Exploring the Synergistic Potential of Radiomics and Laboratory Biomarkers for Enhanced Identification of Vulnerable COVID-19 Patients

BACKGROUND

Severe courses and high hospitalization rates were ubiquitous during the first pandemic SARS-CoV-2 waves. Thus, we aimed to examine whether integrative diagnostics may aid in identifying vulnerable patients using crucial data and materials obtained from COVID-19 patients hospitalized between 2020 and 2021 (n = 52). Accordingly, we investigated the potential of laboratory biomarkers, specifically the dynamic cell decay marker cell-free DNA and radiomics features extracted from chest CT.

METHODS

Separate forward and backward feature selection was conducted for linear regression with the Intensive-Care-Unit (ICU) period as the initial target. Three-fold cross-validation was performed, and collinear parameters were reduced. The model was adapted to a logistic regression approach and verified in a validation naïve subset to avoid overfitting.

RESULTS

The adapted integrated model classifying patients into "ICU/no ICU demand" comprises six radiomics and seven laboratory biomarkers. The models' accuracy was 0.54 for radiomics, 0.47 for cfDNA, 0.74 for routine laboratory, and 0.87 for the combined model with an AUC of 0.91.

CONCLUSION

The combined model performed superior to the individual models. Thus, integrating radiomics and laboratory data shows synergistic potential to aid clinic decision-making in COVID-19 patients. Under the need for evaluation in larger cohorts, including patients with other SARS-CoV-2 variants, the identified parameters might contribute to the triage of COVID-19 patients.

Therapeutic Nanocarriers Inhibit Chemotherapy-Induced Breast Cancer Metastasis

Chemotherapy, although effective against primary tumors, may promote metastasis by causing the release of proinflammatory factors from damaged cells. Here, polymeric nanoparticles that deliver chemotherapeutics and scavenge proinflammatory factors simultaneously to inhibit chemotherapy-induced breast cancer metastasis are developed. The cationic nanoparticles can adsorb cell-free nucleic acids (cfNAs) based on charge-charge interaction, which downregulates the expression of Toll-like receptors and then reduces the secretion of inflammatory cytokines. Through in vitro structural optimization, cationic polyamidoamine (PAMAM) dendrimers modified with drug-binding dodecyl groups and diethylethanolamine surface groups (PAMAM-G3-C12₅ -DEEA₂₀ ) exhibit the most desirable combination of nanoparticle size (≈140 nm), drug loading, cytotoxicity, cfNA binding, and anti-inflammatory activity. In the mouse models of breast cancer metastasis, paclitaxel-loaded nanoparticles reduce serum levels of cfNAs and inflammatory cytokines compared with paclitaxel treatment alone and inhibit both primary tumor growth and tumor metastasis. Additionally, no significant side effects are detected in the serum or major organs. These results provide a strategy to deliver chemotherapeutics to primary tumors while reducing the prometastatic effects of chemotherapy.

Cell-Free Total Nucleic Acid-Based Genotyping of Aggressive Lymphoma: Comprehensive Analysis of Gene Fusions and Nucleotide Variants by Next-Generation Sequencing

Simple Summary

This study aimed to simultaneously demonstrate pathogenic chromosomal translocations and point mutations from both tissue biopsy and peripheral blood (PB) liquid biopsy (LB) samples of aggressive lymphoma patients. Matched samples were analyzed by next-generation sequencing for the same 125 genes. Eight different gene fusions, including the classical BCL2, BCL6, and MYC genes were detected in the corresponding samples with generally good agreement. Besides, mutations of 29 commonly affected genes, such as BCL2, MYD88, NOTCH2, EZH2, and CD79B could be identified in the matched samples at a rate of 16/24 (66.7%). Our prospective study demonstrates a non-invasive approach to identify frequent gene fusions and variants in aggressive lymphomas. In conclusion, PB LB sampling substantially supports the oncogenetic diagnostics of lymphomas, especially at anatomically critical sites (such as the central nervous system).

Abstract

Chromosomal translocations and pathogenic nucleotide variants both gained special clinical importance in lymphoma diagnostics. Non-invasive genotyping from peripheral blood (PB) circulating free nucleic acid has been effectively used to demonstrate cancer-related nucleotide variants, while gene fusions were not covered in the past. Our prospective study aimed to isolate and quantify PB cell-free total nucleic acid (cfTNA) from patients diagnosed with aggressive lymphoma and to compare with tumor-derived RNA (tdRNA) from the tissue sample of the same patients for both gene fusion and nucleotide variant testing. Matched samples from 24 patients were analyzed by next-generation sequencing following anchored multiplexed polymerase chain reaction (AMP) for 125 gene regions. Eight different gene fusions, including the classical BCL2, BCL6, and MYC genes, were detected in the corresponding tissue biopsy and cfTNA specimens with generally good agreement. Synchronous BCL2 and MYC translocations in double-hit high-grade B-cell lymphomas were obvious from cfTNA. Besides, mutations of 29 commonly affected genes, such as BCL2, MYD88, NOTCH2, EZH2, and CD79B, could be identified in matched cfTNA, and previously described pathogenic variants were detected in 16/24 cases (66.7%). In 3/24 cases (12.5%), only the PB sample was informative. Our prospective study demonstrates a non-invasive approach to identify frequent gene fusions and variants in aggressive lymphomas. cfTNA was found to be a high-value representative reflecting the complexity of the lymphoma aberration landscape.

Analysis of colorectal cancer-related mutations by liquid biopsy: Utility of circulating cell-free DNA and circulating tumor cells

We recruited 56 colorectal cancer patients and compared the mutational spectrum of tumor tissue DNA, circulating cell‐free DNA (ccfDNA) and circulating tumor cell (CTC) DNA (ctcDNA) to evaluate the potential of liquid biopsy to detect heterogeneity of cancer. Tumor tissue DNA, ccfDNA, and ctcDNA were extracted from each patient and analyzed using next‐generation sequencing (NGS) and digital PCR. To maximize yields of CTC, three antibodies were used in the capture process. From 34 untreated patients, 53 mutations were detected in tumor tissue DNA using NGS. Forty‐seven mutations were detected in ccfDNA, including 20 not detected in tissues. Sixteen mutations were detected in ctcDNA, including five not detected in tissues. In 12 patients (35.3%), mutations not found in tumor tissues were detected by liquid biopsy: nine (26.5%) in ccfDNA only and three (8.8%) in ctcDNA only. Combination analysis of the two liquid biopsy samples increased the sensitivity to detect heterogeneity. From 22 stage IV patients with RAS mutations in their primary tumors, RAS mutations were detected in 14 (63.6%) ccfDNA and in eight (36.4%) ctcDNA using digital PCR. Mutations not detected in primary tumors can be identified in ccfDNA and in ctcDNA, indicating the potential of liquid biopsy in complementing gene analysis. Combination analysis improves sensitivity. Sensitivity to detect cancer‐specific mutations is higher in ccfDNA compared with ctcDNA.