Development and validation of a REcurrent Liver cAncer Prediction ScorE (RELAPSE) following liver transplantation in patients with hepatocellular carcinoma: Analysis of the US Multicenter HCC Transplant Consortium

HCC recurrence following liver transplantation (LT) is highly morbid and occurs despite strict patient selection criteria. Individualized prediction of post-LT HCC recurrence risk remains an important need. Clinico-radiologic and pathologic data of 4981 patients with HCC undergoing LT from the US Multicenter HCC Transplant Consortium (UMHTC) were analyzed to develop a REcurrent Liver cAncer Prediction ScorE (RELAPSE). Multivariable Fine and Gray competing risk analysis and machine learning algorithms (Random Survival Forest and Classification and Regression Tree models) identified variables to model HCC recurrence. RELAPSE was externally validated in 1160 HCC LT recipients from the European Hepatocellular Cancer Liver Transplant study group. Of 4981 UMHTC patients with HCC undergoing LT, 71.9% were within Milan criteria, 16.1% were initially beyond Milan criteria with 9.4% downstaged before LT, and 12.0% had incidental HCC on explant pathology. Overall and recurrence-free survival at 1, 3, and 5 years was 89.7%, 78.6%, and 69.8% and 86.8%, 74.9%, and 66.7%, respectively, with a 5-year incidence of HCC recurrence of 12.5% (median 16 months) and non-HCC mortality of 20.8%. A multivariable model identified maximum alpha-fetoprotein (HR = 1.35 per-log SD, 95% CI,1.22-1.50, p < 0.001), neutrophil-lymphocyte ratio (HR = 1.16 per-log SD, 95% CI,1.04-1.28, p < 0.006), pathologic maximum tumor diameter (HR = 1.53 per-log SD, 95% CI, 1.35-1.73, p < 0.001), microvascular (HR = 2.37, 95%-CI, 1.87-2.99, p < 0.001) and macrovascular (HR = 3.38, 95% CI, 2.41-4.75, p < 0.001) invasion, and tumor differentiation (moderate HR = 1.75, 95% CI, 1.29-2.37, p < 0.001; poor HR = 2.62, 95% CI, 1.54-3.32, p < 0.001) as independent variables predicting post-LT HCC recurrence (C-statistic = 0.78). Machine learning algorithms incorporating additional covariates improved prediction of recurrence (Random Survival Forest C-statistic = 0.81). Despite significant differences in European Hepatocellular Cancer Liver Transplant recipient radiologic, treatment, and pathologic characteristics, external validation of RELAPSE demonstrated consistent 2- and 5-year recurrence risk discrimination (AUCs 0.77 and 0.75, respectively). We developed and externally validated a RELAPSE score that accurately discriminates post-LT HCC recurrence risk and may allow for individualized post-LT surveillance, immunosuppression modification, and selection of high-risk patients for adjuvant therapies.

HCC EV ECG score: An extracellular vesicle-based protein assay for detection of early-stage hepatocellular carcinoma

BACKGROUND AND AIMS

The sensitivity of current surveillance methods for detecting early-stage hepatocellular carcinoma (HCC) is suboptimal. Extracellular vesicles (EVs) are promising circulating biomarkers for early cancer detection. In this study, we aim to develop an HCC EV-based surface protein assay for early detection of HCC.

APPROACH AND RESULTS

Tissue microarray was used to evaluate four potential HCC-associated protein markers. An HCC EV surface protein assay, composed of covalent chemistry-mediated HCC EV purification and real-time immuno-polymerase chain reaction readouts, was developed and optimized for quantifying subpopulations of EVs. An HCC EV ECG score, calculated from the readouts of three HCC EV subpopulations ( E pCAM + CD63 + , C D147 + CD63 + , and G PC3 + CD63 + HCC EVs), was established for detecting early-stage HCC. A phase 2 biomarker study was conducted to evaluate the performance of ECG score in a training cohort ( n  = 106) and an independent validation cohort ( n  = 72).Overall, 99.7% of tissue microarray stained positive for at least one of the four HCC-associated protein markers (EpCAM, CD147, GPC3, and ASGPR1) that were subsequently validated in HCC EVs. In the training cohort, HCC EV ECG score demonstrated an area under the receiver operating curve (AUROC) of 0.95 (95% confidence interval [CI], 0.90-0.99) for distinguishing early-stage HCC from cirrhosis with a sensitivity of 91% and a specificity of 90%. The AUROCs of the HCC EV ECG score remained excellent in the validation cohort (0.93; 95% CI, 0.87-0.99) and in the subgroups by etiology (viral: 0.95; 95% CI, 0.90-1.00; nonviral: 0.94; 95% CI, 0.88-0.99).

