Lung cancer is by far the leading cause of cancer death worldwide, with non-small cell lung cancer (NSCLC) accounting for the majority of cases. Recent advances in the understanding of the biology of tumors and in highly sensitive detection technologies for molecular analysis offer targeted therapies, such as epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors. However, our understanding of an individual patient’s lung cancer is often limited by tumor accessibility because of the high risk and invasive nature of current tissue biopsy procedures. “Liquid biopsy”, the analysis of circulating biomarkers from peripheral blood, such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), offers a new source of cancer-derived materials that may reflect the status of the disease better and thereby contribute to more personalized treatment. In this review, we examined the clinical significance and uniqueness of CTCs and ctDNA from NSCLC patients, isolation and detection methods developed to analyze each type of circulating biomarker, and examples of clinical studies of potential applications for early diagnosis, prognosis, treatment monitoring, and prediction of resistance to therapy. We also discuss challenges that remain to be addressed before such tools are implemented for routine use in clinical settings.

The emergence of chemotherapy resistance drives cancer lethality in cancer patients, with treatment initially reducing overall tumor burden followed by resistant recurrent disease. While molecular mechanisms underlying resistance phenotypes have been explored, less is known about the cell biological characteristics of cancer cells that survive to eventually seed the recurrence. To identify the unique phenotypic characteristics associated with survival upon chemotherapy exposure, we characterized nuclear morphology and function as prostate cancer cells recovered following cisplatin treatment. Cells that survived in the days and weeks after treatment and resisted therapy-induced cell death showed increasing cell size and nuclear size, enabled by continuous endocycling resulting in repeated whole genome doubling. We further found that cells that survive after therapy release were predominantly mononucleated and likely employ more efficient DNA damage repair. Finally, we show that surviving cancer cells exhibit a distinct nucleolar phenotype and increased rRNA levels. These data support a paradigm where soon after therapy release, the treated population mostly contains cells with a high level of widespread and catastrophic DNA damage that leads to apoptosis, while the minority of cells that have successful DDR are more likely to access a pro-survival state. These findings are consistent with accession of the polyaneuploid cancer cell (PACC) state, a recently described mechanism of therapy resistance and tumor recurrence. Our findings demonstrate the fate of cancer cells following cisplatin treatment and define key cell phenotypic characteristics of the PACC state. This work is essential for understanding and, ultimately, targeting cancer resistance and recurrence.

Extracellular vesicles (EVs) carry molecular cargo that can reflect the real-time state of parental cells, yet most in vitro EV analyses rely on bulk approaches and therefore average over pronounced heterogeneity in both cell and EV populations. Here, we present a semi-open microfluidic platform that enables multi-marker profiling of EVs released from single-cell-derived clones, allowing EV signatures to be linked to clonal progeny originating from a single parental cell. The platform integrates aligned cell and EV arrays containing 17,305 wells, assembled with a 3D-printed housing to capture released EVs in one-to-one matched wells. Captured EVs are immunolabeled for canonical tetraspanin markers (CD9, CD63, CD81) and EpCAM, imaged by high-resolution fluorescence microscopy, and quantified using an automated image-analysis pipeline. Applying the platform to single-cell-derived PC3 clones revealed substantial heterogeneity in EV marker co-expression, with hierarchical clustering identifying four distinct tetraspanin co-expression profiles. The fraction of EpCAM-positive EVs increased with PC3 cell proliferation, as assessed by endpoint cell number, whereas free (non-EV-associated) EpCAM showed no correlation. This platform enables near single-EV-level, multi-marker profiling from single-cell lineages and provides a practical approach to simultaneously dissect both cellular and EV heterogeneity.