Survival Prognosis Of Patients Research Articles

Total hysterectomy versus radical hysterectomy in neuroendocrine cervical cancer: a SEER-database analysis

PurposeWe conducted this study to evaluate the efficacy of total hysterectomy versus radical hysterectomy in the treatment of neuroendocrine cervical cancer (NECC).MethodsEligible NECC patients were identified from the Surveillance, Epidemiology and End Results (SEER) database. Demographic characteristics, clinical treatment and survival of the patients were collected. The overall survival (OS) and cancer-specific survival (CSS) were estimated by Kaplan–Meier analysis with log-rank test.ResultsA total of 286 patients were included, with 104 patients undergoing total hysterectomy and 182 patients undergoing radical hysterectomy. The 5-year OS were 50.8% in the total hysterectomy group and 47.5% in the radical hysterectomy group (p = 0.450); and the corresponding 5-year CSS were 51.6% and 49.1% (p = 0.494), respectively. Along with surgery, radiotherapy was given to 49.0% of patients in the total hysterectomy group and 50.5% in the radical hysterectomy group; and chemotherapy was administered to 77.9% of patients in the total hysterectomy group and 85.7% in the radical hysterectomy group. Unexpectedly, in patients who received adjuvant radiotherapy with or without chemotherapy, the OS was superior in the total hysterectomy group compared with the radical hysterectomy group (p = 0.034). While in patients who received chemotherapy alone and those who received neither radiotherapy nor chemotherapy, the OS still remained comparable between the total hysterectomy and radical hysterectomy group.ConclusionCompared with radical hysterectomy, total hysterectomy was not associated with compromised survival prognosis in patients with NECC. Total hysterectomy has the potential to be a surgical alternative in the multimodal management of NECC.

Potential applications of dual haptoglobin expression in the reclassification and treatment of hepatocellular carcinoma

HCC is a malignancy characterized by high incidence and mortality rates. Traditional classifications of HCC primarily rely on tumor morphology, phenotype, and multicellular molecular levels, which may not accurately capture the cellular heterogeneity within the tumor. This study integrates scRNA-seq and bulk RNA-seq to spotlight HP as a critical gene within a subgroup of HCC malignant cells. HP is highly expressed in HCC malignant cells and lowly expressed in T cells. Within malignant cells, elevated HP expression interacts with C3, promoting Th1-type responses via the C3/C3AR1 axis. In T cells, down-regulating HP expression favors the expression of Th1 cell-associated marker genes, potentially enhancing Th1-type responses. Consequently, we developed a "HP-promoted Th1 response reclassification" gene set, correlating higher activity scores with improved survival rates in HCC patients. Additionally, four predictive models for neoadjuvant treatment based on HP and C3 expression were established: 1) Low HP and C3 expression with high Th2 cell infiltration; 2) High HP and low C3 expression with high Th2 cell infiltration; 3) High HP and C3 expression with high Th1 cell infiltration; 4) Low HP and high C3 expression with high Th1 cell infiltration. In conclusion, the HP gene selected from the HCC malignant cell subgroup (Malignant_Sub 6) might serve as a potential ally against the tumor by promoting Th1-type immune responses. The establishment of the "HP-promoted Th1 response reclassification" gene set offers predictive insights for HCC patient survival prognosis and neoadjuvant treatment efficacy, providing directions for clinical treatments.

Stratification and prognostic evaluation of breast cancer subtypes defined by obesity-associated genes

