Toward Blood-Based Precision Medicine: Identifying Age-Sex-Specific Vascular Biomarker Quantities on Circulating Vascular Cells.

Introduction: Abnormal angiogenesis is central to vascular disease and cancer, and noninvasive biomarkers of vascular origin are needed to evaluate patients and therapies. Vascular endothelial growth factor receptors (VEGFRs) are often dysregulated in these diseases, making them promising biomarkers, but the need for an invasive biopsy has limited biomarker research on VEGFRs. Here, we pioneer a blood biopsy approach to quantify VEGFR plasma membrane localization on two circulating vascular proxies: circulating endothelial cells (cECs) and circulating progenitor cells (cPCs). Methods: Using quantitative flow cytometry, we examined VEGFR expression on cECs and cPCs in four age-sex groups: peri/premenopausal females (aged < 50 years), menopausal/postmenopausal females (≥ 50 years), and younger and older males with the same age cut-off (50 years). Results: cECs in peri/premenopausal females consisted of two VEGFR populations: VEGFR-low (~ 55% of population: population medians ~ 3000 VEGFR1 and 3000 VEGFR2/cell) and VEGFR-high (~ 45%: 138,000 VEGFR1 and 39,000-236,000 VEGFR2/cell), while the menopausal/postmenopausal group only possessed the VEGFR-low cEC population; and 27% of cECs in males exhibited high plasma membrane VEGFR expression (206,000 VEGFR1 and 155,000 VEGFR2/cell). The absence of VEGFR-high cEC subpopulations in menopausal/postmenopausal females suggests that their high-VEGFR cECs are associated with menstruation and could be noninvasive proxies for studying the intersection of age-sex in angiogenesis. VEGFR1 plasma membrane localization in cPCs was detected only in menopausal/postmenopausal females, suggesting a menopause-specific regenerative mechanism. Conclusions: Overall, our quantitative, noninvasive approach targeting cECs and cPCs has provided the first insights into how sex and age influence VEGFR plasma membrane localization in vascular cells. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-023-00771-1.

Comprehensive Profiling of Cancer-Associated Cells in the Blood of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy to Predict Pathological Complete Response.

Neoadjuvant chemotherapy (NAC) can affect pathological complete response (pCR) in breast cancers; the resection that follows identifies patients with residual disease who are then offered second-line therapies. Circulating tumor cells (CTCs) and cancer-associated macrophage-like cells (CAMLs) in the blood can be used as potential biomarkers for predicting pCR before resection. CTCs are of epithelial origin that undergo epithelial-to-mesenchymal transition to become more motile and invasive, thereby leading to invasive mesenchymal cells that seed in distant organs, causing metastasis. Additionally, CAMLs in the blood of cancer patients are reported to either engulf or aid the transport of cancer cells to distant organs. To study these rare cancer-associated cells, we conducted a preliminary study where we collected blood from patients treated with NAC after obtaining their written and informed consent. Blood was collected before, during, and after NAC, and Labyrinth microfluidic technology was used to isolate CTCs and CAMLs. Demographic, tumor marker, and treatment response data were collected. Non-parametric tests were used to compare pCR and non-pCR groups. Univariate and multivariate models were used where CTCs and CAMLs were analyzed for predicting pCR. Sixty-three samples from 21 patients were analyzed. The median(IQR) pre-NAC total and mesenchymal CTC count/5 mL was lower in the pCR vs. non-pCR group [1(3.5) vs. 5(5.75); p = 0.096], [0 vs. 2.5(7.5); p = 0.084], respectively. The median(IQR) post-NAC CAML count/5 mL was higher in the pCR vs. non-pCR group [15(6) vs. 6(4.5); p = 0.004]. The pCR group was more likely to have >10 CAMLs post-NAC vs. non-pCR group [7(100%) vs. 3(21.4%); p = 0.001]. In a multivariate logistic regression model predicting pCR, CAML count was positively associated with the log-odds of pCR [OR = 1.49(1.01, 2.18); p = 0.041], while CTCs showed a negative trend [Odds Ratio (OR) = 0.44(0.18, 1.06); p = 0.068]. In conclusion, increased CAMLs in circulation after treatment combined with lowered CTCs was associated with pCR.

