Hypomethylation of ATP1A1 Is Associated with Poor Prognosis and Cancer Progression in Triple-Negative Breast Cancer.

Dysregulated DNA methylation in cancer is critical in the transcription machinery associated with cancer progression. Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, but no treatment targeting TNBC biomarkers has yet been developed. To identify specific DNA methylation patterns in TNBC, methyl-binding domain protein 2 (MBD) sequencing data were compared in TNBC and the three other major breast cancer subtypes. Integrated analysis of DNA methylation and gene expression identified a gene set showing a correlation between DNA methylation and gene expression. ATPase Na+/K+-transporting subunit alpha 1 (ATP1A1) was found to be specifically hypomethylated in the coding sequence (CDS) region and to show increased expression in TNBC. The Cancer Genome Atlas (TCGA) database also showed that hypomethylation and high expression of ATP1A1 were strongly associated with poor survival in patients with TNBC. Furthermore, ATP1A1 knockdown significantly reduced the viability and tumor-sphere formation of TNBC cells. These results suggest that the hypomethylation and overexpression of ATP1A1 could be a prognostic marker in TNBC and that the manipulation of ATP1A1 expression could be a therapeutic target in this disease.

Computational drug repositioning with attention walking.

Drug repositioning aims to identify new therapeutic indications for approved medications. Recently, the importance of computational drug repositioning has been highlighted because it can reduce the costs, development time, and risks compared to traditional drug discovery. Most approaches in this area use networks for systematic analysis. Inferring drug-disease associations is then defined as a link prediction problem in a heterogeneous network composed of drugs and diseases. In this article, we present a novel method of computational drug repositioning, named drug repositioning with attention walking (DRAW). DRAW proceeds as follows: first, a subgraph enclosing the target link for prediction is extracted. Second, a graph convolutional network captures the structural features of the labeled nodes in the subgraph. Third, the transition probabilities are computed using attention mechanisms and converted into random walk profiles. Finally, a multi-layer perceptron takes random walk profiles and predicts whether a target link exists. As an experiment, we constructed two heterogeneous networks with drug-drug similarities based on chemical structures and anatomical therapeutic chemical classification (ATC) codes. Using 10-fold cross-validation, DRAW achieved an area under the receiver operating characteristic (ROC) curve of 0.903 and outperformed state-of-the-art methods. Moreover, we demonstrated the results of case studies for selected drugs and diseases to further confirm the capability of DRAW to predict drug-disease associations.

Novel Potential Therapeutic Targets in Autosomal Dominant Polycystic Kidney Disease from the Perspective of Cell Polarity and Fibrosis.

Autosomal dominant polycystic kidney disease (ADPKD), a congenital genetic disorder, is a notable contributor to the prevalence of chronic kidney disease worldwide. Despite the absence of a complete cure, ongoing research aims for early diagnosis and treatment. Although agents such as tolvaptan and mTOR inhibitors have been utilized, their effectiveness in managing the disease during its initial phase has certain limitations. This review aimed to explore new targets for the early diagnosis and treatment of ADPKD, considering ongoing developments. We particularly focus on cell polarity, which is a key factor that influences the process and pace of cyst formation. In addition, we aimed to identify agents or treatments that can prevent or impede the progression of renal fibrosis, ultimately slowing its trajectory toward end-stage renal disease. Recent advances in slowing ADPKD progression have been examined, and potential therapeutic approaches targeting multiple pathways have been introduced. This comprehensive review discusses innovative strategies to address the challenges of ADPKD and provides valuable insights into potential avenues for its prevention and treatment.

Primary Cilium in Neural Crest Cells Crucial for Anterior Segment Development and Corneal Avascularity.