ObjectiveBreast cancer was the most common type of cancer among women worldwide, significantly impacting their quality of life and survival rates. And obesity has been widely accepted as an important risk factor for breast cancer. However, the specific mechanisms by which obesity affects breast cancer were still unclear. Therefore, studying the impact mechanisms of obesity as a risk factor for breast cancer was of utmost importance.MethodsThis study was based on TCGA breast cancer RNA transcriptomic data and the GeneCard obesity gene set. Through single and multiple factor Cox analysis and LASSO coefficient screening, seven hub genes were identified. The independent mechanisms of these seven hub genes were evaluated from various aspects, including survival data, genetic mutation data, single-cell sequencing data, and immune cell data. Additionally, the risk prognosis model and the neural network diagnostic model were established to further investigate these seven hub genes. In order to achieve precision treatment for breast cancer (BRCA), based on the RNA transcriptomic data of the seven genes, 1226 BRCA patients were divided into two subtypes: BRCA subtype 1 and BRCA subtype 2. By studying and comparing the immune microenvironment, investigating the mechanisms of differential gene expression, and exploring the mechanisms of subnetworks, we aim to explore the clinical differences in the presentation of BRCA subtypes and achieve precision treatment for BRCA. Finally, qRT-PCR experiments were conducted to validate the conclusions of the bioinformatics analysis.ResultsThe 7 hub genes showed good diagnostic independence and can serve as excellent biomarkers for molecular diagnosis. However, they do not perform well as independent prognostic molecular markers for BRCA patients. When predicting the survival of BRCA patients, their AUC values at 1 year, 3 years, and 5 years are mostly below 0.5. Nevertheless, through the establishment of the risk prognosis model considering the combined effect of the seven hub genes, it was found that the survival prediction of BRCA patients can be significantly improved. The risk prognosis model, compared to the independent use of the seven hub genes as prognostic markers, achieved higher timeROC AUC values at 1 year, 3 years, and 5 years, with values of 0.651, 0.669, and 0.641 respectively. Additionally, the neural network diagnostic model constructed from the 7 genes performs well in diagnosing BRCA, with an AUC value of 0.94, accurately identifying BRCA patients. The two subtypes identified by the seven hub genes exhibited significant differences in survival period, with subtype 1 having a poor prognosis. The differential mechanisms between the two subtypes mainly originate from regulatory differences in the immune microenvironment. Finally, the results of this study’s bioinformatics analysis were validated through qRT-PCR experiments.Conclusion7 hub genes serve as excellent independent biomarkers for molecular diagnosis, and the neural network diagnostic model can accurately distinguish BRCA patients. In addition, based on the expression levels of these seven genes in BRCA patients, two subtypes can be reliably identified: BRCA subtype 1 and BRCA subtype 2, and these two subtypes showed significant differences in BRCA patient survival prognosis, proportion of immune cells, and expression levels of immune cells. Among them, patients with subtype 1 of BRCA had a poor prognosis.

Implications of Pretreatment Serum Carcinoembryonic Antigen Levels and Perineural Invasion with Staging, Prognosis, and Management in Stage I-III Colon Cancer after Surgery: A Retrospective Cohort Study in the SEER Database.

Pretreatment levels of serum carcinoembryonic antigen (CEA) and perineural invasion (PNI) are related to poor prognosis in colon cancer. We analyzed the CEA and PNI (defined as incorporation of carcinoembryonic antigen and perineural invasion (CP)-stage), which are included in the Tumor-Node-Metastasis (TNM) staging system of the American Joint Committee on Cancer (AJCC), and evaluated the survival prognosis of patients treated with surgery in I-III stage colon carcinoma. We employed a retrospective study for eligible colon carcinoma patients obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Kaplan-Meier curve and Multivariate Cox regression analysis were used to analyze different TNM-CP stages for the cancer-specific survival (CSS) probabilities in colon cancer. In our study, CEA levels and PNI were significant prognostic factors (p < 0.05), and the newly proposed CP-stage was an independent prognostic index in stage I-III colon carcinoma after surgery. Multivariate Cox regression analyses indicated that CP1-stage was related to a 63.9% increased risk of cancer-specific mortality (hazard ratio (HR): 1.639, 95% confidence interval (CI): 1.544-1.739, p < 0.001), compared with CP0-stage in colon cancer. In respective TNM stages, the CP0-stage had an advantage over the CP1-stage for CSS (p < 0.001). Moreover, CP1-stage patients with node-negative colon cancer were contacted with similar or worse survival in comparison to CP0-stage patients with node-positive. For postoperative patients with stage I-III colon cancer, our study indicated that the CP stage is a significant prognostic factor for CSS, which deserves more clinical attention. It's worth noting that including the CP stage in the AJCC TNM staging system of colon carcinoma is beneficial to the survival prediction and clinical treatment.

