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.

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.

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.

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 (ORadj, 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 ratioadj, 0.97; 95% CI, 0.90-1.04 for all patients, hazard ratioadj, 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.

Closed Facebook™ groups and CME credit: a new format for continuing medical education.

BACKGROUND: The International Hernia Collaboration (IHC) is a closed Facebook™ group that allows international surgeons to post clinical questions and exchange transparent feedback with the intent to optimize patient outcomes. Despite the educational value of closed FB groups, CME credits have not been available to members. To determine feasibility of and user interest in earning CME credit through social media, the IHC piloted a series of expert lectures followed by an interactive Facebook Live session as a novel pathway offering CME credit. METHODS: Nine monthly lectures and Facebook Live sessions were presented. CME credit was offered for the final seven lectures. Participation in the form of views, comments, and likes was quantified by a Facebook analytics service and an engagement score, defined as [(the number of comments × 2) + (the number of reactions)], was calculated for each lecture and Facebook Live session. CME credit was obtained through a two-question quiz. RESULTS: Of 5400 + Facebook members of the IHC, an average of 1116 (20.4 ± 4.0%) viewed the live session event following each lecture (n = 9 events). The average Facebook engagement score for Facebook Live was 259 ± 75, a significant difference with the average Facebook engagement score on the IHC (40.8) over the same time period (p < 0.001). On average, 16 users [range 8-35, (n = 7 events)] claimed CME credit for each educational series. CONCLUSIONS: Closed Facebook groups can be a useful media to offer educational content and CME credit. The pilot IHC Lecture and Facebook Live series offering CME credit resulted in significantly more engagement amongst its members compared to other posts during the same time period. A small portion of participants qualified for CME credit. Future social media educational series may increase participants qualifying for CME by streamlining the interface to obtain CME credit.

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 O2. 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.