Purpose: Intraflagellar transport 46 (IFT46) is an integral subunit of the IFT-B complex, playing a key role in the assembly and maintenance of primary cilia responsible for transducing signaling pathways. Despite its predominant expression in the basal body of cilia, the precise role of Ift46 in ocular development remains undetermined. This study aimed to elucidate the impact of neural crest (NC)-specific deletion of Ift46 on ocular development. Methods: NC-specific conditional knockout mice for Ift46 (NC-Ift46F/F) were generated by crossing Ift46F mice with Wnt1-Cre2 mice, enabling the specific deletion of Ift46 in NC-derived cells (NCCs). Sonic Hedgehog (Shh) and Notch signaling activities in NC-Ift46F/F mice were evaluated using Gli1lacZ and CBF:H2B-Venus reporter mice, respectively. Cell fate mapping was conducted using ROSAmTmG reporter mice. Results: The deletion of Ift46 in NCCs resulted in a spectrum of ocular abnormalities, including thickened corneal stroma, hypoplasia of the anterior chamber, irregular iris morphology, and corneal neovascularization. Notably, this deletion led to reduced Shh signal activity in the periocular mesenchyme, sustained expression of key transcription factors Foxc1, Foxc2 and Pitx2, along with persistent cell proliferation. Additionally, it induced increased Notch signaling activity and the development of ectopic neovascularization within the corneal stroma. Conclusions: The absence of primary cilia due to Ift46 deficiency in NCCs is associated with anterior segment dysgenesis (ASD) and corneal neovascularization, suggesting a potential link to Axenfeld-Rieger syndrome, a disorder characterized by ASD. This underscores the pivotal role of primary cilia in ensuring proper anterior segment development and maintaining an avascular cornea.

Integrative transcriptomic and genomic analyses unveil the IFI16 variants and expression as MASLD progression markers.

BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a broad and continuous spectrum of liver diseases ranging from fatty liver to steatohepatitis. The intricate interactions of genetic, epigenetic, and environmental factors in the development and progression of MASLD remain elusive. Here, we aimed to achieve an integrative understanding of the genomic and transcriptomic alterations throughout the progression of MASLD. APPROACH AND RESULTS: RNA-Seq profiling (n = 146) and whole-exome sequencing (n = 132) of MASLD liver tissue samples identified 3 transcriptomic subtypes (G1-G3) of MASLD, which were characterized by stepwise pathological and molecular progression of the disease. Macrophage-driven inflammatory activities were identified as a key feature for differentiating these subtypes. This subtype-discriminating macrophage interplay was significantly associated with both the expression and genetic variation of the dsDNA sensor IFI16 (rs6940, A>T, T779S), establishing it as a fundamental molecular factor in MASLD progression. The in vitro dsDNA-IFI16 binding experiments and structural modeling revealed that the IFI16 variant exhibited increased stability and stronger dsDNA binding affinity compared to the wild-type. Further downstream investigation suggested that the IFI16 variant exacerbated DNA sensing-mediated inflammatory signals through mitochondrial dysfunction-related signaling of the IFI16-PYCARD-CASP1 pathway. CONCLUSIONS: This study unveils a comprehensive understanding of MASLD progression through transcriptomic classification, highlighting the crucial roles of IFI16 variants. Targeting the IFI16-PYCARD-CASP1 pathway may pave the way for the development of novel diagnostics and therapeutics for MASLD.

Identification of signature gene set as highly accurate determination of metabolic dysfunction-associated steatotic liver disease progression.

BACKGROUND/AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. METHODS: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. RESULTS: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. CONCLUSION: We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

A Decline in Overutilization of Transfusion after Total Knee Arthroplasty Using Pharmacological Agents for Patient Blood Management in South Korea: An Analysis Based on the Korean National Health Insurance Claims Database from 2008 to 2019.

Background: This study aimed to evaluate the annual trends of transfusion rates and utilization of blood management agents in total knee arthroplasty (TKA) based on the operation type and to analyze the risk factors of transfusion after TKA. Methods: Using the Korean National Insurance claims database of 797,106 primary and revision TKAs between January 2008 and October 2019, data on the patients' characteristics, comorbidities, utilization of transfusion, and blood management agents were collected. The patients were categorized into three groups based on the operation type: primary, revision, and simultaneous bilateral TKA. The transfusion rate and utilization of blood management agents (intraoperative tranexamic acid [TXA] and preoperative iron supplements) were compared, and the risk factors for transfusion were evaluated. Results: After excluding the inaccurate data, 730,554 arthroplasties (636,292 primary, 10,540 revision, and 41,861 simultaneous bilateral TKAs) were identified. The transfusion rates of primary, revision, and simultaneous bilateral TKAs in 2019 were 64.0%, 67.7%, and 68.9%, respectively, which were significantly decreased compared with 83.2%, 88.0%, and 92.5% in 2008, respectively (p < 0.001). Conversely, the utilization of intraoperative TXA and preoperative iron supplements was significantly increased from 4.6% and 13.8%, respectively, in 2008 to 52.4% and 27.0%, respectively, in 2019 (p < 0.001). The utilization of intraoperative TXA and preoperative iron supplements significantly lowered the risk of transfusion after TKA (odds ratio [OR], 0.20; p < 0.001 and OR, 0.71; p < 0.001). Conclusions: The transfusion rate after TKA decreased gradually from 83.5% to 64.5% between 2008 and 2019 in South Korea corresponding with the increased utilization of blood management agents. Therefore, consistent attention to patient blood management should be emphasized to reduce the transfusion rate after TKA.