Inborn errors of immunity: features of epidemiology and continuity of medical care in the Republic of Tatarstan

BACKGROUND: Currently, inborn errors of immunity represent one of the most interesting problems in clinical immunology. The data obtained in the field of studying pathogenetic mechanisms and clinical manifestations, expanding diagnostic capabilities, including molecular genetic methods, formed the basis for revising the classification and introducing new modern treatment methods. The study of regional characteristics of inborn errors of immunity is important because it allows us to determine epidemiological indicators, clinical features of diseases and evaluate the therapy being carried out.&#x0D; AIM: To assess the effectiveness and level of continuity of medical care in the Republic of Tatarstan based on an epidemiological analysis of a group of patients diagnosed with primary immunodeficiency.&#x0D; MATERIALS AND METHODS: analysis of the register of patients living in the Republic of Tatarstan with an established diagnosis of primary immunodeficiency, observed from 1994 to 2023. A total of 240 patients were included in the study.&#x0D; RESULTS: An epidemiological analysis of inborn errors of immunity in the Republic of Tatarstan revealed an overall prevalence of 6.0 per 100,000 population, with the status "alive" ― 4.98 per 100,000 population, excluding patients with selective IgA deficiency ― 5.3 and 4.4 per 100,000 population, respectively, with a high proportion of patients over 18 years of age (53%), with the largest group of patients having defects in antibody production (42%).&#x0D; CONCLUSION: The increasing relevance of the problem of primary immunodeficiency requires special attention to the organization of medical care for patients with primary immunodeficiency, increasing continuity between specialized pediatric services and the adult network, as well as developing issues of interdisciplinary interaction.

Bayesian network-based survival prediction model for patients having undergone post-transjugular intrahepatic portosystemic shunt for portal hypertension.

Portal hypertension (PHT), primarily induced by cirrhosis, manifests severe symptoms impacting patient survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To our knowledge, existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation. To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS. The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively analyzed. Variables were selected using Cox and least absolute shrinkage and selection operator regression methods, and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for PHT. Variable selection revealed the following as key factors impacting survival: age, ascites, hypertension, indications for TIPS, postoperative portal vein pressure (post-PVP), aspartate aminotransferase, alkaline phosphatase, total bilirubin, prealbumin, the Child-Pugh grade, and the model for end-stage liver disease (MELD) score. Based on the above-mentioned variables, a BN-based 2-year survival prognostic prediction model was constructed, which identified the following factors to be directly linked to the survival time: age, ascites, indications for TIPS, concurrent hypertension, post-PVP, the Child-Pugh grade, and the MELD score. The Bayesian information criterion was 3589.04, and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of 0.16. The model's accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72. This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.

The Role of NK Cells in Allogeneic Hematopoietic Stem Cell Micro-Transplantation for Acute Myeloid leukemia

To explore the role of NK cells in allogeneic hematopoietic stem cell micro-transplantation(MST) in the treatment of patients with acute myeloid leukemia(AML). Data from 93 AML patients treated with MST at our center from 2013-2018 were retrospectively analyzed. The induction regimen was anthracycline and cytarabine combined with peripheral blood stem cells transplantation mobilization by granulocyte colony stimulating factor (GPBSC), followed by 2-4 courses of intensive treatment with medium to high doses of cytarabine combined with GPBSC after achieving complete remission (CR). The therapeutic effects of one and two courses of MST induction therapy on 42 patients who did not reach CR before transplantation were evaluated. Cox proportional hazards regression analysis was used to analyze the impact of donor NK cell dose and KIR genotype, including KIR ligand mismatch, 2DS1, haplotype, and HLA-Cw ligands on survival prognosis of patients. Forty-two patients received MST induction therapy, and the CR rate was 57.1% after 1 course and 73.7% after 2 courses. Multivariate analysis showed that, medium and high doses of NK cells was significantly associated with improved disease-free survival (DFS) of patients (HR=0.27, P =0.005; HR=0.21, P =0.001), and high doses of NK cells was significantly associated with improved overall survival (OS) of patients (HR=0.15, P =0.000). Donor 2DS1 positive significantly increases OS of patients (HR=0.25, P =0.011). For high-risk patients under 60 years old, patients of the donor-recipient KIR ligand mismatch group had longer DFS compared to the nonmismatch group (P =0.036); donor 2DS1 positive significantly prolonged OS of patients (P =0.009). NK cell dose, KIR ligand mismatch and 2DS1 influence the therapeutic effect of MST, improve the survival of AML patients.