CONCLUSION

HCC EV ECG score demonstrated great potential for detecting early-stage HCC. It could augment current surveillance methods and improve patients' outcomes.

Coupling Lipid Labeling and Click Chemistry Enables Isolation of Extracellular Vesicles for Noninvasive Detection of Oncogenic Gene Alterations

Well-preserved molecular cargo in circulating extracellular vesicles (EVs) offers an ideal material for detecting oncogenic gene alterations in cancer patients, providing a noninvasive diagnostic solution for detection of disease status and monitoring treatment response. Therefore, technologies that conveniently isolate EVs with sufficient efficiency are desperately needed. Here, a lipid labeling and click chemistry-based EV capture platform ("Click Beads"), which is ideal for EV message ribonucleic acid (mRNA) assays due to its efficient, convenient, and rapid purification of EVs, enabling downstream molecular quantification using reverse transcription digital polymerase chain reaction (RT-dPCR) is described and demonstrated. Ewing sarcoma protein (EWS) gene rearrangements and kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutation status are detected and quantified using EVs isolated by Click Beads and matched with those identified in biopsy specimens from Ewing sarcoma or pancreatic cancer patients. Moreover, the quantification of gene alterations can be used for monitoring treatment responses and disease progression.

Circulating Tumor Cell-Based Messenger RNA Scoring System for Prognostication of Hepatocellular Carcinoma: Translating Tissue-Based Messenger RNA Profiling Into a Noninvasive Setting

Numerous studies in hepatocellular carcinoma (HCC) have proposed tissue-based gene signatures for individualized prognostic assessments. Here, we develop a novel circulating tumor cell (CTC)-based transcriptomic profiling assay to translate tissue-based messenger RNA (mRNA) signatures into a liquid biopsy setting for noninvasive HCC prognostication. The HCC-CTC mRNA scoring system combines the NanoVelcro CTC Assay for enriching HCC CTCs and the NanoString nCounter platform for quantifying the HCC-CTC Risk Score (RS) panel in enriched HCC CTCs. The prognostic role of the HCC-CTC RS was assessed in The Cancer Genome Atlas (TCGA) HCC cohort (n = 362) and validated in an independent clinical CTC cohort (n = 40). The HCC-CTC RS panel was developed through our integrated data analysis framework of 8 HCC tissue-based gene signatures and identified the top 10 prognostic genes (discoidin domain receptor tyrosine kinase 1 [DDR1], enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase [EHHADH], androgen receptor [AR], lumican [LUM], hydroxysteroid 17-beta dehydrogenase 6[HSD17B6], prostate transmembrane protein, androgen induced 1 [PMEPA1], tsukushi, small leucine rich proteoglycan [TSKU], N-terminal EF-hand calcium binding protein 2 [NECAB2], ladinin 1 [LAD1], solute carrier family 27 member 5 [SLC27A5]) highly expressed in HCC with low expressions in white blood cells. The panel accurately discriminated overall survival in TCGA HCC cohort (hazard ratio [HR], 2.0; 95% confidence interval [CI], 1.4-2.9). The combined use of the scoring system and HCC-CTC RS panel successfully distinguished artificial blood samples spiked with an aggressive HCC cell type, SNU-387, from those spiked with PLC/PRF/5 cells (P = 0.02). In the CTC validation cohort (n = 40), HCC-CTC RS remained an independent predictor of survival (HR, 5.7; 95% CI, 1.5-21.3; P = 0.009) after controlling for Model for End-Stage Liver Disease score, Barcelona Clinic Liver Cancer stage, and CTC enumeration count. Our study demonstrates a novel interdisciplinary approach to translate tissue-based gene signatures into a liquid biopsy setting. This noninvasive approach will allow real-time disease profiling and dynamic prognostication of HCC.

Optimal Timing of Administration of Direct-acting Antivirals for Patients With Hepatitis C-associated Hepatocellular Carcinoma Undergoing Liver Transplantation

OBJECTIVE

To investigate the optimal timing of direct acting antiviral (DAA) administration in patients with hepatitis C-associated hepatocellular carcinoma (HCC) undergoing liver transplantation (LT).