Long non-coding RNAs: key regulators of liver and kidney fibrogenesis.

Fibrosis is a pathological condition that is characterized by an abnormal buildup of extracellular matrix (ECM) components, such as collagen, in tissues. This condition affects various organs of the body, including the liver and kidney. Early diagnosis and treatment of fibrosis are crucial, as it is a progressive and irreversible process in both organs. While there are certain similarities in the fibrosis process between the liver and kidney, there are also significant differences that must be identified to determine molecular diagnostic markers and potential therapeutic targets. Long non-coding RNAs (lncRNAs), a class of RNA molecules that do not code for proteins, are increasingly recognized as playing significant roles in gene expression regulation. Emerging evidence suggests that specific lncRNAs are involved in fibrosis development and progression by modulating signaling pathways, such as the TGF-ß/Smad pathway and the ß-catenin pathway. Thus, identifying the precise lncRNAs involved in fibrosis could lead to novel therapeutic approaches for fibrotic diseases. In this review, we summarize lncRNAs related to fibrosis in the liver and kidney, and propose their potential as therapeutic targets based on their functions. [BMB Reports 2023; 56(7): 374-384].

Effects of Whey Protein Supplement on 4-Week Resistance Exercise-Induced Improvements in Muscle Mass and Isokinetic Muscular Function under Dietary Control.

(1) The purpose of this study was to investigate the effect of whey protein supplementation under dietary control on improvements in muscle mass and function following resistance exercise training. (2) Thirty-two men were randomly assigned to a whey protein supplementation group taking whey protein isolate (PSG, n = 17) and a placebo group (CON, n = 15). Participants were provided with three meals per day corresponding to the estimated individual daily energy intake. The supervised resistance exercise program was conducted 60 min per day, six days per week, for four weeks. (3) Post-intervention, there was a significant interaction between groups in terms of muscle mass increase (p = 0.033, η2 = 0.14), with a greater increase in the PSG. There were also significant interactions between the groups and increases in peak torque of the dominant knee flexors (p = 0.048, η2 = 0.12), dominant shoulder extensors, and non-dominant shoulder extensors (p = 0.028, η2 = 0.15; p = 0.015, η2 = 0.18), and the total work of the dominant knee and shoulder extensors (p = 0.012, η2 = 0.19; p = 0.013, η2 = 0.19), with greater increases in the PSG. (4) These results suggest that whey protein supplementation enhances resistance exercise-induced increase in muscle mass and overall muscular strength and endurance, independent of dietary influence.

Effect of a Patient Blood Management Program on the Appropriateness of Red Blood Cell Transfusion and Clinical Outcomes in Elderly Patients Undergoing Hip Fracture Surgery.

BACKGROUND: Elderly patients with hip fractures frequently receive perioperative transfusions, which are associated with increased morbidity and mortality. This study aimed to evaluate the impact of a patient blood management (PBM) program on the appropriateness of red blood cell (RBC) transfusion and clinical outcomes in geriatric patients undergoing hip fracture surgery. METHODS: In 2018, the revised PBM program was implemented at the Korea University Anam Hospital, Seoul, Republic of Korea. Elderly patients aged ≥ 65 years who underwent hip fracture surgery from 2017 to 2020 were evaluated. Clinical characteristics and outcomes were analyzed according to the timing of PBM implementation (pre-PBM, early-PBM, and late-PBM). Multiveriate regression analysis was used to evaluate the risk factors of the adverse outcomes, such as in-hospital mortality or 30-day readmission. RESULTS: A total of 884 elderly patients were included in this study. The proportion of patients who received perioperative RBC transfusions decreased significantly (43.5%, 40.1%, and 33.2% for pre-PBM, early-PBM, and late-PBM, respectively; P = 0.013). However, the appropriateness of RBC transfusion significantly increased (54.0%, 60.1%, and 94.7%, respectively; P < 0.001). The duration of in-hospital stay and 30-day readmission rates significantly decreased. Multivariable regression analysis revealed that RBC transfusion (odds ratio, 1.815; 95% confidence interval, 1.137-2.899; P = 0.013) was significantly associated with adverse outcomes. CONCLUSION: Implementing the PBM program increased the appropriateness of RBC transfusion without compromising transfusion quality and clinical outcomes. Therefore, adopting the PBM program may improve the clinical management of elderly patients following hip fracture surgery.