FEN1 upregulation mediated by SUMO2 via antagonizing proteasomal degradation promotes hepatocellular carcinoma stemness

PurposeMetastasis of hepatocellular carcinoma (HCC) critically impacts the survival prognosis of patients, with the pivotal role of hepatocellular carcinoma stem cells in initiating invasive metastatic behaviors. The Flap Endonuclease 1 (FEN1) is delineated as a metallonuclease, quintessential for myriad cellular processes including DNA replication, DNA synthesis, DNA damage rectification, Okazaki fragment maturation, baseexcision repair, and the preservation of genomic stability. Furthermore, it has been recognized as an oncogene in a diverse range of malignancies. Our antecedent research has highlighted a pronounced overexpression of protein FEN1 in hepatocellular carcinoma, where it amplifies the invasiveness and metastatic potential of liver cancer cells. However, its precise role in liver cancer stem cells (LCSCs) remains an enigma and requires further investigation. MethodsTo rigorously evaluate the stemness attributes of LCSCs, we employed sphere formation assays and flow cytometric evaluations. Both CD133+ and CD133- cell populations were discerningly isolated utilizing immunomagnetic bead separation techniques. The expression levels of pertinent genes were assayed via real-time quantitative PCR (RT-qPCR) and western blot analyses, while the expression profiles in hepatocellular carcinoma tissues were gauged using immunohistochemistry. Subsequent immunoprecipitation, in conjunction with mass spectrometry, ascertained the concurrent binding of proteins FEN1 and Small ubiquitin-related modifier 2 (SUMO2) in HCC cells. Lastly, the impact of SUMO2 on proteasomal degradation pathway of FEN1 was validated by supplementing MG132. ResultsOur empirical findings substantiate that protein FEN1 is profusely expressed in spheroids and CD133+ cells. In vitro investigations demonstrate that the upregulation of protein FEN1 unequivocally augments the stemness of LCSCs. In a congruent in vivo context, elevation of FEN1 noticeably enhances the tumorigenic potential of LCSCs. Conversely, inhibiting protein FEN1 resulted in a marked reduction in LCSC stemness. From a mechanistic perspective, there exists a salient positive correlation between the protein expression of FEN1 and SUMO2 in liver cancer tissues. Furthermore, the level of SUMO2-mediated modification of FEN1 is pronouncedly elevated in LCSCs. Interestingly, SUMO2 has the ability to bind to FEN1, leading to a inhibition in the proteasomal degradation pathway of FEN1 and an enhancement in its protein expression. However, it is noteworthy that this interaction does not affect the mRNA level of FEN1. ConclusionIn summation, our research elucidates that protein FEN1 is an effector in augmenting the stemness of LCSCs. Consequently, strategic attenuation of protein FEN1 might proffer a pioneering approach for the efficacious elimination of LCSCs.

Plasma membrane SK2 channel activity regulates migration and chemosensitivity of high-grade serous ovarian cancer cells.

No data are currently available on the functional role of small conductance Ca2+-activated K+ channels (SKCa) in ovarian cancer. Here, we characterized the role of SK2 (KCa2.2) in ovarian cancer cell migration and chemosensitivity. Using the selective non-cell-permeant SK2 inhibitor Lei-Dab7, we identified functional SK2 channels at the plasma membrane, regulating store-operated Ca2+ entry (SOCE) in both cell lines tested (COV504 and OVCAR3). Silencing KCNN2 with short interfering RNA (siRNA), or blocking SK2 activity with Lei-Dab7, decreased cell migration. The more robust effect of KCNN2 knockdown compared to Lei-Dab7 treatment suggested the involvement of functional intracellular SK2 channels in both cell lines. In cells treated with lysophosphatidic acid (LPA), an ovarian cancer biomarker of progression, SK2 channels are a key player of LPA pro-migratory activity but their role in SOCE is abolished. Concerning chemotherapy, SK2 inhibition increased chemoresistance to Taxol® and low KCNN2 mRNA expression was associated with the worst prognosis for progression-free survival in patients with serous ovarian cancer. The dual roles of SK2 mean that SK2 activators could be used as an adjuvant chemotherapy to potentiate treatment efficacy and SK2 inhibitors could be administrated as monotherapy to limit cancer cell dissemination.

MiR-2110 induced by chemically synthesized cinobufagin functions as a tumor-metastatic suppressor via targeting FGFR1 to reduce PTEN ubiquitination degradation in nasopharyngeal carcinoma.