SUMMARY OF BACKGROUND DATA

In patients with hepatitis C (HCV) associated HCC undergoing LT, the optimal timing of direct-acting antivirals (DAA) administration to achieve sustained virologic response (SVR) and improved oncologic outcomes remains a topic of much debate.

METHODS

The United States HCC LT Consortium (2015-2019) was reviewed for patients with primary HCV-associated HCC who underwent LT and received DAA therapy at 20 institutions. Primary outcomes were SVR and HCC recurrence-free survival (RFS).

RESULTS

Of 857 patients, 725 were within Milan criteria. SVR was associated with improved 5-year RFS (92% vs 77%, P < 0.01). Patients who received DAAs pre-LT, 0-3 months post-LT, and ≥3 months post-LT had SVR rates of 91%, 92%, and 82%, and 5-year RFS of 93%, 94%, and 87%, respectively. Among 427 HCV treatment-naïve patients (no previous interferon therapy), patients who achieved SVR with DAAs had improved 5-year RFS (93% vs 76%, P < 0.01). Patients who received DAAs pre-LT, 0-3 months post-LT, and ≥3 months post-LT had SVR rates of 91%, 93%, and 78% (P < 0.01) and 5-year RFS of 93%, 100%, and 83% (P = 0.01).

CONCLUSIONS

The optimal timing of DAA therapy appears to be 0 to 3 months after LT for HCV-associated HCC, given increased rates of SVR and improved RFS. Delayed administration after transplant should be avoided. A prospective randomized controlled trial is warranted to validate these results.

Abstract 764: Circulating tumor cell-based mRNA scoring system for prognostication of hepatocellular carcinoma - Translating HCC tissue-based mRNA profiling into a non-invasive setting

Background and Aims Numerous studies in hepatocellular carcinoma (HCC) have proposed tissue-based gene signatures for individualized prognostic assessments. In this study, we aim to develop the HCC circulating tumor cell (CTC) mRNA Scoring System and the HCC-CTC Risk Score (RS) panel to translate tissue-based mRNA signatures into a liquid biopsy setting for non-invasive HCC prognostication.

Methods We developed the HCC CTC mRNA Scoring System by combining the NanoVelcro CTC Assay for enriching HCC CTCs and the NanoString nCounter platform for quantifying the HCC-CTC RS panel in enriched HCC CTCs. The prognostic role of HCC-CTC RS was assessed in the Cancer Genome Atlas (TCGA) HCC cohort (n=362) and validated in an independent CTC cohort (n=40).

Results The HCC-CTC RS panel was developed from 8 HCC tissue-based prognostic gene signatures. Through our integrated data analysis framework, the top 10 prognostic genes highly expressed in HCC cells and lowly expressed in white blood cells were selected as the HCC-CTC RS panel. The panel accurately discriminated overall survival in TCGA HCC cohort (hazard ratio [HR]: 2.01, 95% confidence intervals [CI]: 1.39-2.91). In addition, the combined use of Scoring System and panel successfully distinguished artificial blood samples spiked with an aggressive HCC cell type, SNU-387, from those spiked with PLC/PRF/5 cells (P=0.02). Finally, the prognostic value of HCC-CTC RS was further validated in the CTC cohort (HR: 8.48, 95% CI: 1.89-38.03) by multivariable analysis.

Conclusions Our pilot study demonstrates a novel interdisciplinary approach to translate tissue-based gene signatures into a liquid biopsy setting. This non-invasive approach will allow real-time disease profiling and dynamical prognostication of HCC.

Citation Format: Yi-Te Lee, Na Sun, Minhyung Kim, Jasmine J. Wang, Benjamin V. Tran, Ryan Y. Zhang, Ceng Zhang, Saeed Sadeghi, Richard S. Finn, Sammy Saab, Ronald W. Busuttil, Yazhen Zhu, Hsian-Rong Tseng, Sungyong You, Ju Dong Yang, Vatche G. Agopian. Circulating tumor cell-based mRNA scoring system for prognostication of hepatocellular carcinoma - Translating HCC tissue-based mRNA profiling into a non-invasive setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 764.