bITH, a blood-based metric of intratumor heterogeneity, is associated with clinical response to immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Intratumor heterogeneity (ITH) has been associated with poor prognosis in advanced non-small cell cancer (NSCLC) patients receiving immune checkpoint blockade (ICB) therapies. However, there is currently no evidence supporting an ITH metric as a predictor of clinical benefit from ICB. The unique advantages of blood make it a promising material for ITH estimation and relevant applications. This study aims to develop and validate a blood-based ITH index for predicting ICB response. METHODS: NSCLC patients from the OAK and POPLAR clinical trials were used as the training cohorts for algorithm development. Survival analyses with overall survival (OS) and progression-free survival (PFS) as endpoints were performed to assess clinical response. The predictive value of bITH was subsequently validated with an independent cohort of 42 NSCLC patients treated with PD-1 blockade. FINDINGS: bITH was significantly associated with the differential OS and PFS elicited by atezolizumab vs. docetaxel in both univariable and multivariable analyses in the OAK patients, suggesting bITH as an independent predictor for response to ICB. Moreover, compared with blood tumor mutation burden (bTMB), bITH enabled greater OS segregation and comparable PFS segregation, and obtained a predictive role regardless of bTMB status. Moreover, the association between bITH and PFS was validated with an independent cohort. INTERPRETATION: Patients with low blood-based ITH metric manifest significant OS and PFS benefit from immunotherapy versus chemotherapy. Future research is awaited to corroborate our findings and to enrich the clinical utility of ITH. FUNDING: This study was supported by the National Natural Science Foundation of China (Nos. 81972718 and 81572321), the Natural Scientific Foundation of Zhejiang Province, China (No. LY19H160007), the Science and Technology Program for Health and Medicine in Zhejiang Province, China (No. 2021KY541), the Scientific Research Project, Science and Technology Department of Sichuan Province (No. 21YYJC1616), the Scientific Research Project, Sichuan Medical Association (No. S20002), Wu Jieping Medical Foundation (No. 320.6750), and 2018 Entrepreneurial Leading Talent of Guangzhou Huangpu District and Guangzhou Development District (No. 2022-L023).

Identification of DNA methylation and genetic alteration simultaneously from a single blood biopsy.

BACKGROUND: High-throughput sequencing of blood cell-free DNA (cfDNA) techniques offer an opportunity to characterize and monitor cancer rapidly in a non-invasive and real-time manner. Nonetheless, there lacks a tool within therapeutic arsenal to identify multi-omics alterations simultaneously from a single biopsy. In current times, bisulfite-based sequencing detects 5mC and 5hmC at single-base resolution is the golden standard of DNA methylation, while the degradation of DNA and biased sequencing data are the problems of this method. OBJECTIVE: To identify the consistency analysis of methylation and genetic variation with single library, we presented a platform detecting multi-omics data simultaneously from a single blood biopsy using bisulfite-free method of genomic methylation sequencing (GM-seq) mediated by TET enzyme. METHODS: We detected methylomic and genetic changes simultaneously from a single blood biopsy in NA12878 and randomly chose ten blood biopsies from colorectal cancer or lung cancer patients to validate the ability of GM-seq. RESULTS: Similar cytosine methylation level between whole genome bisulfite sequencing (WGBS) and GM-seq were identified in NA12878. Moreover, longer insert size, CpGs coverage and GC distribution were outperformed than WGBS. In addition, the comparison of the single nucleotide polymorphism (SNP), insertion-deletion (Indel) and copy number variation (CNV) in NA12878 or ctDNA from liver cancer between GM-seq and whole genome sequencing (WGS) show a good consistency, indicating that this method is feasible for detecting genetic variation in blood. CONCLUSION: In conclusion, our work demonstrated a method for identification of the methylated modification and genetic variations simultaneously from a single blood biopsy.

Increased blood-based intratumor heterogeneity (bITH) is associated with unfavorable outcomes of immune checkpoint inhibitors plus chemotherapy in non-small cell lung cancer.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) and chemotherapy has been the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) patients with driver-gene negative. However, efficacy biomarkers for ICIs-based combination therapy are lacking. We aimed to identify potential factors associated with outcomes of ICIs plus chemotherapy at baseline and dynamic changes in peripheral blood. METHODS: We collected plasma samples of 51 advanced NSCLC patients without EGFR/ALK/ROS1 alteration at baseline and/or after two treatment cycles of ICIs plus chemotherapy. A blood-based intratumor heterogeneity (bITH) score was calculated based on the allele frequencies of somatic mutations using a 520-gene panel. bITH-up was defined as a ≥ 10% increase in bITH score from baseline, with a second confirmatory measurement after treatment. RESULTS: At baseline, the number of metastatic organs and lung immune prognostic index (LIPI) were significantly associated with shorter progression-free survival (PFS) of ICIs plus chemotherapy, while bITH and other common molecular biomarkers, including ctDNA level, blood-based tumor mutational burden (bTMB), and PD-L1 expression, had no effect on PFS. LRP1B mutation at baseline was significantly associated with favorable outcomes to ICIs plus chemotherapy. There were 37 patients who had paired samples at baseline and after two cycles of treatment, with the median interval of 53 days. Intriguingly, patients with bITH-up had significant shorter PFS (HR, 4.92; 95% CI, 1.72-14.07; P = 0.001) and a lower durable clinical benefit rate (0 vs 41.38%, P = 0.036) than those with bITH-stable or down. Case studies indicated that bITH was promising to predict disease progression. CONCLUSIONS: The present study is the first to report that increased bITH is associated with unfavorable outcomes of ICIs plus chemotherapy in advanced NSCLC patients.