Tumor cell metastasis is the key cause of death in patients with nasopharyngeal carcinoma (NPC). MiR-2110 was cloned and identified in Epstein-Barr virus (EBV)-positive NPC, but its role is unclear in NPC. In this study, we investigated the effect of miR-2110 on NPC metastasis and its related molecular basis. In addition, we also explored whether miR-2110 can be regulated by cinobufotalin (CB) and participate in the inhibition of CB on NPC metastasis. Bioinformatics, RT-PCR, and in situ hybridization were used to observe the expression of miR-2110 in NPC tissues and cells. Scratch, Boyden, and tail vein metastasis model of nude mouse were used to detect the effect of miR-2110 on NPC metastasis. Western blot, Co-IP, luciferase activity, colocalization of micro confocal and ubiquitination assays were used to identify the molecular mechanism of miR-2110 affecting NPC metastasis. Finally, miR-2110 induced by CB participates in CB-stimulated inhibition of NPC metastasis was explored. The data showed that increased miR-2110 significantly suppresses NPC cell migration, invasion, and metastasis. Suppressing miR-2110 markedly restored NPC cell migration and invasion. Mechanistically, miR-2110 directly targeted FGFR1 and reduced its protein expression. Decreased FGFR1 attenuated its recruitment of NEDD4, which downregulated NEDD4-induced phosphatase and tensin homolog (PTEN) ubiquitination and degradation and further increased PTEN protein stability, thereby inactivating PI3K/AKT-stimulated epithelial-mesenchymal transition signaling and ultimately suppressing NPC metastasis. Interestingly, CB, a potential new inhibitory drug for NPC metastasis, significantly induced miR-2110 expression by suppressing PI3K/AKT/c-Jun-mediated transcription inhibition. Suppression of miR-2110 significantly restored cell migration and invasion in CB-treated NPC cells. Finally, a clinical sample assay indicated that reduced miR-2110 was negatively correlated with NPC lymph node metastasis and positively related to NPC patient survival prognosis. In summary, miR-2110 is a metastatic suppressor involving in CB-induced suppression of NPC metastasis.

Machine Learning Meets Cancer.

The role of machine learning (a part of artificial intelligence-AI) in the diagnosis and treatment of various types of oncology is steadily increasing. It is expected that the use of AI in oncology will speed up both diagnostic and treatment planning processes. This review describes recent applications of machine learning in oncology, including medical image analysis, treatment planning, patient survival prognosis, and the synthesis of drugs at the point of care. The fast and reliable analysis of medical images is of great importance in the case of fast-flowing forms of cancer. The introduction of ML for the analysis of constantly growing volumes of big data makes it possible to improve the quality of prescribed treatment and patient care. Thus, ML is expected to become an essential technology for medical specialists. The ML model has already improved prognostic prediction for patients compared to traditional staging algorithms. The direct synthesis of the necessary medical substances (small molecule mixtures) at the point of care could also seriously benefit from the application of ML. We further review the main trends in the use of artificial intelligence-based technologies in modern oncology. This review demonstrates the future prospects of using ML tools to make progress in cancer research, as well as in other areas of medicine. Despite growing interest in the use of modern computer technologies in medical practice, a number of unresolved ethical and legal problems remain. In this review, we also discuss the most relevant issues among them.

Prognostic value of brain perfusion by MRI in the initial study of high grade gliomas

ObjectivesTo evaluate if the tumour perfusion at the initial MRI scan is a marker of prognosis for survival in patients diagnosed with High Grade Gliomas (HGG). To analyse the risk factors which influence on the mortality from HGG to quantify the overall survival to be expected in patients. Patients and methodsThe patients diagnosed with HGG through a MRI scan in a third-level hospital between 2017 and 2019 were selected. Clinical and tumour variables were collected. The survival analysis was used to determine the association between the tumour perfusion and the survival time. The relation between the collected variables and the survival period was assessed through Wald’s statistical method, measuring the relationship via Cox’s regression model. Finally, the type of relationship that exists between the tumour perfusion and the survival was analysed through the Lineal Regression method.Those statistical analysis were carried out using the software SPSS v.17. Results38 patients were included (average age: 61.1 years old). The general average survival period was 20.6 months. A relationship between the tumour perfusion at the MRI scan and the overall survival has been identified, in detail, a group with intratumor values of relative cerebral blood volume (rCBV)>3.0 has shown a significant decline in the average survival period with regard to the average survival period of the group with values <3.0 (14.6 months vs. 22.8 months, p = 0.046). It has also been proved that variables like Karnofsky’s scale and the response time since the intervention significantly influence on the survival period. ConclusionsIt has become evident that the tumour perfusion via MRI scan has a prognostic value in the initial analysis of HGG. The average survival period of patients with rCBV less than or equal to 3.0 is significantly higher than those patients whose values are higher, which allows to be more precise with the prognosis of each patient.