The Role of Extracellular Vesicles in Disease Progression and Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and one of the leading causes of cancer-related death worldwide. Despite the improvements in surveillance and treatment, the prognosis of HCC remains poor. Extracellular vesicles (EVs) are a heterogeneous group of phospholipid bilayer-enclosed particles circulating in the bloodstream and mediating intercellular communication. Emerging studies have shown that EVs play a crucial role in regulating the proliferation, immune escape, and metastasis of HCC. In addition, because EVs are present in the circulation at relatively early stages of disease, they are getting attention as an attractive biomarker for HCC detection. Over the past decade, dedicated efforts have been made to isolate EVs more efficiently and make them useful tools in different clinical settings. In this review article, we provide an overview of the EVs isolation methods and highlight the role of EVs as mediators in the pathogenesis and progression of HCC. Lastly, we summarize the potential applications of EVs in early-stage HCC detection.

Covalent Chemistry-Mediated Multimarker Purification of Circulating Tumor Cells Enables Noninvasive Detection of Molecular Signatures of Hepatocellular Carcinoma

Transcriptomic profiling of tumor tissues introduces a large database, which has led to improvements in the ability of cancer diagnosis, treatment, and prevention. However, performing tumor transcriptomic profiling in the clinical setting is very challenging since the procurement of tumor tissues is inherently limited by invasive sampling procedures. Here, we demonstrated the feasibility of purifying hepatocellular carcinoma (HCC) circulating tumor cells (CTCs) from clinical patient samples with improved molecular integrity using Click Chips in conjunction with a multimarker antibody cocktail. The purified CTCs were then subjected to mRNA profiling by NanoString nCounter platform, targeting 64 HCC-specific genes, which were generated from an integrated data analysis framework with 8 tissue-based prognostic gene signatures from 7 publicly available HCC transcriptomic studies. After bioinformatics analysis and comparison, the HCC CTC-derived gene signatures showed high concordance with HCC tissue-derived gene signatures from TCGA database, suggesting that HCC CTCs purified by Click Chips could enable the translation of HCC tissue molecular profiling into a noninvasive setting.

Persistence of racial disparities in early-stage lung cancer treatment

OBJECTIVE

Although the incidence of lung cancer has decreased over the past decades, disparities in survival and treatment modalities have been observed for black and white patients with early-stage non-small cell lung cancer, despite the fact that surgical resection has been established as the standard of care. Possible contributors to these disparities are stage at diagnosis, comorbidities, socioeconomic factors, and patient preference. This study examines racial disparities in treatment, adjusting for clinicodemographic factors.

METHODS

The Surveillance, Epidemiology, and End Results-Medicare dataset was queried to identify patients diagnosed with primary stage I non-small cell lung cancer between 1992 and 2009. Multivariable logistic regressions were performed to assess the association between race and treatment modalities within 1 year of diagnosis, adjusted for clinical and demographic factors. Adjusted Cox proportional hazards models were performed to evaluate disparities in survival, accounting for mode of treatment.

RESULTS

We identified 22,724 patients; 21,230 (93.4%) white and 1494 (6.6%) black. Black patients were less likely to receive treatment (odds ratio [OR]_adj, 0.62; 95% confidence interval [CI], 0.53-0.73) and less likely to receive surgery only when treated (OR_adj, 0.70, 95% CI, 0.61-0.79). Although univariate survival for black patients was worse, when accounting for treatment mode, there was no difference in survival (hazard ratio_adj, 0.97; 95% CI, 0.90-1.04 for all patients, hazard ratio_adj, 0.98; 95% CI: 0.90-1.06 for treated patients).

CONCLUSIONS

Treatment disparities persist, even when adjusting for clinical and demographic factors. However, when black patients receive similar treatment, survival is comparable with white patients.

Oxygen Use After Lung Cancer Surgery

BACKGROUND

There are no published reports on predictors of oxygen (O₂) use after lung cancer surgery. The prospect of O₂ use after lung cancer surgery may affect a patient's therapy choice.

METHODS

The Surveillance, Epidemiology, and End Results (SEER)-Medicare data set was queried to identify patients diagnosed with primary lung cancer (stage I/II) who underwent surgical resection from 1994 to 2010. Patients with a second resection within 6 months of their first and those with preoperative O₂ use were excluded. Multivariable logistic regression was performed to evaluate the odds ratios and 95% confidence intervals of O₂ use (defined as being billed for home O₂) after discharge for lung cancer surgery.

