Identification of ABCC5 Among ATP-Binding Cassette Transporter Family as a New Biomarker for Hepatocellular Carcinoma Based on Bioinformatics Analysis

Abstract

Liver cancer is the fifth most common type of cancer worldwide, and the ATPbinding cassette (ABC) transporter family has been widely accepted as a cause of multidrug resistance. This study was conducted to explore the potential value and mechanisms of the ABC transporter gene family in the liver hepatocellular carcinoma (LIHC). Materials and Methods: Data were collected from different public databases. UALCAN, ONCOMINE, and GEPIA were used to retrieve a selection of differently expressed and pathological stage-related genes among the ABC family. Principal component analysis (PCA) was utilized for grouping, and its prognostic value was evaluated by univariate and multivariate Cox analyses. The co-expression pattern was constructed with UALCAN, and the functional analyses were carried out with DAVID. The correlation between the biomarker and immune infiltration, genetic alteration frequency, and drug sensitivity were explored with TIMER, cBioPortal, GDSC and CTRP, respectively. Finally, tSNE algorithm was used to explore the distribution of ABCC5 expressed cells. Results: Among the ABC transporter family members, ABCC5 was differently expressed and strongly related to the pathological stage of LIHC. PCA divided patients of LIHC into two groups, and Cox analyses demonstrated that ABCC5 was an independent risk factor of LIHC. Functional analyses indicated that the genes were enriched in the pathways of transmembrane transporter, ATPase activity, and bile secretion. ABCC5 is also associated with immune infiltration of cells like macrophages, neutrophils, and dendritic cells. The genetic alteration frequency of ABCC5 confirmed its potential value in LIHC. In addition, several drugs were explored and found to be relevant to LIHC. The t-SNE showed that expression of ABCC5 was most concentrated in macrophages, followed by hepatocytes. Conclusion: ABCC5 may facilitate LIHC progression through different mechanisms and be a potential biomarker and target for diagnosis, prognosis, and therapy of LIHC.

Prognostic nutrition index is associated with the all‐cause mortality in sepsis patients: A retrospective cohort study

“…Sepsis, caused by infection, is a syndrome of the systemic inflammatory response 1,32 ; it is usually evaluated by measuring the body temperature, peripheral blood leukocyte count, neutrophil percentage, C‐reaction protein (CRP) levels, 33 and organ function. However, the sensitivity and specificity of these indicators remain poor; our findings further confirmed their low value in evaluating the severity of sepsis and failure to identify patients with potential poor prognoses 34,35 …”

“…However, the sensitivity and specificity of these indicators remain poor; our findings further confirmed their low value in evaluating the severity of sepsis and failure to identify patients with potential poor prognoses. 34,35 Nutritional status is closely linked to the prognosis of patients. 36,37 Inadequate nutrition leads to poorer survival outcomes in patients with sepsis.…”

“…However, the sensitivity and specificity of these indicators remain poor; our findings further confirmed their low value in evaluating the severity of sepsis and failure to identify patients with potential poor prognoses. 34 , 35 …”

Prognostic value of pulmonary ultrasound score combined with plasma miR‐21‐3p expression in patients with acute lung injury

“…Qiu et al Identified ABCC5 as a new biomarker of hepatocellular carcinoma by bioinformatics analysis. 10 Li et al 11 constructed a melanoma prognosis model based on apoptosis‐related genes using bioinformatics. miRNA is a kind of endogenous, non‐coding small molecule RNA that can regulate the expression of target genes and play an important role in cell proliferation, differentiation, apoptosis, angiogenesis, and inflammatory immune response.…”

Identification and Construction of a Predictive Immune-Related lncRNA Signature Model for Melanoma

“…For melanoma, which is a tumor with a poor prognosis, the establishment of an effective prognostic model and the exploration of its mechanism of action can improve the macrophages but negatively correlated with the abundance of CD8 + T cells. 19 M1 macrophages exhibit proinflammatory activity and play an antitumor role, while M2 macrophages exhibit anti-inflammatory activity and promote tumor growth. It has been shown that the antitumor effects of immune checkpoint inhibitors can be enhanced by repolarizing M2 macrophages into M1 macrophages, and CD8 T cells located at the melanoma tumor invasive margin can predict the clinical response to PD-1 blockade therapy and are positively correlated with the response to pembrolizumab.…”