Liss, M. A. | Search bioRxiv

bioRxiv2026

Strategies of mechanical adaptations of circulating tumor cells and properties of their cellular microenvironment have predictive and prognostic biomarker value

Mechanically demanding conditions in the blood circulation damage and kill majority of tumor-shed circulating tumor cells (CTCs). Mechanical fitness: a set of mechanical properties detected with atomic force spectroscopy based force spectrometry supports survival of CTCs. We propose that live CTCs isolated from peripheral blood of prostate cancer patients represent distinct strategies of fitness promoting mechanical adaptations to the fluid shear stress. Some of the cells mimicked properties of erythrocytes (high stiffness) or leukocytes (high deformability). The clustering strategy characterized by exceptionally high adhesion is ingenious to CTCs and not found in blood cells. The abundance of CTCs with elevated adhesion has a predictive value for prostate cancer patients starting first round of androgen deprivation therapy. Moreover, a high adhesion score based on individual cells or average patient-specific adhesion is instrumental to stratify recurrent patients that underwent diagnostic imaging by PSMA-PET/CT and clarify inconclusive PSMA scan results. Including contribution of erythrocyte-like strategy broadened the predictive power of CTC mechanophenotyping. Improved biomarking opportunities to predict early castration resistances were noted when the composition of CTC microenvironment was included alongside the mechanical properties. We demonstrated previously that the CTC microenvironment is formed by large cells co-purifying by microfiltration of the blood of cancer patients. Analysis of the association of particular components of CTC microenvironment with the clustering strategy led to pointing at highly adhesive CTC-EMT. However, in the advanced patients adhesiveness of CTC-EMT was surpassed by tumor hybrid cells (THCs), a distinctive kind of invasive species formed by incomplete phagocytosis of CTCs by macrophages. THCs changed their mechanical phenotype and strategy preference with disease progression pointing at the dynamic nature of adaptations of tumor-shed cells to circulation conditions.

cancer biology↗

bioRxiv2026

Circulating Microbial DNA as a Potential Cancer Biomarker: Technical Challenges and Controlled Evaluation

Abstract Background. Circulating microbial DNA (cmDNA) has been proposed as a non-invasive cancer biomarker, but most evidence comes from cancer-sequencing datasets not designed for microbial analysis and lacking contamination controls. Whether reported signatures reflect biology or artifact is unclear in low-biomass specimens, where standard taxonomic pipelines are prone to systematic error. Methods. In a tightly controlled pilot study of metastatic castration-resistant prostate cancer, we profiled plasma cell-free DNA (cfDNA) and buffy-coat genomic DNA (gDNA) from two patients and two healthy volunteers alongside mock blood-draw and reagent controls, each with and without host-DNA depletion. Reads were classified with Kraken2/Bracken and, independently, with the marker-gene classifier MetaPhlAn. As informatics controls, reads were per-base shuffled to randomize nucleotide order while preserving read length and guanine-cytosine (GC) content, and purely synthetic reads were generated from a four-base process matched only to an aggregate GC target; both were classified identically. Genus abundances were regressed against Kraken2 database k-mer representation and against GC content. Results. Across 40 samples, Kraken2 reported several thousand genera, samples clustered by specimen type in principal-coordinate analysis (PCoA), and pooled genus counts correlated strongly with a published cancer-microbiome catalog (The Cancer Genome Atlas lung adenocarcinoma, TCGA-LUAD; Spearman {rho} = 0.81 over 282 shared genera), a pattern readily interpreted as biological signal. However, these observations were also made in per-base shuffling, which preserves GC content and length but destroys all biological sequence: shuffled reads were still abundantly classified, still clustered by specimen type, and still correlated with the catalog ({rho} {approx} 0.7), as did every sample group, including pure reagent controls. Genus counts scaled tightly with each genus's k-mer representation in the Kraken2 database on real (r 2 = 0.74) and shuffled (r2 = 0.85) reads, and the same dependence appeared in the independent published cohort. Purely synthetic reads carrying no information beyond an aggregate GC target reproduced much of the cross-cohort agreement (synthetic TCGA-LUAD {rho} = 0.61 versus 0.81 for real reads; significant in 27 of 33 TCGA cancers), and replicate shuffles of a low-GC versus a high-GC plasma sample, for which the true difference is zero, produced spurious significant differences in about 46% of genera. Regressing observed counts against the shuffled baseline left 23 genera above the artifact floor at 5% false discovery rate (FDR), nearly all known kit contaminants, control-enriched viruses, or very-low-abundance taxa; a four-criterion validity filter reduced thousands of Kraken2 genera to a single defensible candidate, Klebsiella. Conclusions. Much of the apparent cmDNA structure, including its agreement with a published cancer-microbiome catalog, is explained by base composition and reference-database architecture rather than authentic biology, and short-read k-mer pipelines cannot separate the two on their own. We find little positive evidence of an authentic circulating microbial signal, though our small sample cannot prove its absence. To limit false discovery in low-biomass metagenomics, we recommend specimen-matched negative controls, corroboration with a conservative second classifier, per-base shuffling (with GC-matched synthetic reads as a stricter floor), and GC-aware analysis.

bioinformatics↗