Transcriptional programming of pathogenic genes in polycystic kidney disease.

Transcriptional dysregulation is a prominent contributor to the pathogenesis of autosomal dominant polycystic kidney disease. Lakhia et al. identified an enhancer landscape associated with disease genes and its pathologic role in autosomal dominant polycystic kidney disease to understand cyst formation. This commentary discusses these findings reported by Lakhia et al. in the broader contexts of transcriptional programming and the identification of potential autosomal dominant polycystic kidney disease therapeutic targets.

Blood Transfusion, All-Cause Mortality and Hospitalization Period in COVID-19 Patients: Machine Learning Analysis of National Health Insurance Claims Data.

This study presents the most comprehensive machine-learning analysis for the predictors of blood transfusion, all-cause mortality, and hospitalization period in COVID-19 patients. Data came from Korea National Health Insurance claims data with 7943 COVID-19 patients diagnosed during November 2019−May 2020. The dependent variables were all-cause mortality and the hospitalization period, and their 28 independent variables were considered. Random forest variable importance (GINI) was introduced for identifying the main factors of the dependent variables and evaluating their associations with these predictors, including blood transfusion. Based on the results of this study, blood transfusion had a positive association with all-cause mortality. The proportions of red blood cell, platelet, fresh frozen plasma, and cryoprecipitate transfusions were significantly higher in those with death than in those without death (p-values < 0.01). Likewise, the top ten factors of all-cause mortality based on random forest variable importance were the Charlson Comorbidity Index (53.54), age (45.68), socioeconomic status (45.65), red blood cell transfusion (27.08), dementia (19.27), antiplatelet (16.81), gender (14.60), diabetes mellitus (13.00), liver disease (11.19) and platelet transfusion (10.11). The top ten predictors of the hospitalization period were the Charlson Comorbidity Index, socioeconomic status, dementia, age, gender, hemiplegia, antiplatelet, diabetes mellitus, liver disease, and cardiovascular disease. In conclusion, comorbidity, red blood cell transfusion, and platelet transfusion were the major factors of all-cause mortality based on machine learning analysis. The effective management of these predictors is needed in COVID-19 patients.

Drug-Disease Association Prediction Using Heterogeneous Networks for Computational Drug Repositioning.

Drug repositioning, which involves the identification of new therapeutic indications for approved drugs, considerably reduces the time and cost of developing new drugs. Recent computational drug repositioning methods use heterogeneous networks to identify drug-disease associations. This review reveals existing network-based approaches for predicting drug-disease associations in three major categories: graph mining, matrix factorization or completion, and deep learning. We selected eleven methods from the three categories to compare their predictive performances. The experiment was conducted using two uniform datasets on the drug and disease sides, separately. We constructed heterogeneous networks using drug-drug similarities based on chemical structures and ATC codes, ontology-based disease-disease similarities, and drug-disease associations. An improved evaluation metric was used to reflect data imbalance as positive associations are typically sparse. The prediction results demonstrated that methods in the graph mining and matrix factorization or completion categories performed well in the overall assessment. Furthermore, prediction on the drug side had higher accuracy than on the disease side. Selecting and integrating informative drug features in drug-drug similarity measurement are crucial for improving disease-side prediction.

MicroRNA-dependent inhibition of WEE1 controls cancer stem-like characteristics and malignant behavior in ovarian cancer.