Classification algorithms applied to blood-based transcriptome meta-analysis to predict idiopathic Parkinson's disease.

Diagnosis of Parkinson's disease (PD) remains a challenge in clinical practice, mostly due to lack of peripheral blood markers. Transcriptomic analysis of blood samples has emerged as a potential means to identify biomarkers and gene signatures of PD. In this context, classification algorithms can assist in detecting data patterns such as phenotypes and transcriptional signatures with potential diagnostic application. In this study, we performed gene expression meta-analysis of blood transcriptome from PD and control patients in order to identify a gene-set capable of predicting PD using classification algorithms. We examined microarray data from public repositories and, after systematic review, 4 independent cohorts (GSE6613, GSE57475, GSE72267 and GSE99039) comprising 711 samples (388 idiopathic PD and 323 healthy individuals) were selected. Initially, analysis of differentially expressed genes resulted in minimal overlap among datasets. To circumvent this, we carried out meta-analysis of 17,712 genes across datasets, and calculated weighted mean Hedges' g effect sizes. From the top-100- positive and negative gene effect sizes, algorithms of collinearity recognition and recursive feature elimination were used to generate a 59-gene signature of idiopathic PD. This signature was evaluated by 9 classification algorithms and 4 sample size-adjusted training groups to create 36 models. Of these, 33 showed accuracy higher than the non-information rate, and 2 models built on Support Vector Machine Regression bestowed best accuracy to predict PD and healthy control samples. In summary, the gene meta-analysis followed by machine learning methodology employed herein identified a gene-set capable of accurately predicting idiopathic PD in blood samples.

Association of mutant EGFR L858R and exon 19 concentration in circulating cell-free DNA using droplet digital PCR with response to EGFR-TKIs in NSCLC.

The present study aimed to determine the diagnostic concordance of plasma epidermal growth factor receptor (EGFR) mutation using droplet digital polymerase chain reaction (ddPCR) with tumor tissue samples and the predictive clinical significance of plasma EGFR mutation concentration. Plasma DNA samples from patients with non-small cell lung cancer (NSCLC) were analyzed for EGFR exon 21 codon 858 (L858R) mutation, deletion of exon 19 (ex19del) and exon 20 codon 790 (T790M) mutation using ddPCR. Firstly, the mutations in the plasma samples were compared with the matched tumor samples to determine the concordance. Secondly, image examination follow-ups were analyzed to assess the association between plasma EGFR mutation concentration and patients' response to EGFR-tyrosine kinase inhibitors (TKIs). A total of 51 patients with NSCLC were enrolled, including 48 newly diagnosed patients. Compared with tumor tissue samples, the sensitivity and specificity of ddPCR were 76.19% (16/21) and 96.55% (28/29) for mutant L858R, and 88.89% (8/9) and 100% (41/41) for ex19del, respectively. No patient exhibited the T790M mutation in the tumor tissue or plasma samples. Furthermore, 5 patients with the L858R mutation and 4 patients with ex19del in plasma and tumor tissue samples had been followed up with image examination for ≥3 months following EGFR-TKI treatment. The baseline mutant EGFR concentrations were positively correlated with a reduction in tumor burden (Spearman's r=0.7000, P=0.0358). When analyzed separately, ex19del concentrations (Spearman's r=1.0000, P<0.0001) were also positively correlated with the reduction, while mutant L858R concentrations were not (Spearman's r=0.7000, P=0.1881). In the present study, detection of plasma EGFR mutations using ddPCR exhibited sufficient concordance with tumor tissue sample results. Baseline plasma mutant EGFR and ex19del concentrations were significantly and positively correlated with response to EGFR-TKIs.

Estimation of cell-free circulating EGFR mutation concentration predicts outcomes in NSCLC patients treated with EGFR-TKIs.

