Cell by cell immuno- and cancer marker profiling of non-small cell lung cancer tissue: Checkpoint marker expression on CD103+, CD4+ T-cells predicts circulating tumor cells

Single-cell RNA sequencing reveals the dynamics and heterogeneity of lymph node immune cells during acute and chronic viral infections

Introduction

The host immune response determines the differential outcome of acute or chronic viral infections. The comprehensive comparison of lymphoid tissue immune cells at the single-cell level between acute and chronic viral infections is largely insufficient.

Methods

To explore the landscape of immune responses to acute and chronic viral infections, single-cell RNA sequencing(scRNA-seq), scTCR-seq and scBCR-seq were utilized to evaluate the longitudinal dynamics and heterogeneity of lymph node CD45+ immune cells in mouse models of acute (LCMV Armstrong) and chronic (LCMV clone 13) viral infections.

Results

In contrast with acute viral infection, chronic viral infection distinctly induced more robust NK cells and plasma cells at the early stage (Day 4 post-infection) and acute stage (Day 8 post-infection), respectively. Moreover, chronic viral infection exerted decreased but aberrantly activated plasmacytoid dendritic cells (pDCs) at the acute phase. Simultaneously, there were significantly increased IgA+ plasma cells (MALT B cells) but differential usage of B-cell receptors in chronic infection. In terms of T-cell responses, Gzma-high effector-like CD8+ T cells were significantly induced at the early stage in chronic infection, which showed temporally reversed gene expression throughout viral infection and the differential usage of the most dominant TCR clonotype. Chronic infection also induced more robust CD4+ T cell responses, including follicular helper T cells (Tfh) and regulatory T cells (Treg). In addition, chronic infection compromised the TCR diversity in both CD8+ and CD4+ T cells.

Discussion

In conclusion, gene expression and TCR/BCR immune repertoire profiling at the single-cell level in this study provide new insights into the dynamic and differential immune responses to acute and chronic viral infections.

Novel insights into biomarkers of progression in Desmoid tumor

Desmoid tumor (DT) is a rare neoplasm characterized by the proliferation of myofibroblastic cells that infiltrates and invades adjacent tissues. Due to its locally aggressive and recurrent nature, DT often causes local symptoms and can be challenging to manage clinically. Therefore, identifying biomarkers that can predict the progression of DT and guide treatment decisions is critical. This review summarizes several biomarkers that have been implicated in active surveillance (AS) and the prediction of postoperative recurrence and attempts to elucidate their underlying mechanisms. Some of these novel markers could provide prognostic value for clinicians, and ultimately help facilitate optimal and accurate therapeutic decisions for DT.

Label-free detection and enumeration of rare circulating tumor cells by bright-field image cytometry and multi-frame image correlation analysis

Identification and enumeration of circulating tumor cells (CTCs) in peripheral blood are proved to correlate with the progress of metastatic cancer and can provide valuable information for diagnosis and monitoring of cancer. Here, we introduce a bright-field image cytometry (BFIC) technique, assisted by a multi-frame image correlation (MFIC) algorithm, as a label-free approach for tumor cell detection in peripheral blood. For this method, images of flowing cells in a wide channel were continuously recorded and cell types were determined simultaneously using a deep neural network of YOLO-V4 with an average precision (AP) of 98.63%, 99.04%, and 98.95% for cancer cell lines HT29, A549, and KYSE30, respectively. The use of the wide microfluidic channel (400 μm width) allowed for a high throughput of 50 000 cells per min without clogging. Then erroneous or missed cell classifications caused by imaging angle differences or accidental misinterpretations in single frames were corrected by the multi-frame correlation analysis. This further improved the AP to 99.40%, 99.52%, and 99.47% for HT29, A549, and KYSE30, respectively. Meanwhile, cell counting was also accomplished in this dynamic process. Moreover, our imaging cytometry method can readily detect as few as 10 tumor cells from 100 000 white blood cells and was unaffected by the EMT process. Furthermore, CTCs from 8 advanced-stage cancer clinical samples were also successfully detected, while none for 6 healthy control subjects. Although this method is implemented for CTCs, it can also be used for the detection of other rare cells.

Multi-omics data integration approaches for precision oncology

Next-generation sequencing (NGS) has been pivotal to enhance the molecular characterization of human malignancies, allowing multiple omics data types to be available for cancer researchers and practitioners. In this context,...

Programmed Cell Death Ligand 1-Expressing Circulating Tumor Cells: A New Prognostic Biomarker in Non-Small Cell Lung Cancer

BACKGROUND

In non-small cell lung cancer (NSCLC), analysis of programmed cell death ligand 1 (PD-L1) expression in circulating tumor cells (CTCs) is a potential alternative to overcome the problems linked to the tumor biopsy spatiotemporal heterogeneity. However, the prognostic significance of PD-L1-positive [PD-L1(+)] CTCs remains controversial.

METHODS

We prospectively evaluated the correlation with clinicopathological variables and prognostic value of PD-L1(+) CTCs, detected with the FDA-cleared CellSearch® system, in 54 patients with advanced NSCLC.

RESULTS

We detected CTCs and PD-L1(+) CTCs in 43.4% and 9.4% of patients with NSCLC. PD-L1 expression concordance between tumor tissue and CTCs was low (54%). The presence of PD-L1(+) CTC correlated with the absence of gene alterations in tumor tissue and with poor prognosis-related biological variables (anemia, hyponatremia, increased lactate dehydrogenase). In univariate analysis, absence of gene alterations, number of metastatic sites, prior systemic therapies, and presence of CTCs and PD-L1(+) CTCs were associated with worse overall survival, whereas PD-L1 expression in tumor tissue was not. In multivariate analysis, squamous cell carcinoma histology, number of prior systemic treatments, and the presence of CTC were significantly associated with overall survival. Survival was worse in patients with PD-L1(+) CTCs than in patients with PD-L1-negative CTC or without any CTC.

CONCLUSIONS

Our study suggests that the presence of PD-L1(+) CTCs is associated with poor prognosis in patients with advanced NSCLC. Studies with larger samples are needed to confirm our results and to determine how PD-L1(+) CTC detection could help to predict the response or resistance to anti-PD-1/PD-L1 therapies.Clinical trial registration NCT02866149.