Network approach in liquidomics landscape

Abstract Tissue-based biopsy is the present main tool to explore the molecular landscape of cancer, but it also has many limits to be frequently executed, being too invasive with the risk of side effects. These limits and the ability of cancer to constantly evolve its genomic profile, have recently led to the need of a less invasive and more accurate alternative, such as liquid biopsy. By searching Circulating Tumor Cells and residues of their nucleic acids or other tumor products in body fluids, especially in blood, but also in urine, stools and saliva, liquid biopsy is becoming the future of clinical oncology. Despite the current lack of a standardization for its workflows, that makes it hard to be reproduced, liquid biopsy has already obtained promising results for cancer screening, diagnosis, prognosis, and risk of recurrence. Through a more accessible molecular profiling of tumors, it could become easier to identify biomarkers predictive of response to treatment, such as EGFR mutations in non-small cell lung cancer and KRAS mutations in colorectal cancer, or Microsatellite Instability and Mismatch Repair as predictive markers of pembrolizumab response. By monitoring circulating tumor DNA in longitudinal repeated sampling of blood we could also predict Minimal Residual Disease and the risk of recurrence in already radically resected patients. In this review we will discuss about the current knowledge of limitations and strengths of the different forms of liquid biopsies for its inclusion in normal cancer management, with a brief nod to their newest biomarkers and its future implications

Large−scale profiling of extracellular vesicles identified miR−625−5p as a novel biomarker of immunotherapy response in advanced non−small−cell lung cancer patients

Immune checkpoint inhibitors (ICIs) are largely used in the treatment of patients with advanced non−small−cell lung cancer (NSCLC). Novel biomarkers that provide biological information that could be useful for clinical management are needed. In this respect, extracellular vesicles (EV)−associated microRNAs (miRNAs) that are the principal vehicle of intercellular communication may be important sources of biomarkers. We analyzed the levels of 799 EV−miRNAs in the pretreatment plasma of 88 advanced NSCLC patients who received anti−PD−1 therapy as single agent. After data normalization, we used a two−step approach to identify candidate biomarkers associated to both objective response (OR) by RECIST and longer overall survival (OS). Univariate and multivariate analyses including known clinicopathologic variables and new findings were performed. In our cohort, 24/88 (27.3%) patients showed OR by RECIST. Median OS in the whole cohort was 11.5 months. In total, 196 EV−miRNAs out 799 were selected as expressed above background. After multiplicity adjustment, abundance of EV−miR−625−5p was found to be correlated with PD−L1 expression and significantly associated to OR by RECIST (p = 0.0366) and OS (p = 0.0031). In multivariate analysis, PD−L1 staining and EV−miR−625−5p levels were constantly associated to OR and OS. Finally, we showed that EV−miR−625−5p levels could discriminate patients with longer survival, in particular in the class expressing PD−L1 ≥50%. EV−miRNAs represent a source of relevant biomarkers. EV−miR−625−5p is an independent biomarker of response and survival in ICI−treated NSCLC patients, in particular in patients with PD−L1 expression ≥50%

Significance of PD-L1 in Metastatic Urothelial Carcinoma Treated With Immune Checkpoint Inhibitors

Importance Immune checkpoint inhibitors (ICIs) have broadened the metastatic urothelial carcinoma (mUC) therapeutic scenario. The association of programmed death ligand 1 (PD-L1) with response and survival in patients treated with ICIs is still controversial. Objectives To evaluate the association of PD-L1 with response rate and overall survival among patients with mUC treated with ICIs. Data Sources PubMed, Embase, American Society of Clinical Oncology and European Society for Medical Oncology Meeting Libraries, and Web of Science were searched up to December 10, 2023. Study Selection Two authors independently screened the studies. Included studies were randomized and nonrandomized clinical trials enrolling patients with mUC receiving ICIs with available overall survival (OS), progression-free survival (PFS), or overall response rate (ORR) data, separated between patients with PD-L1-positive and -negative tumors. Data Extraction and Synthesis The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed. Two reviewers independently extracted data. Fixed- or random-effects models were used depending on the heterogeneity among the studies. Main Outcomes and Measures Primary outcomes were odds ratios (ORs) for ORR and hazard ratios (HRs) for OS, comparing patients with PD-L1-positive tumors and patients with PD-L1-negative tumors. Secondary outcomes were the PFS HR between patients with PD-L1-positive and -negative tumors and OS HR between ICI arms and non-ICI arms of only randomized clinical trials. Results A total of 14 studies were selected, comprising 5271 patients treated with ICIs (2625 patients had PD-L1-positive tumors). The ORR was 13.8% to 78.6% in patients with PD-L1-positive tumors and 5.1% to 63.2% in patients with PD-L1-negative tumors, with an association between PD-L1 status and ORR favoring patients with PD-L1-positive tumors (OR, 1.94; 95% CI, 1.47-2.56; P < .001). Median OS ranged from 8.4 to 24.1 months in patients with PD-L1-positive tumors and from 6.0 to 19.1 months in patients with PD-L1-negative tumors. The pooled HR showed a significant reduction for patients with PD-L1-positive tumors compared with those with PD-L1-negative tumors in the risk of death (HR, 0.71; 95% CI, 0.57-0.89; P = .003) and risk of progression (HR, 0.55; 95% CI, 0.44-0.69; P < .001) when ICIs were administered. PD-L1 is not likely to be a predictive biomarker of ICI response. Conclusions and Relevance This systematic review and meta-analysis suggests that PD-L1 expression is associated with improved ORR, OS, and PFS for patients with mUC who receive ICIs, but it is unlikely to be useful as a predictive biomarker. Developing predictive biomarkers is essential to select patients most likely to benefit from ICIs and avoid toxic effects and financial burden with these agents