Multi-omics analysis for ferroptosis-related genes as prognostic factors in cutaneous melanoma.

Melanoma is highly malignant and heterogeneous. It is essential to develop a specific prognostic model for improving the patients' survival and treatment strategies. Recent studies have shown that ferroptosis results from the overproduction of lipid peroxidation and is an iron-dependent form of programmed cell death. Despite this, ferroptosis-related genes (FRGs) and their clinical significances remain unknown in malignant melanoma. This study aims to assess the role of FRGs in melanoma, with the goal of developing a novel prognostic model that provides new insights into personalized treatment and improvement of therapeutic outcomes for melanoma. We systematically characterized the genetic alterations and mRNA expression of 73 FRGs in The Cancer Genome Atlas (TCGA)-skin cutaneous melanoma (SKCM) dataset in this study. The results were validated with real-time RT-PCR and Western blotting. Subsequently, a multi-gene feature model was constructed using the TCGA-SKCM cohort. Melanoma patients were classified into a high-risk group and a low-risk group based on the feature model. As a final step, correlations between ferroptosis-related signatures and immune features, immunotherapy efficacy, or drug response were analyzed. By analyzing melanoma samples from TCGA-SKCM dataset, FRGs exhibited a high frequency of genetic mutations and copy number variations (CNVs), significantly impacting gene expression. Additionally, compared with normal skin tissue, 30 genes with significantly differential expression were identified in melanoma tissues. A prognostic model related to FRGs, constructed using the LASSO Cox regression method, identified 13 FRGs associated with overall survival prognosis in patients and was validated with external datasets. Finally, functional enrichment and immune response analysis further indicated significant differences in immune cell infiltration, mutation burden, and hypoxia status between the high-risk group and the low-risk group, and the model was effective in predicting responses to immunotherapy and drug sensitivity. This study develops a strong ferroptosis-related prognostic signature model which could put forward new insights into target therapy and immunotherapy for patients with melanoma.

Chronic lymphocytic leukemia in combination with COVID-19: clinical features and unfavorable prognosis factors

Background. At the end of 2019, a new coronavirus infection caused by the SARS-CoV-2 virus was registered. In March 2020, the first cases of COVID-19 were detected in Moscow. Patients with chronic lymphocytic leukemia, characterized by profound immune dysfunction, have risk factors for severe viral disease.Aim. To identify risk factors for hospital mortality and severe course of COVID-19, as well as to optimize therapeutic and preventive measures.Materials and methods. The analysis included 238 patients (142 (59 %) men and 96 (41 %) women) with chronic lymphocytic leukemia and COVID-19 with a median age of 66 (37-90) years, who were hospitalized at City Clinical Hospital No. 52 (Moscow) between April 2020 and April 2023. To compare hospital mortality and severity of COVID-19, patients were divided into 2 groups depending on the hospitalization period: 2020-2021 and 2022-2023, which correlates with the prevalence of some SARS-CoV-2 variants from December 2021 and changes in Moscow epidemiological situation.Results. Overall hospital mortality rate in 2020-2021 was 25 % (n = 45). Age over 73 years was a significant unfavorable factor in men. Cardiovascular diseases increase the risk of death by 2.3 times. Patients with a Charlson Comorbidity Index of 6 or more have a 2.2 times greater risk of death. A history of 1 or more lines of immunochemotherapy increased the risk of hospital mortality by 1.5 times. Relapse/progression of the disease were factors of unfavorable prognosis for patient survival. Binet stage C also showed a significant unfavorable prognosis. When studying all cases of death (n = 51), complications such as myelotoxic agranulocytosis, secondary bacterial complications and severe interstitial pulmonary damage &gt;75 % were identified.Conclusion. Coronavirus infection caused by SARS-CoV-2 represents an infectious threat among patients with chronic lymphocytic leukemia and may affect the regimen and tactics of antitumor therapy. The use of a full range of preventive measures, vaccination and pre-exposure prophylaxis in this cohort of patients is of great importance.

