An Algorithm that Predicts the Viability and the Yield of Human Hepatocytes Isolated from Remnant Liver Pieces Obtained from Liver Resections

<div><p>Isolated human primary hepatocytes are an essential <i>in vitro</i> model for basic and clinical research. For successful application as a model, isolated hepatocytes need to have a good viability and be available in sufficient yield. Therefore, this study aims to identify donor characteristics, intra-operative factors, tissue processing and cell isolation parameters that affect the viability and yield of human hepatocytes. Remnant liver pieces from tissue designated as surgical waste were collected from 1034 donors with informed consent. Human hepatocytes were isolated by a two-step collagenase perfusion technique with modifications and hepatocyte yield and viability were subsequently determined. The accompanying patient data was collected and entered into a database. Univariate analyses found that the viability and the yield of hepatocytes were affected by many of the variables examined. Multivariate analyses were then carried out to confirm the factors that have a significant relationship with the viability and the yield. It was found that the viability of hepatocytes was significantly decreased by the presence of fibrosis, liver fat and with increasing gamma-glutamyltranspeptidase activity and bilirubin content. Yield was significantly decreased by the presence of liver fat, septal fibrosis, with increasing aspartate aminotransferase activity, cold ischemia times and weight of perfused liver. However, yield was significantly increased by chemotherapy treatment. In conclusion, this study determined the variables that have a significant effect on the viability and the yield of isolated human hepatocytes. These variables have been used to generate an algorithm that can calculate projected viability and yield of isolated human hepatocytes. In this way, projected viability can be determined even before isolation of hepatocytes, so that donors that result in high viability and yield can be identified. Further, if the viability and yield of the isolated hepatocytes is lower than expected, this will highlight a methodological problem that can be addressed.</p></div

Liver variables that have significant relationships with the viability (%) of hepatocytes after linear regression analyses.

<p>Figures show relationships between viability and (<b>A</b>) fibrosis, (<b>B</b>) liver fat or (<b>C</b>) Ludwig score. Values were deemed significant when P<0.05. For the variable of Ludwig score, variables not sharing the same alphabet are significantly different, <i>P</i><0.05.</p

Variables considered for statistical analyses.

<p>Variables considered for statistical analyses.</p

Variables measured in the blood or serum that have significant relationships with the yield (million hepatocytes/gram liver) after linear regression analyses.

<p>Figures show relationships between yield and (<b>A</b>) alkaline phosphatase activity (AP; U/L), (<b>B</b>) aspartate aminotransferase activity (GOT; U/L), (<b>C</b>) gamma-glutamyltranspeptidase activity (GGT; U/L), (<b>D</b>) alanine aminotransferase activity (GPT; U/L), (<b>E</b>) bilirubin (mg/dL), (<b>F</b>) partial thromboplastin time (PTT; s) or (<b>G</b>) quick value (%). Values were deemed significant when P<0.05.</p

The number of replicates (<i>N</i>) and the <i>P</i> values obtained after linear regression of the individual variables listed below to viability (%) or yield (million hepatocytes/g liver) of isolated human hepatocytes.

<p>*Significant at <i>P</i><0.05. Data are transformed to follow a normal distribution by logit¹, fourth root² or natural logarithm³ transformation.</p><p>The number of replicates (<i>N</i>) and the <i>P</i> values obtained after linear regression of the individual variables listed below to viability (%) or yield (million hepatocytes/g liver) of isolated human hepatocytes.</p

The model for calculating projected viability is appropriate.

<p>(<b>A</b>) Residuals versus fitted plot. (<b>B</b>) Normal quantile plot. (<b>C</b>) Square root of the standardised residuals versus fitted plot. (<b>D</b>) Standardised residuals versus leverage plot.</p

The model for calculating projected yield is appropriate.

<p>(<b>A</b>) Residuals versus fitted plot. (<b>B</b>) Normal quantile plot. (<b>C</b>) Square root of the standardised residuals versus fitted plot. (<b>D</b>) Standardised residuals versus leverage plot.</p

Liver variables that have significant relationships with the yield (million hepatocytes/gram liver) of hepatocytes after linear regression analyses.

<p>Figures show relationships between yield and (<b>A</b>) cirrhosis, (<b>B</b>) liver fat, (<b>C</b>) liver fat (%) or (<b>D</b>) Ludwig score. Values were deemed significant when P<0.05. For the variables of Ludwig score, operation type and surgical indication, variables not sharing the same alphabet are significantly different, <i>P</i><0.05.</p

Tissue processing and cell isolation variables that have significant relationships with the yield (million hepatocytes/gram liver) of hepatocytes after linear regression analyses.

<p>Figures show relationships between yield and (<b>A</b>) warm ischemia <i>ex vivo</i> (min) or (<b>B</b>) weight of perfused liver (g). Values were deemed significant when P<0.05.</p

Operation variables that have significant relationships with the yield (million hepatocytes/gram liver) of hepatocytes after linear regression analyses.

<p>Figures show relationships between yield and (<b>A</b>) surgical indication, (<b>B</b>) operation type, (<b>C</b>) warm ischemia <i>in vivo</i> (min) or (<b>D</b>) weight of resected liver (g). Values were deemed significant when P<0.05. Abbreviations; hepatocarcinoma (HCC), focal nodular hyperplasia (FNH), cholangiocarcinoma (CCC), hemihepatectomy right (HR), hemihepatectomy left (HL), segment resection (SR), atypical resection (AR), extended hepatectomy (EH), lobectomy (L) and liver transplantation (LT).</p