Soluble PD-L1 predicts tumor response and immune-related adverse events in patients with advanced melanoma treated with anti-PD-1 antibodies.

Immune checkpoint inhibitors (ICIs) bring prognostic benefits to patients with malignancies. However, there is a substantial number of patients whose lesions are not improved by ICIs. In addition, ICIs may cause immune-related adverse events (irAEs), which could lead to an unfavorable prognosis with fatal consequences. Therefore, we conducted a retrospective study to evaluate the utility of circulating sPD-L1 (soluble programmed cell death 1 ligand 1) as a biomarker in patients with advanced melanoma treated with anti-PD-1 (programmed cell death 1 protein) antibodies. Sera from 31 consecutive patients were prospectively collected before and after anti-PD-1 antibody treatment and the serum level of sPD-L1 was evaluated. We found that high sPD-L1 levels before treatment were associated with better prognosis, and this association was observed only in patients with a low tumor burden. We also found that sPD-L1 levels were elevated in patients who developed severe irAEs after treatment, and the patients with severe irAEs had significantly higher fluctuations in sPD-L1 (delta sPD-L1) than those without severe irAEs. Our study suggests that serum sPD-L1 level is a useful biomarker to predict tumor response and irAE development in patients with advanced melanoma treated with anti-PD-1 antibodies.

Erratum: Deep convolutional neural networks-based scatterer density and resolution estimators in optical coherence tomography: erratum.

[This corrects the article on p. 168 in vol. 13, PMID: 35154862.].

Label-free visualization and quantification of the drug-type-dependent response of tumor spheroids by dynamic optical coherence tomography.

We demonstrate label-free dynamic optical coherence tomography (D-OCT)-based visualization and quantitative assessment of patterns of tumor spheroid response to three anti-cancer drugs. The study involved treating human breast adenocarcinoma (MCF-7 cell-line) with paclitaxel (PTX), tamoxifen citrate (TAM), and doxorubicin (DOX) at concentrations of 0 (control), 0.1, 1, and 10 µM for 1, 3, and 6 days. In addition, fluorescence microscopy imaging was performed for reference. The D-OCT imaging was performed using a custom-built OCT device. Two algorithms, namely logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDS[Formula: see text]) were used to visualize the tissue dynamics. The spheroids treated with 0.1 and 1 µM TAM appeared similar to the control spheroid, whereas those treated with 10 µM TAM had significant structural corruption and decreasing LIV and OCDS[Formula: see text] over treatment time. The spheroids treated with PTX had decreasing volumes and decrease of LIV and OCDS[Formula: see text] signals over time at most PTX concentrations. The spheroids treated with DOX had decreasing and increasing volumes over time at DOX concentrations of 1 and 10 µM, respectively. Meanwhile, the LIV and OCDS[Formula: see text] signals decreased over treatment time at all DOX concentrations. The D-OCT, particularly OCDS[Formula: see text], patterns were consistent with the fluorescence microscopic patterns. The diversity in the structural and D-OCT results among the drug types and among the concentrations are explained by the mechanisms of the drugs. The presented results suggest that D-OCT is useful for evaluating the difference in the tumor spheroid response to different drugs and it can be a useful tool for anti-cancer drug testing.

Label-free drug response evaluation of human derived tumor spheroids using three-dimensional dynamic optical coherence tomography.

This study aims at demonstrating label-free drug-response-patterns assessment of different tumor spheroids and drug types by dynamic optical coherence tomography (D-OCT). The study involved human breast cancer (MCF-7) and colon cancer (HT-29) spheroids. The MCF-7 and HT-29 spheroids were treated with paclitaxel (Taxol; PTX) and the active metabolite of irinotecan SN-38, respectively. The drugs were applied with 0 (control), 0.1, 1, and 10 µM concentrations and the treatment durations were 1, 3, and 6 days. A swept-source OCT microscope equipped with a repeated raster scanning protocol was used to scan the spheroids. Logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDS[Formula: see text]) algorithms were used to visualize the tumor spheroid dynamics. LIV and OCDS[Formula: see text] images visualized different response patterns of the two types of spheroids. In addition, spheroid morphology, LIV, and OCDS[Formula: see text] quantification showed different time-courses among the spheroid and drug types. These results may indicate different action mechanisms of the drugs. The results showed the feasibility of D-OCT for the evaluation of drug response patterns of different cell spheroids and drug types and suggest that D-OCT can perform anti-cancer drug testing.

Theoretical model for en face optical coherence tomography imaging and its application to volumetric differential contrast imaging.

A new formulation of the lateral imaging process of point-scanning optical coherence tomography (OCT) and a new differential contrast method designed by using this formulation are presented. The formulation is based on a mathematical sample model called the dispersed scatterer model (DSM), in which the sample is represented as a material with a spatially slowly varying refractive index and randomly distributed scatterers embedded in the material. It is shown that the formulation represents a meaningful OCT image and speckle as two independent mathematical quantities. The new differential contrast method is based on complex signal processing of OCT images, and the physical and numerical imaging processes of this method are jointly formulated using the same theoretical strategy as in the case of OCT. The formula shows that the method provides a spatially differential image of the sample structure. This differential imaging method is validated by measuring in vivo and in vitro samples.