Multiple machine-learning tools identifying prognostic biomarkers for acute Myeloid Leukemia

BackgroundAcute Myeloid Leukemia (AML) generally has a relatively low survival rate after treatment. There is an urgent need to find new biomarkers that may improve the survival prognosis of patients. Machine-learning tools are more and more widely used in the screening of biomarkers.MethodsLeast Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), lrFuncs, IdaProfile, caretFuncs, and nbFuncs models were used to screen key genes closely associated with AML. Then, based on the Cancer Genome Atlas (TCGA), pan-cancer analysis was performed to determine the correlation between important genes and AML or other cancers. Finally, the diagnostic value of important genes for AML was verified in different data sets.ResultsThe survival analysis results of the training set showed 26 genes with survival differences. After the intersection of the results of each machine learning method, DNM1, MEIS1, and SUSD3 were selected as key genes for subsequent analysis. The results of the pan-cancer analysis showed that MEIS1 and DNM1 were significantly highly expressed in AML; MEIS1 and SUSD3 are potential risk factors for the prognosis of AML, and DNM1 is a potential protective factor. Three key genes were significantly associated with AML immune subtypes and multiple immune checkpoints in AML. The results of the verification analysis show that DNM1, MEIS1, and SUSD3 have potential diagnostic value for AML.ConclusionMultiple machine learning methods identified DNM1, MEIS1, and SUSD3 can be regarded as prognostic biomarkers for AML.

The pathological reactions of brachial artery during and their significance in treatment of patients with chronic obstructive pulmonary disease

Background. The purpose of this study was to analyse the pathological reactions of brachial artery (BA) during test with reactive hyperemia (RH) for endothelial function (EF) estimation and their applicable significance in treatment of patients with chronic obstructive pulmonary disease (COPD). Material and methods. There were investigated 61 patients, mean age 47,7±5,11 years with moderate to severe forms of COPD (by GOLD criterion). Endothelial dysfunction (ED) estimation was performed non-invasive, using probe with RH with brachycephalic arteries Duplex with high resolution 8,0-10,0 MHz („Logiq S8” „General Electric”, SUA) by David S. Celermajer proposed method. ED was considered when EF index was less than 10%. Results. The analysis of obtained data revealed considerable decreasing of EF: mean EF index was 7,14±11,22%, between -15,0% and 29,4%. In 10 patients after RH test was noted pathological reaction of BA: instead of awaited endothelialdependent BA dilatation, there were observed spastic and negative reactions (in limits between 0% and −15,0%). In parallel there were visualized in a. carotis solitary and binary atherosclerotic plagues with 20-40% of vascular stenosis without any clinical manifestations. The levels of total cholesterol and LDL-C also were elevated: 7,5±2,0 mm/l и 4,7±1,8 mm/l, respectively. In all 10 patients with pathological BA reactions do not reduced mean and systolic pulmonary artery pressure after 5 weeks of treatment with perindopril (mean dose 2,9±1,5 mg once daily) or valsartan (mean dose 54,5±15,4 mg once daily). Conclusions. Thus, BA pathological reaction during RH test for ED estimation may be used like a criterion predictor of efficacity of treatment with perindopril or valsartan and for prognosis of survival in patients with severe forms of COPD.

Effects of oncoplastic breast-conserving surgery on the psychological status, quality of life and survival prognosis of patients with early-stage breast cancer

Effects of oncoplastic breast-conserving surgery on the psychological status, quality of life and survival prognosis of patients with early-stage breast cancer

The Impact of Proton Pump Inhibitors on the Efficacy of Immune Checkpoint Inhibitor Combinations in Patients with HBV-Associated Advanced Hepatocellular Carcinoma.

