Blood-based gene expression profiling in castrate-resistant prostate cancer

Rucker L, Johnson J, Ghosh S. Transcriptomics of MASLD Pathobiology in African American Patients in the Washington DC Area †

Metabolic-dysfunction-associated steatotic liver disease (MASLD) is becoming the most common chronic liver disease worldwide and is of concern among African Americans (AA) in the United States. This pilot study evaluated the differential gene expressions and identified the signature genes in the disease pathways of AA individuals with MASLD. Blood samples were obtained from MASLD patients (n = 23) and non-MASLD controls (n = 24) along with their sociodemographic and medical details. Whole-blood transcriptomic analysis was carried out using Affymetrix Clarion-S Assay. A validation study was performed utilizing TaqMan Arrays coupled with Ingenuity Pathway Analysis (IPA) to identify the major disease pathways. Out of 21,448 genes in total, 535 genes (2.5%) were significantly (p < 0.05) and differentially expressed when we compared the cases and controls. A significant overlap in the predominant differentially expressed genes and pathways identified in previous studies using hepatic tissue was observed. Of note, TGFB1 and E2F1 genes were upregulated, and HMBS was downregulated significantly. Hepatic fibrosis signaling is the top canonical pathway, and its corresponding biofunction contributes to the development of hepatocellular carcinoma. The findings address the knowledge gaps regarding how signature genes and functional pathways can be detected in blood samples ('liquid biopsy') in AA MASLD patients, demonstrating the potential of the blood samples as an alternative non-invasive source of material for future studies.

NETest: serial liquid biopsies in gastroenteropancreatic NET surveillance

Objective

Up to now, serial NETest measurements in individuals assessing the disease course of gastroenteropancreatic neuroendocrine tumors (GEPNETs) at long-term follow-up and treatment response were not studied.

Design

The study was a longitudinal validation study of serial NETest measurements - a blood-based gene expression signature - in 132 patients with GEPNETs on therapy or watch-and-wait strategy.

Methods

Serial samples were collected during 46 (range: 6-71) months of follow-up. NETest scores were compared with Response Evaluation Criteria in Solid Tumors version 1.1-defined treatment response (e.g. no evidence of disease (NED), stable disease (SD) or progressive disease (PD)).

Results

Consecutive NETest scores fluctuated substantially (range: 0-100) over time in individuals with SD (n = 28) and NED (n = 30). Follow-up samples were significantly higher in SD (samples 3-5) and NED subgroups (samples 2-5) compared with baseline results, without changes in imaging. In 82% of untreated patients with PD, consecutive NETest scores consistently remained high. In patients undergoing systemic treatment, the median pre-treatment NETest score in treatment-responders was 76.5 (n = 22) vs 33 (n = 12) in non-responders (P = 0.001). Patients with low pre-treatment scores had 21 months reduced progression-free survival (10 vs 31 months; P = 0.01). The accuracy of the NETest for treatment response prediction was 0.73 (P = 0.009).

Conclusion

In patients not undergoing treatment, consecutive low NETest scores are associated with indolent behavior. Patients who develop PD exhibit elevated scores. Elevated results have important predictive value for treatment responsiveness and could be used for individualizing decisions on systemic therapy. The clinical value of follow-up NETest scores for patients who choose to watch and wait requires further study.

A blood-based 22-gene expression signature for hepatocellular carcinoma identification

Background

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Early detection of HCC could largely reduce mortalities. Ultrasonography (US) and serum Alpha Fetoprotein (AFP) test are the screening methods that are most frequently applied to high-risk populations. Due to the poor performance of AFP testing, and the highly operator-dependent nature of US, a biomarker for HCC early diagnosis is highly sought after. We developed a method for HCC screening using a 22-gene expression signature.

Methods

Peripheral whole blood of 98 patients were processed through microarrays for the first round of feature selection via two strategies, Minimal Redundancy Maximal Relevance and Least Absolute Shrinkage and Selection Operator combined with Support Vector Machine (SVM). Candidate genes were combined for further validation through qPCR in an enlarged population with 316 samples with 104 chronic hepatitis, 112 liver cirrhosis (LC), and 100 HCC.

Results

A 22-gene signature was established in classifying HCC and non-cancer samples with good performance. The area under curve reached 0.94 in all of the samples and 0.93 in the AFP -negative samples.

Conclusions

We have established a blood mRNA signature with high performance for HCC screening. Our results show transcriptome of peripheral blood could be valuable source for biomarkers.