RESULTS

Of 21,245 eligible patients from 1994 to 2010, 3,255 (15.3%) were billed for O₂ use in the first month of discharge. Of these, 13.7% (447 of 3,255) stopped using within 1 month, and 1.47% died. By 6 months, an additional 6.7% died, and 46.27% (1,384 of 2,991) were still alive and using O_2. Discharge on O₂ was associated with higher odds of death within 6 months (odds ratio, 1.35; 95% confidence interval, 1.17 to 1.55). The significant, independent risk factors for O₂ use at discharge were procedure, sex, race, histology, pulmonary comorbidities, obesity, length of stay, pulmonary complications, and discharge mode.

CONCLUSIONS

Home O₂ use after lung cancer surgery comprises a sizable portion of this population and is correlated with death in the first 6 months. Various predictors significantly increased the risk of O₂ use at discharge. However, 49.3% of those originally discharged on O₂ were alive and off O₂ at 6 months.

Altered ratios of alternatively spliced long and short gamma2 subunit mRNAs of the gamma-amino butyrate type A receptor in prefrontal cortex of schizophrenics

The relative abundance of alternatively spliced long (gamma2L) and short (gamma2S) mRNAs of the gamma2 subunit of the gamma-amino butyrate type A (GABAA) receptor was examined in dorsolateral prefrontal cortex of schizophrenics and matched controls by using in situ hybridization histochemistry and semiquantitative reverse transcription-PCR (RT-PCR) amplification. A cRNA probe identifying both mRNAs showed that the transcripts are normally expressed at moderately high levels in the prefrontal cortex. Consistent with previous studies, overall levels of gamma2 transcripts in prefrontal cortex of brains from schizophrenics were reduced by 28.0%, although this reduction did not reach statistical significance. RT-PCR, performed under nonsaturating conditions on total RNA from the same blocks of tissue used for in situ hybridization histochemistry, revealed a marked reduction in the relative proportion of gamma2S transcripts in schizophrenic brains compared with controls. In schizophrenics, gamma2S transcripts had fallen to 51.7% (+/-7.9% SE; P < 0.0001) relative to control levels. Levels of gamma2L transcripts showed only a small and nonsignificant reduction of 16. 9% (+/-12.0% SE, P > 0.05). These findings indicate differential transcriptional regulation of two functionally distinct isoforms of one of the major GABAA receptor subunits in the prefrontal cortex of schizophrenics. The specific reduction in relative abundance of gamma2S mRNAs and the associated relative increase in gamma2L mRNAs should result in functionally less active GABAA receptors and have severe consequences for cortical integrative function.

Nucleus- and cell-specific expression of NMDA and non-NMDA receptor subunits in monkey thalamus

Subcortical and corticothalamic inputs excite thalamic neurons via a diversity of glutamate receptor subtypes. Differential expression of alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA), kainate, and N-methyl-D-aspartate (NMDA) receptor subunits (GluR1-4; GluR5-7; NR1, NR2A-D) on a nucleus- and cell type-specific basis was examined by quantitative in situ hybridization histochemistry and by immunocytochemical staining for receptor subunits and colocalized gamma-aminobutyric acid (GABA) or calcium binding proteins. Levels of NMDA subunit expression, except NR2C, are higher than for the most highly expressed AMPA (GluR1,3,4) and kainate (GluR6) receptor subunits. Expression of NR2C, GluR2, GluR5, and GluR7 is extremely low. Major differences distinguish the reticular nucleus and the dorsal thalamus and, within the dorsal thalamus, the intralaminar and other nuclei. In the reticular nucleus, GluR4 is by far the most prominent, and NMDA receptors are at comparatively low levels. In the dorsal thalamus, NMDA receptors predominate. Anterior intralaminar nuclei are more enriched in GluR4 and GluR6 subunits than other nuclei, whereas posterior intralaminar nuclei are enriched in GluR1 and differ among themselves in relative NMDA receptor subunit expression. GABAergic intrinsic neurons of the dorsal thalamus express much higher levels of GluR1 and GluR6 receptor subunits than do parvalbumin- or calbindin-immunoreactive relay cells and low or absent NMDA receptors. Relay cells are dominated by NMDA receptors, along with GluR3 and GluR6 subunits not expressed by GABA cells. High levels of NR2B are found in astrocytes. Differences in NMDA and non-NMDA receptor profiles will affect functional properties of the thalamic GABAergic and relay cells.