There is limited research on whether Proton Pump Inhibitors (PPIs) will affect the efficacy of immune checkpoint inhibitors (ICIs) in treating hepatocellular carcinoma (HCC).This study aimed to determine whether PPIs affect the survival outcomes of patients with HBV-associated advanced HCC receiving combination therapy based on ICIs. We retrospectively analyzed patients with hepatitis B virus (HBV)-associated advanced HCC who underwent ICIs combination therapy from January 1, 2020, to December 30, 2022. Patients were stratified into PPI and non-PPI groups based on whether they received PPI treatment within 30 days before or after ICIs therapy. Patients' survival and the risk of PPI-associated mortality was assessed. Adverse events were also evaluated. A total of 183 patients with HBV-associated HCC treated with ICI combination therapy were included. The median survival time (12.5 months vs 13.7 months, P = 0.285) and incidence of adverse events (P = 0.729) did not significantly differ between the PPI and non-PPI groups. Even after propensity score matching, the difference in median overall survival (OS) between the two groups was not significant (10.7 months vs 11.4 months; P = 0.596) and the patient's OS is not significantly related to the dosage of PPI application (P > 0.05).However, according to our subgroup analysis, among HCC patients with a serum HBV DNA concentration ≥ 200 IU/mL, the use of PPIs significantly increased the risk of mortality in patients receiving ICI combination therapy (P = 0.024). PPIs do not notably influence the survival prognosis of patients receiving ICI combination therapy for HBV-associated advanced HCC. However, among patients with high levels of HBV DNA, PPIs increase the risk of mortality. Therefore, antiviral therapy should be intensified in the patients with HBVDNA > 200 IU/mL. Additionally, PPIs do not impact the incidence of adverse reactions in these patients.

Combined learning models for survival analysis of patients with pulmonary hypertension

Background Pulmonary hypertension is a disease that manifests itself by excessive and chronic elevation of pressure in the pulmonary arteries. Pulmonary Hypertension (PH) presents non-specific initial symptoms, and this leads to an often-late diagnosis with a prognosis that can compromise the survival of the patient.Methods This paper will propose a combined methodological approach of the survival Support Vector Machine (SVM), Cox Proportional-Hazards Model (Cox-PHM), and Association Rule Mining (ARM) methods to examine the associated factors that are critical to the survival prognosis of patients with pulmonary hypertension (PAH).Results This approach was applied to data from 171 patients with PAH from 9 hospitals in 4 sub-Saharan African countries. For the study, nine PAH-related parameters were recorded for each patient. The SVM and Cox-PHM models showed that "Associated with Schistosomiasis" was the most significant parameter on death status. These allowed the ARM model to identify all the rules related to this significant parameter to provide more necessary information, such as detecting any other parameter that may enter the game with more precision.Conclusion The interpretation of results from the combined approach offers clarifications that are useful for a good understanding of the etiological factors and influential variables in the prognosis of survival of pulmonary hypertension. This provides an additional perspective in line with the messages of recent international recommendations which suggest that early diagnosis and treatment contribute to improving the vital prognosis of patients.

Multi‑dimensional analysis reveals NCKAP5L is a promising biomarker for the diagnosis and prognosis of human cancers, especially colorectal cancer.

The Nck-associated protein 5-like (NCKAP5L) gene, also known as Cep169, is associated with certain cancers. However, the diagnosis and prognosis value of NCKAP5L in several types of human cancer, including colorectal cancer, is not fully understood. In the present study, a comprehensive pan-cancer analysis of NCKAP5L was performed using several approaches, including gene expression and alteration, protein phosphorylation, immune infiltration, survival prognosis analyses and gene enrichment using the following: The University of California Santa Cruz Genome Browser Human Dec. 2013 (GRCh38/hg38) Assembly, Tumor Immune Estimation Resource (version 2), Human Protein Atlas, Gene Expression Profiling Interactive Analysis (version 2), University of Alabama at Birmingham Cancer Data Analysis portal, the Kaplan-Meier Plotter, cBioportal, Search Tool for the Retrieval of Interacting Genes/Proteins, Jvenn and the Metascape server. The role of NCKAP5L in colorectal cancer was further assessed by reverse transcription-quantitative PCR. The results demonstrated that NCKAP5L was upregulated in the majority of cancer types, including colorectal cancer. The high expression of NCKAP5L was significantly correlated with patient survival prognosis and immune infiltration of cancer-associated fibroblasts in numerous types of cancer, including colorectal cancer. Furthermore, Gene Ontology analysis identified that NCKAP5L may serve an important role in metabolic and cellular processes in human cancers. In summary, the data from the present study demonstrate that NCKAP5L is a potential tumor biomarker for the diagnosis and prognosis of human cancers, especially colorectal cancer.