibitors national comprehensive cancer network puts imatinib, dastinib and nilotinib as category 1 recommendation for initial treatment of chronic phase chronic myeloid leukemia. Second generation tyrosine kinase inhibitors; nilotinib, dasatinib, bosutinib and ponatinib had shown inducing higher rates of early optimal responses, although their impact on long-term overall survival remains to be determined. There are also drugs for the treatment of chronic myeloid leukemia such as histone deacetylase inhibitors, proteasome inhibitors and farnesyl transferase inhibitors which are under investigation. In addition to these vaccines are under investigation as a part of treatment for chronic myeloid leukemia which still needs further research.

Краткое сообщение

Circulating Tumor Cells (CTCs) as Biomarker for PD-1/PD-L1 Blockade Immunotherapy

Chunyan YUE and Zhiyuan HU

The PD-1/PD-L1 (programmed death-1, programmed death-1 ligand-1) checkpoint is involved in dampening autoimmunity of peripheral tissues to help control local inflammatory responses. It is reported that this pathway activation results in peripheral immunologic tolerance in T cells [1]. As an identified ligand of PD-1, PD-L1 expressed in tumor cells facilitates tumor escape by inducing a net immunosuppressive effect after binding to PD-1 present on the surface of activated T cells and B cells [2]. The enhanced understanding of the complex interplay between the tumor and the immune system has promoted the development of anti-PD therapy for the treatment of human cancers. Antibodies blocking PD-1/PD-L1 have demonstrated durable responses in a number of different advanced malignancies [3,4]. However, while increasing a baseline T-cell-specific immune response, immune checkpoint inhibitors might result in autoimmune-like/ inflammatory side-effects, which cause collateral damage to normal organ systems and tissues, such as skin, lung and liver [5]. Therefore, detection of potential biomarkers that may predict benefit is pivotal in order to optimize clinical efficacy and safety of checkpoint blockade immunotherapy.

История болезни

Breast Cancer Arising from a Suspected Fibroadenoma during Pregnancy: A Case Report and Review of Literature

Yasamin Ghazvini Kor, Mehdi Saeedan and Mohamed Sobhy Badr Sobei

Introduction: Fibroadenomas are the most common benign neoplastic lesion of the breast. These hormonesensitive tumors can grow rapidly under the influence of pregnancy hormones. Although rare, malignant transformation of these lesions has been reported. The risk of the standard treatment regimen on the fetus makes the PABC (Pregnancy-Associated Breast Cancer) a challenging task for clinicians. Overall treatment is based on guidelines for the general population with some variations to decrease the risk of fetal damage as much as possible.

Case report: A 37-year-old Indian female, presented with a palpable mass in her right breast in the first month of pregnancy. A preliminary diagnosis of fibroadenoma was made at the time. She came back at 39 weeks of gestation with severe vaginal bleeding and a huge painful mass in the right breast. Labor was induced upon diagnosis of intrauterine fetal death and ultrasonography of the breast revealed a lobulated soft tissue mass with multiple cystic areas and internal vascularity; measuring 16 cm in largest diameter. Excisional biopsy under GA (General Anesthesia) was performed upon request of the patient and microscopic HPE (Histopathological Examination) reported the presence of Grade 3 invasive ductal carcinoma.

Conclusion: Breast cancer arising within fibroadenoma during pregnancy is extremely rare but presents unique challenges in evaluation and management. An enlarging breast mass during pregnancy should never be neglected, and thorough investigation including biopsy is strongly advised to establish a definitive diagnosis.

исследовательская статья

Integrative Analysis of Transcriptome and MicroRNome Profiles in Cholangiocarcinoma

Fábio E Severino, Claudia N Hasimoto, Maria A M Rodrigues, Juan C Llanos and Patricia P Reis

Aim: To identify deregulated expression of miRNAs and target genes in cholangiocarcinoma (CCA), as well as drug-gene interactions that may be useful for patient treatment.

Methods: We analyzed quantitative transcriptome and miRNA deep sequencing expression data from 45 samples, 36 CCA and 9 histologically normal biliary tissues, obtained from the public repository The Cancer Genome Atlas (TCGA). Bioinformatic methods were used to identify and integrate differential expression of miRNA and transcriptome profiles in CCA vs. normal tissues. Deregulated miRNA and corresponding target genes were identified and mapped into miRNA-mRNA networks.

Results: Results showed 64 differentially expressed miRNAs (48 over and 16 under-expressed) between CCA and corresponding normal biliary tissues. Additionally, 432 genes (180 over and 252 under-expressed) were identified between CCA and normal samples. We identified individual miRNAs with the largest number of gene targets. Among these, miR-125a was over-expressed and had the highest number of direct interactions with 33 mRNA targets. miRNAs miR-122 and miR-139 were the under-expressed miRNAs with the highest number of interactions (9 targets each). miR-122 was found to modulate the expression of the transcription factor FOXM1, known to be involved in tumorigenesis and the matrix metalloproteinase MMP7, an important mediator of tumor invasion. miR-148 and miR-194 were predicted to modulate NQO1, which is up-regulated in cancer and associated with treatment resistance in cholangiocarcinoma.