Cancer stem-like cells (CSCs) have been suggested to be responsible for chemoresistance and tumor recurrence owing to their self-renewal capacity and differentiation potential. Although WEE1 is a strong candidate target for anticancer therapies, its role in ovarian CSCs is yet to be elucidated. Here, we show that WEE1 plays a key role in regulating CSC properties and tumor resistance to carboplatin via a microRNA-dependent mechanism. We found that WEE1 expression is upregulated in ovarian cancer spheroids because of the decreased expression of miR-424 and miR-503, which directly target WEE1. The overexpression of miR-424/503 suppressed CSC activity by inhibiting WEE1 expression, but this effect was reversed on the restoration of WEE1 expression. Furthermore, we demonstrated that NANOG modulates the miR-424/503-WEE1 axis that regulates the properties of CSCs. We also demonstrated the pharmacological restoration of the NANOG-miR-424/503-WEE1 axis and attenuation of ovarian CSC characteristics in response to atorvastatin treatment. Lastly, miR-424/503-mediated WEE1 inhibition re-sensitized chemoresistant ovarian cancer cells to carboplatin. Additionally, combined treatment with atorvastatin and carboplatin synergistically reduced tumor growth, chemoresistance, and peritoneal seeding in the intraperitoneal mouse models of ovarian cancer. We identified a novel NANOG-miR-424/503-WEE1 pathway for regulating ovarian CSCs, which has potential therapeutic utility in ovarian cancer treatment.

KLC3 Regulates Ciliary Trafficking and Cyst Progression in CILK1 Deficiency-Related Polycystic Kidney Disease.

BACKGROUND: Ciliogenesis-associated kinase 1 (CILK1) is a ciliary gene that localizes in primary cilia and regulates ciliary transport. Mutations in CILK1 cause various ciliopathies. However, the pathogenesis of CILK1-deficient kidney disease is unknown. METHODS: To examine whether CILK1 deficiency causes PKD accompanied by abnormal cilia, we generated mice with deletion of Cilk1 in cells of the renal collecting duct. A yeast two-hybrid system and coimmunoprecipitation (co-IP) were used to identify a novel regulator, kinesin light chain-3 (KLC3), of ciliary trafficking and cyst progression in the Cilk1-deficient model. Immunocytochemistry and co-IP were used to examine the effect of KLC3 on ciliary trafficking of the IFT-B complex and EGFR. We evaluated the effects of these genes on ciliary trafficking and cyst progression by modulating CILK1 and KLC3 expression levels. RESULTS: CILK1 deficiency leads to PKD accompanied by abnormal ciliary trafficking. KLC3 interacts with CILK1 at cilia bases and is increased in cyst-lining cells of CILK1-deficient mice. KLC3 overexpression promotes ciliary recruitment of IFT-B and EGFR in the CILK1 deficiency condition, which contributes to the ciliary defect in cystogenesis. Reduction in KLC3 rescued the ciliary defects and inhibited cyst progression caused by CILK1 deficiency. CONCLUSIONS: Our findings suggest that CILK1 deficiency in renal collecting ducts leads to PKD and promotes ciliary trafficking via increased KLC3.

Network-Based Approaches for Disease-Gene Association Prediction Using Protein-Protein Interaction Networks.

Genome-wide association studies (GWAS) can be used to infer genome intervals that are involved in genetic diseases. However, investigating a large number of putative mutations for GWAS is resource- and time-intensive. Network-based computational approaches are being used for efficient disease-gene association prediction. Network-based methods are based on the underlying assumption that the genes causing the same diseases are located close to each other in a molecular network, such as a protein-protein interaction (PPI) network. In this survey, we provide an overview of network-based disease-gene association prediction methods based on three categories: graph-theoretic algorithms, machine learning algorithms, and an integration of these two. We experimented with six selected methods to compare their prediction performance using a heterogeneous network constructed by combining a genome-wide weighted PPI network, an ontology-based disease network, and disease-gene associations. The experiment was conducted in two different settings according to the presence and absence of known disease-associated genes. The results revealed that HerGePred, an integrative method, outperformed in the presence of known disease-associated genes, whereas PRINCE, which adopted a network propagation algorithm, was the most competitive in the absence of known disease-associated genes. Overall, the results demonstrated that the integrative methods performed better than the methods using graph-theory only, and the methods using a heterogeneous network performed better than those using a homogeneous PPI network only.

Comparison of Denosumab and Zoledronic Acid in Postmenopausal Women With Osteoporosis: Bone Mineral Density (BMD) and Trabecular Bone Score (TBS).

