The Human TOR Signaling Regulator Is the Key Indicator of Liver Cancer Patients' Overall Survival: TIPRL/LC3/CD133/CD44 as Potential Biomarkers for Early Liver Cancers

Abstract

Recently, we reported the involvement of TIPRL/LC3/CD133 in liver cancer aggressiveness. This study assessed the human TOR signaling regulator (TIPRL)/microtubule-associated light chain 3 (LC3)/prominin-1 (CD133)/cluster of differentiation 44 (CD44) as potential diagnostic and prognostic biomarkers for early liver cancer. For the assessment, we stained tissues of human liver disease/cancer with antibodies against TIPRL/LC3/CD133/CD44/CD46, followed by confocal observation. The roles of TIPRL/LC3/CD133/CD44/CD46 in liver normal and cancer cell lines were determined by in vitro studies. We analyzed the prognostic and diagnostic potentials of TIPRL/LC3/CD133/CD44/CD46 using the receiver-operating characteristic curve, a Kaplan-Meier and uni-/multi-Cox analyses. TIPRL and LC3 were upregulated in tissues of HCCs and adult hepatocytes-derived liver diseases while downregulated in iCCA. Intriguingly, TIPRL levels were found to be critically associated with liver cancer patients' survivability, and TIPRL is the key player in liver cancer cell proliferation and viability via stemness and self-renewal induction. Furthermore, we demonstrate that TIPRL/LC3/CD133 have shown prominent efficiency for diagnosing patients with grade 1 iCCA. TIPRL/LC3/CD133/CD44 have also provided excellent potential for prognosticating patients with grade 1 iCCA and grade 1 HCCs, together with demonstrating that TIPRL/LC3/CD133/CD44 are, either individually or in conjunction, potential biomarkers for early liver cancer.

Keywords: Kaplan–Meier analysis; cluster of differentiation 44 (CD44); hepatocellular carcinomas (HCCs); human TOR signaling regulator (TIPRL); intrahepatic carcinomas (iCCA); liver cancer; microtubule-associated light chain 3 (LC3); prominin-1 (CD133); receiver-operating characteristic (ROC) curve; uni-/multi-Cox analyses.

Figure 1

Differential expression of all five variables, depending on liver cancer cell types. Human liver cancer tissues were stained with the indicated antibodies followed by confocal observation. (A,C) The levels of all five variables were obtained using the ZEN program, and then global normalization was carried out (Tables S2 and S3). p-values (** p < 0.01; *** p < 0.001) were determined by a paired t-test, and % differences are shown. (n) is the number of samples. (B,D) The images represent normal and HCCs (B)/iCCA (D), respectively. DAPI was used for nucleus staining, and scar bars, 20 μm (inserted), and 100 μm.

Figure 2

TIPRL predicts the poor prognosis of liver disease patients. (A) The survival time of liver disease patients in the training set was calculated using the Kaplan–Meier estimator. HR, (95%CI), Log-rank and p-values are noted. (B) A public database (www.kmplot.com accessed on 12 January 2021) shows the survivability of liver cancer patients in each variable.

Figure 3

The prominent role of TIPRL in huh7, HCC, cell viability and stemness. Chang (A,C) and huh7 (A–F) cells were cultured, and then cells were seeded in a 96-well plate (A) or Anoikis plates (B,D–F) followed by transfected with the indicated siRNAs (100 nM). For cell proliferation (A) and viability (B) assays, 48 h after siRNA transfection, an MTT assay was performed. For quantification analysis of expression in stemness-related genes, we performed RT-qPCR using primers (C,D; Table S12). (E,F) We counted the numbers of spheroids after 72 h siRNAs transfection. TSFE, tumorsphere formation efficiency: [(the number of tumorspheres formed/the initial number of cells seeded) × 100]. All experiments were independently repeated three times. ** p < 0.01, *** p < 0.001 by unpaired t-test. ns, not significant.

Figure 4

The significant diagnostic and prognostic efficacies of the variables, TIPRL, LC3, and CD133, excluding CD46, as a single or in conjunction for grade 1 iCCA. (A,B) The diagnostic and (C,D) prognostic potentials of the variables were determined using ROC analysis. AUC, the area under the curve, and CI, confidence interval. The number of cancer grade 1 used = 82.