Culture of circulating tumor cells using a microfilter device.

Circulating tumor cells (CTCs) are associated with cancer metastasis and prognosis but their scarcity in whole blood prevents their use as a diagnostic tool. The purpose of the present study was to establish a novel approach to capture and cultivate CTCs using a microfilter device. The present study was a prospective study of patients with pancreatic cancer at the University of Tsukuba Hospital (Tsukuba, Japan). From each patient, 5 ml of whole blood was collected into an EDTA collection tube. Whole blood was filtered to isolate CTCs and cells captured on the microfilter were cultured in place. A total of 15 patients were enrolled. CTCs and/or CTC clusters were detected in 2 of 6 cases on day 0. In all cases, CTCs and/or formed clusters and/or colonies were observed during long­term culture periods of up to 103 days. In samples where CTCs were not immediately evident, CTC clusters and colonies emerged after long­term culture. To confirm activity of the cultured CTCs on the filters, staining with Calcein AM was performed and epithelial cellular adhesion molecule­positive cells were observed. The system enables the capture and culture of CTCs. Cultured CTCs may be used for patient­specific drug susceptibility testing and genomic profiling of cancer.

Virtual-freezing fluorescence imaging flow cytometry with 5-aminolevulinic acid stimulation and antibody labeling for detecting all forms of circulating tumor cells.

Circulating tumor cells (CTCs) are precursors to cancer metastasis. In blood circulation, they take various forms such as single CTCs, CTC clusters, and CTC-leukocyte clusters, all of which have unique characteristics in terms of physiological function and have been a subject of extensive research in the last several years. Unfortunately, conventional methods are limited in accurately analysing the highly heterogeneous nature of CTCs. Here we present an effective strategy for simultaneously analysing all forms of CTCs in blood by virtual-freezing fluorescence imaging (VIFFI) flow cytometry with 5-aminolevulinic acid (5-ALA) stimulation and antibody labeling. VIFFI is an optomechanical imaging method that virtually freezes the motion of fast-flowing cells on an image sensor to enable high-throughput yet sensitive imaging of every single event. 5-ALA stimulates cancer cells to induce the accumulation of protoporphyrin (PpIX), a red fluorescent substance, making it possible to detect all cancer cells even if they show no expression of the epithelial cell adhesion molecule, a typical CTC biomarker. Although PpIX signals are generally weak, VIFFI flow cytometry can detect them by virtue of its high sensitivity. As a proof-of-principle demonstration of the strategy, we applied cancer cells spiked in blood to the strategy to demonstrate image-based detection and accurate classification of single cancer cells, clusters of cancer cells, and clusters of a cancer cell(s) and a leukocyte(s). To show the clinical utility of our method, we used it to evaluate blood samples of four breast cancer patients and four healthy donors and identified EpCAM-positive PpIX-positive cells in one of the patient samples. Our work paves the way toward the determination of cancer prognosis, the guidance and monitoring of treatment, and the design of antitumor strategies for cancer patients.

Simultaneous Detection and HER2 Profiling of Circulating Breast Cancer Cells in Clinical Patients Using a Rare Cell Sorter.

BACKGROUND/AIM: This study describes a rare cell sorter (RCS) method to detect circulating tumor cells (CTCs) and CTC clusters in whole blood without pretreatment. PATIENTS AND METHODS: We collected samples from breast cancer patients at the University of Tsukuba Hospital. A total of 15 whole-blood specimens from patients with breast cancer were collected and analyzed via a microfluidics chip, fluorescence-conjugated antibody staining, and fluorescence microscopy. Of 15 total cases, eight were analyzed by RCS ver3 and seven were analyzed by RCS ver3.5 to reveal potential clinical differences in scanning methods. We then examined the HER2 status on 4 of the 15 patients using our RCS system. RESULTS: RCS efficiently detected all subtypes of CTCs and CTC clusters from the peripheral blood of cancer patients. The concordance rate of HER2 status between tissue and CTCs in 4 tested clinical samples was 100%. CONCLUSION: RCS is a non-invasive method that allows for simultaneous detection of CTCs, cluster presence, and surface marker (e.g., HER2) status. Frequent sampling is, thus, possible and the large amount of data obtained will be clinically useful to predict response to therapy as well as plan adjunct support therapies in cancer patients.

Plasma Exchange May Enhance Antitumor Effects by Removal of Soluble Programmed Death-Ligand 1 and Extracellular Vesicles: Preliminary Study.