BACKGROUND: Denosumab (DEN) and zoledronic acid (ZOL) currently represent the most potent antiresorptive agents for the treatment of osteoporosis. Despite similar effects on bone resorption, these agents have distinct mechanisms of action. The objective of this study was to compare the effect of DEN and ZOL after two-year administration on bone mineral density (BMD), trabecular bone score (TBS), bone turnover markers, and persistence. METHODS: A total of 585 postmenopausal women with osteoporosis who did not use osteoporosis medications were retrospectively reviewed. 290 patients were administered 60 mg DEN subcutaneously every 6 months from 2017 to 2018, and 295 patients were treated with 5 mg ZOL intravenously yearly from 2015 to 2017. BMD, TBS, and C-terminal cross-linking telopeptide of type 1 collagen (CTX) measurements were obtained at baseline and two-year after DEN injection or ZOL infusion. RESULTS: After two-year follow-up, 188 patients in the DEN group and 183 patients in the ZOL group were compared. BMD change from baseline at two years was significantly greater in the DEN group compared with the ZOL group (P < 0.001). The changes of TBS in the DEN group were statistically significant compared with baseline (P < 0.001) and the ZOL group (P < 0.001). The DEN group led to significantly greater reduction of CTX compared with ZOL group (P = 0.041). CONCLUSION: In postmenopausal women with osteoporosis, DEN was associated with greater BMD increase at all measured skeletal sites, greater increase of TBS, and greater inhibition of bone remodeling compared with ZOL.

Reduced miR-371b-5p expression drives tumor progression via CSDE1/RAC1 regulation in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer; however, specific prognostic biomarkers have not yet been developed. In this study, we identified dysregulated microRNAs (miRNAs) in TNBC by profiling miRNA and mRNA expression. In patients with TNBC, miR-371b-5p expression was reduced, and miR-371b-5p overexpression significantly mitigated TNBC cell growth, migration, and invasion. In addition, we found that expression of cold shock domain-containing protein E1 (CSDE1), a direct target gene of miR-371b-5p, was upregulated in TNBC cells, and inhibition of CSDE1 expression alleviated TNBC cell growth by regulating RAC1 transcription. Mechanistically, CSDE1, phosphorylated C-terminal domain (p-CTD) of RNA polymerase II (RNAPII), and CDK7 form a complex, and downregulation of CSDE1 leads to weak interaction between RNAPII p-CTD and CDK7, resulting in a decrease in RNAPII p-CTD expression to reduce RAC1 transcript levels in CSDE1-deficient TNBC cells. Our data demonstrate that miR-371b-5p is a tumor-suppressive miRNA that regulates the CSDE1/Rac1 axis and could be a potential prognostic biomarker for TNBC.

Blood transfusion has an adverse impact on the prognosis of patients receiving chemotherapy for advanced colorectal cancer: experience from a single institution with a patient blood management program.

PURPOSE: Perioperative blood transfusion in early stage cancer patients had a negative effect on the prognosis of patients, but the prognostic impact of transfusion in advanced cancer patients remains unclear. To minimize and guide rational transfusion, an institutional patient blood management (PBM) program was launched, and we evaluated the new program that has changed the practice and impacted on the prognosis of advanced cancer patients. METHODS: We investigated the medical records of colorectal cancer patients who received chemotherapy from 2015 to 2020. The amount and frequency of transfusion, iron replacement and laboratory findings, and overall survival were compared before and after implementation of PBM. RESULTS: The rate of transfusion in colorectal cancer patients was significantly decreased from 23.5/100 person-quarter in 2015 to 1.2/100 person-quarter in 2020, but iron supplementation therapy was frequently used, and the proportion of patients who received transfusion under hemoglobin 7 g/dL significantly increased from 15.9% in 2015 to 55.3% in 2020. Multivariate analysis revealed that transfusion was a significant risk factor affecting the overall survival of patients (HR 2.70, 95% CI: 1.93-3.78, p<0.001). Kaplan-Meier analysis revealed that overall survival was significantly longer in non-transfused patients than in transfused patients (11.0 versus 22.4 months; HR 0.69, 95% CI: 0.56-0.86, p<0.001). CONCLUSIONS: This study shows that minimized transfusion through an institutional PBM can positively affect the prognosis of patients who are receiving chemotherapy for advanced colorectal cancer.