Conclusion: The novelty of our study is the identification of complex deregulated networks of miRNAs and target genes in CCA. miRNAs with a large number of targets may have a higher functional impact on cell regulation. These findings contribute for a better understanding of CCA biology. Identified miRNAs and target genes are potential candidates for the design of validation strategies towards the characterization of clinically applicable biomarkers; such biomarkers may be useful for the development of molecularly-targeted therapeutics that can benefit patients.

исследовательская статья

Is It Possible To Reduce the Risk of Hepatocellular Carcinoma by Taking Statin in Diabeties Mellitus Patients with HBV or HCV

Guei-Fen Chiu, Yu-Han Chang, Den-Chang Wu, Ming-Tsang Wu4 and Kun-Der Lin

Objectives: To determine the relationship between the dose effect of Statin and the risk of HCC.

Methods: This study was a case-control study. All participants were ≧ 50 years of age and were diagnosed with diabetes (ICD-9250.0x 0, 205.0 × 2) and were treated with an anti-diabetic agent for at least for 3 months according to the NHID, LHID2010 (longitudinal health insurance database 2010). We captured the use of a Statin before the index date in patients with type II diabetes. Patients diagnosed with a hepatoma (ICD-9:155) were defined as the case group.

Results: The risk of hepatoma was reduced in patients with higher cumulative DDDs statin use compared to statin non-users. (HBV population: cumulative dose>298 DDDs: OR=0.41; 95% CI:0.24-0.72; HCV population: cumulative dose>205 DDDs: [OR=0.25; 95% CI: 0.13-0.48]).

Conclusion: A dose-response relationship exists between lower risk of hepatoma and higher cumulative DDDs of statin use.

исследовательская статья

Клиническое значение и терапевтический потенциал экспрессии лиганда программируемой смерти-1 (PD-L1) и PD-L2 при колоректальном раке человека

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????: ???? ????????, ??? ???? ??????????????????? ??????-1/??????? ??????????????????? ?????? (PD-1/PD-L) ? ????????? ?-?????? ?????? ?????? ???? ? ????????? ??????? ?? ?????????? ???????. ??????????????? ???????? ?????????? PD-L1 ? PDL2 ??? ?????????????? ???? (???) ??? ??? ???????????. ?? ????????????????, ????? ?? ????????????? ???????????? ??????????????? PD-1-?????????? ?-?????? ????? PD-L1 ? PD-L2 ?????? ??????? ?????????????? ??????????? ???????????????? ??????? ??????????? ???????? ????????? ?????????????????? ??????????.

??????: ?? ??????????? ?????????? PD-L1 ? PD-L2 ? ???????? ????????? ? ?????????????? ????? ? ???????????????? ?? ??????????????? ???????? ? ????? ?????? ??????? ???????????.

??????????: ???????????? ?-?????? ??????????? ? 90,5% ????????, ?????? ? 58% ????????? ? ???????? ???? ?????????? PD-1-????????????? ?-??????. ? ?????????, ? ??????? ????????? PD-1-????????????? ???????????? ?-??????, ??????????? ?????????? ?????????? PD-L1- ? ????????, ??? ? ??? ? ????????????? ??????????? ?? PD-1-?-??????. ??????? ??????????????? ??????? PD-1-????????????? ?-?????? ???? ????? ???????? ??? ???? ?? ??????? ??????, ??? ??? ???? ?? ?????? ??????. ?????????? ??????? (PD-L1/PD-L2) ? ???????? ? ????????? ? ??????? PD-1-????????????? ????????????? ?-?????? ???? ??????? ? ?????? ?????????. ?????????????? ?????? ???????, ??? ?????????? PD-L ? ???????? ???? ??????????? ??????????????? ???????? ??? ?????????????? ????.

??????????: ?????????????? ?????????? ??????? ??????? ????????? ???????? ? ????????? ? ??? ????????????, ??? ????????????? ???????????? ??????????????? PD-1-????????????? ?-?????? ????? ?????????? PD-L1 ?????? ??????? ????? ?????????????? ??????????? ???????????????? ??????? ????? ?????????? ?????????????????? ??????????. ???? ?????????? ???????????? PD-1 ?? CD4/Foxp3-????????????? ?-???????, ??? ????????? ?? ?????????, ?????????????? ????????????? ?-????????, ? ??????? ??????? ?????????? ?????? ????? ???????? ????????? ????????????? ? ??????????. ??? ???????????? ????????????? ???????? ?????????, ???????????? ????????????? ???????????? PD-1/PD-L1 ??? ???.

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