Using cfRNA as a tool to evaluate clinical treatment outcomes in patients with metastatic lung cancers and other tumors.

Aim: We report an exploratory analysis of cfRNA as a biomarker to monitor clinical responses in non-small cell lung cancer (NSCLC), breast cancer, and colorectal cancer (CRC). An analysis of cfRNA as a method for measuring PD-L1 expression with comparison to clinical responses was also performed in the NSCLC cohort. Methods: Blood samples were collected from 127 patients with metastatic disease that were undergoing therapy, 52 with NSCLC, 50 with breast cancer, and 25 with CRC. cfRNA was purified from fractionated plasma, and following reverse transcription (RT), total cfRNA and gene expression of PD-L1were analyzed by real-time polymerase chain reaction (qPCR) using beta-actin expression as a surrogate for relative amounts of cfDNA and cfRNA. For the concordance study of liquid biopsies and tissue biopsies, the isolated RNA was analyzed by RNAseq for the expressions of 13 genes. We had to close the study early due to a lack of follow-up during the Covid-19 pandemic. Results: We collected a total of 373 blood samples. Mean cfRNA PCR signals after RT were about 50-fold higher than those of cfDNA. cfRNA was detected in all patients, while cfDNA was detected in 88% of them. A high concordance was found for the expression levels of 13 genes between blood and solid tumor tissue. Changes in cfRNA levels followed over the course of treatments were associated with response to therapy, increasing in progressive disease (PD) and falling when a partial response (PR) occurred. The expression of PD-L1 over time in patients treated with immunotherapy decreased with PR but increased with PD. Pre-treatment levels of PD-L1 were predictive of response in patients treated with immunotherapy. Conclusion: Changes in cfRNA correlate with clinical response to the therapy. Total cfRNA may be useful in predicting clinical outcomes. PD-L1 gene expression may provide a biomarker to predict response to PD-L1 inhibition.

Multiparametric liquid biopsy analysis in metastatic prostate cancer.

Molecular profiling of prostate cancer with liquid biopsies, such as circulating tumor cells (CTCs) and cell-free nucleic acid analysis, yields informative yet distinct data sets. Additional insights may be gained by simultaneously interrogating multiple liquid biopsy components to construct a more comprehensive molecular disease profile. We conducted an initial proof-of-principle study aimed at piloting this multiparametric approach. Peripheral blood samples from men with metastatic castrate-resistant prostate cancer were analyzed simultaneously for CTC enumeration, single-cell copy number variations, CTC DNA and matched cell-free DNA mutations, and plasma cell-free RNA levels of androgen receptor (AR) and AR splice variant (ARV7). In addition, liquid biopsies were compared with matched tumor profiles when available, and a second liquid biopsy was drawn and analyzed at disease progression in a subset of patients. In this manner, multiparametric liquid biopsy profiles were successfully generated for each patient and time point, demonstrating the feasibility of this approach and highlighting shared as well as unique cancer-relevant alterations. With further refinement and validation in large cohorts, multiparametric liquid biopsies can optimally integrate disparate but clinically informative data sets and maximize their utility for molecularly directed, real-time patient management.

Frequencies and expression levels of programmed death ligand 1 (PD-L1) in circulating tumor RNA (ctRNA) in various cancer types.

BACKGROUND: Precision medicine and prediction of therapeutic response requires monitoring potential biomarkers before and after treatment. Liquid biopsies provide noninvasive prognostic markers such as circulating tumor DNA and RNA. Circulating tumor RNA (ctRNA) in blood is also used to identify mutations in genes of interest, but additionally, provides information about relative expression levels of important genes. In this study, we analyzed PD-L1 expression in ctRNA isolated from various cancer types. Tumors inhibit antitumor response by modulating the immune checkpoint proteins programmed death ligand 1 (PD-L1) and its cognate receptor PD1. The expression of these genes has been implicated in evasion of immune response and resistance to targeted therapies. METHODS: Blood samples were collected from gastric (GC), colorectal (CRC), lung (NSCLC), breast (BC), prostate cancer (PC) patients, and a healthy control group. ctRNA was purified from fractionated plasma, and following reverse transcription, levels of PD-L1 expression were analyzed using qPCR. RESULTS: PD-L1 expression was detected in the plasma ctRNA of all cancer types at varying frequencies but no PD-L1 mRNA was detected in cancer-free individuals. The frequencies of PD-L1 expression were significantly different among the various cancer types but the median relative PD-L1 expression values were not significantly different. In 12 cases where plasma and tumor tissue were available from the same patients, there was a high degree of concordance between expression of PD-L1 protein in tumor tissues and PD-L1 gene expression in plasma, and both methods were equally predictive of response to nivolumab. CONCLUSIONS: PD-L1 mRNA can be detected and quantitated in ctRNA of cancer patients. These results pave the way for further studies aimed at determining whether monitoring the levels of PD-L1 mRNA in blood can identify patients who are most likely to benefit from the conventional treatment.

Insulin-Leptin Axis, Cardiometabolic Risk and Oxidative Stress in Elderly with Metabolic Syndrome.

Insulin and leptin have an overlapping anorexigenic action as well as opposite effects on glucose and lipid metabolism. The study focuses on the biochemical and clinical relevance of new indices of insulin-leptin axis utilized in the study of the relationships between leptinemia, insulin sensitivity and oxidative stress, in elderly subjects with metabolic syndrome. We conducted clinical studies on elderly people with metabolic syndrome versus control subjects by creating new insulin-adipogenic indices, namely Insulin-to-Leptin Ratio (ILR) and Insulin-Adipogenic Resistance index (IAR-index). Inflammation and oxidative stress biomarkers evaluated were the high-sensitivity C-reactive protein (hsCRP), the advanced oxidation protein products (AOPP), and the serum antioxidant capacity measured as ferric reducing antioxidant potential (FRAP). The metabolic syndrome group showed significantly (p<0.01) lower levels of ILR and not significant (p=0.09) higher values of IAR-index, as compared to the control group. In metabolic syndrome subjects, the IAR-index was significantly positively correlated with uric acid (r=0.313, p<0.05), FRAP (r=0.347, p<0.05) and AOPP (r=0.677, p<0.01), and negatively correlated with HDL-cholesterol (r=- 0.340, p<0.05) as well as with the ratio FRAP/uric acid (r=- 0.315, p<0.05). ILR and IAR-index reflected the biological state of adipose and pancreatic ß-cells and seem to depict the adipo-insular axis status related to metabolic and oxidative stress better than individual markers. Therefore, ILR and IAR-index could represent integrated high-potential biomarkers for disease and patient stratification.