Detection of circulating tumor DNA using droplet digital polymerase chain reaction (ddPCR) is a highly-sensitive, minimally invasive alternative to serial biopsies for assessment and management of cancer. We used ddPCR to assess the utility of measuring plasma concentrations of common epidermal growth factor receptor (EGFR) mutations (L858R, exon 19 deletion, and T790M) in 57 non-small cell lung cancer (NSCLC) patients treated with EGFR tyrosine kinase inhibitors (EGFR-TKIs). High baseline plasma EGFR mutation (pEGFRmut) concentrations were associated with shorter progression-free survival (8.43 months) than low baseline pEGFRmut (16.23 months; p = 0.0019). By contrast, there were no differences in tumor shrinkage or overall survival between groups. During EGFR-TKI treatment, pEGFRmut levels decreased to zero in 89.58% of patients. Twenty-five of the 27 patients who progressed had basal pEGFRmut, and 18 also had circulating T790M. All 20 patients with dramatic progression (according to a categorization system for EGFR-TKIs failure) had basal pEGFRmut, and 13 had T790M mutation at progression. These results support the use of ddPCR for analysis of plasma EGFR mutations for prediction of PFS and to monitor clinical responses to EGFR-TKIs in NSCLC patients.

An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma.

Circulating tumor cells (CTCs) are shed into the bloodstream by invasive cancers, but the difficulty inherent in identifying these rare cells by microscopy has precluded their routine use in monitoring or screening for cancer. We recently described a high-throughput microfluidic CTC-iChip, which efficiently depletes hematopoietic cells from blood specimens and enriches for CTCs with well-preserved RNA. Application of RNA-based digital PCR to detect CTC-derived signatures may thus enable highly accurate tissue lineage-based cancer detection in blood specimens. As proof of principle, we examined hepatocellular carcinoma (HCC), a cancer that is derived from liver cells bearing a unique gene expression profile. After identifying a digital signature of 10 liver-specific transcripts, we used a cross-validated logistic regression model to identify the presence of HCC-derived CTCs in nine of 16 (56%) untreated patients with HCC versus one of 31 (3%) patients with nonmalignant liver disease at risk for developing HCC (P < 0.0001). Positive CTC scores declined in treated patients: Nine of 32 (28%) patients receiving therapy and only one of 15 (7%) patients who had undergone curative-intent ablation, surgery, or liver transplantation were positive. RNA-based digital CTC scoring was not correlated with the standard HCC serum protein marker alpha fetoprotein (P = 0.57). Modeling the sequential use of these two orthogonal markers for liver cancer screening in patients with high-risk cirrhosis generates positive and negative predictive values of 80% and 86%, respectively. Thus, digital RNA quantitation constitutes a sensitive and specific CTC readout, enabling high-throughput clinical applications, such as noninvasive screening for HCC in populations where viral hepatitis and cirrhosis are prevalent.

Circulating tumor cells in localized prostate cancer: isolation, cultivation in vitro and relationship to T-stage and Gleason score.

The most promising near-term application of circulating tumor cells (CTCs) monitoring relates to the development of targeted cancer therapies, and the need to tailor such treatments to individual tumor characteristics. A high number of new innovative technologies to improve methods for detecting CTCs, with extraordinarily high sensitivity, have recently been presented. The identification and characterization of CTCs require extremely sensitive and specific methods that are able to isolate CTCs with the possibility of cultivation and downstream analysis of in vitro culture of separated CTCs. In this original research paper, we demonstrate that it is possible to isolate human CTCs from a patient with prostate cancer, with subsequent cultivation and proliferation in vitro. We show that the use of a filtration device implemented by MetaCell® can fulfil all the requirements mentioned above. Fifty-five patients with localized prostate cancer have so far been enrolled into the study. CTCs were detected in the blood samples of 28 (52%) out of the 55 patients. We report successful isolation of CTCs from patients with prostate cancer, capturing cells with a proliferative capacity in 18 (64.3%) out of the 28 CTC-positive patients. Direct correlation with Gleason score and T stage was not proven. The cells, captured by a size-based filtration approach, remain in a good state, unaffected by any antibodies or lysing solutions. During the filtration process, no interactions occurred between antibodies and antigens on the surface of CTCs. This biological interaction is specific for immunomagnetic methods. The MetaCell device provides the possibility of reaching virgin CTCs suitable for subsequent cultivation or single-cell analysis. This aspect will have an important impact on the future design of clinical trials testing new drugs against targets expressed on metastatic cancer cells. In addition to measurement of CTC counts, future trials with targeted therapies should also include the assessment of the specific therapeutic target on CTCs.