The antitumor effect of antibody-drug conjugates (ADC) is the main factor in achieving cures. Although the mechanism of tumor resistance to treatment is multifaceted, tumor-derived extracellular vesicles (T-EVs) have been implicated as contributing to the attenuation of ADC therapeutic efficacy. Thus, strategies to eliminate T-EVs are highly promising for overcoming drug resistance. Here we demonstrate plasma exchange therapy to remove T-EVs, decreasing their amount in vitro by 75%. Although trastuzumab emtansine (T-DM1) treatment alone was effective in our rat tumor model, the combination therapy of T-DM1 and T-EV filtration achieved early tumor shrinkage. Our results indicate that T-EV filtration plus ADC is a promising strategy for overcoming drug resistance.

Longitudinal investigation of a xenograft tumor zebrafish model using polarization-sensitive optical coherence tomography.

Breast cancer is a leading cause of death in female patients worldwide. Further research is needed to get a deeper insight into the mechanisms involved in the development of this devastating disease and to find new therapy strategies. The zebrafish is an established animal model, especially in the field of oncology, which has shown to be a promising candidate for pre-clinical research and precision-based medicine. To investigate cancer growth in vivo in zebrafish, one approach is to explore xenograft tumor models. In this article, we present the investigation of a juvenile xenograft zebrafish model using a Jones matrix optical coherence tomography (JM-OCT) prototype. Immunosuppressed wild-type fish at 1-month post-fertilization were injected with human breast cancer cells and control animals with phosphate buffered saline in the tail musculature. In a longitudinal study, the scatter, polarization, and vasculature changes over time were investigated and quantified in control versus tumor injected animals. A significant decrease in birefringence and an increase in scattering signal was detected in tumor injected zebrafish in comparison to the control once. This work shows the potential of JM-OCT as a non-invasive, label-free, three-dimensional, high-resolution, and tissue-specific imaging tool in pre-clinical cancer research based on juvenile zebrafish models.

Deep convolutional neural network-based scatterer density and resolution estimators in optical coherence tomography.

We present deep convolutional neural network (DCNN)-based estimators of the tissue scatterer density (SD), lateral and axial resolutions, signal-to-noise ratio (SNR), and effective number of scatterers (ENS, the number of scatterers within a resolution volume). The estimators analyze the speckle pattern of an optical coherence tomography (OCT) image in estimating these parameters. The DCNN is trained by a large number (1,280,000) of image patches that are fully numerically generated in OCT imaging simulation. Numerical and experimental validations were performed. The numerical validation shows good estimation accuracy as the root mean square errors were 0.23%, 3.65%, 3.58%, 3.79%, and 6.15% for SD, lateral and axial resolutions, SNR, and ENS, respectively. The experimental validation using scattering phantoms (Intralipid emulsion) shows reasonable estimations. Namely, the estimated SDs were proportional to the Intralipid concentrations, and the average estimation errors of lateral and axial resolutions were 1.36% and 0.68%, respectively. The scatterer density estimator was also applied to an in vitro tumor cell spheroid, and a reduction in the scatterer density during cell necrosis was found.

Three-dimensional dynamics optical coherence tomography for tumor spheroid evaluation.

We present a completely label-free three-dimensional (3D) optical coherence tomography (OCT)-based tissue dynamics imaging method for visualization and quantification of the metabolic and necrotic activities of tumor spheroid. Our method is based on a custom 3D scanning protocol that is designed to capture volumetric tissue dynamics tomography images only in a few tens of seconds. The method was applied to the evaluation of a tumor spheroid. The time-course viability alteration and anti-cancer drug response of the spheroid were visualized qualitatively and analyzed quantitatively. The similarity between the OCT-based dynamics images and fluorescence microscope images was also demonstrated.

Clinical Significance of Circulating Tumor Cell Induced Epithelial-Mesenchymal Transition in Patients with Metastatic Colorectal Cancer by Single-Cell RNA-Sequencing.

BACKGROUND: Circulating tumor cells (CTCs) are a prognostic marker in patients with metastatic colorectal cancer (mCRC). However, little is known about the characterization of CTCs in mCRC at the single-cell level using RNA sequencing. The purpose of this study was to validate the capability to detect and isolate single CTCs for single-cell RNA sequencing (scRNA-seq) and to identify clinical significance at a single CTC level. METHODS: Single CTCs from 27 mCRC patients were collected by CTC-FIND, which is comprised of filter separation and immunomagnetic depletion to collect ultra-pure CTC samples. To address tumor heterogeneity, CTCs were collected without relying on any traditional CTC markers, such as epithelial and mesenchymal cell antigens, and were undertaken by scRNA-seq using SMART-Seq v4. RESULTS: We identified 59 single CTCs which were classified into four groups by epithelial, epithelial-mesenchymal transition (EMT) and stem cell-related gene expression. Patients receiving second or later-line treatment who had EMT gene expressing CTCs had a significantly shorter PFS and OS. CONCLUSIONS: Exploiting CTC-FIND with SMART-Seq v4 showed that scRNA-seq of CTCs may shed new insight into tumor heterogeneity of mCRC and that the presence of CTCs expressing EMT-related genes at the single-cell level could have prognostic value in mCRC patients.

Role of enterocyte-specific gene polymorphisms in response to adjuvant treatment for stage III colorectal cancer.

OBJECTIVES: The enterocyte subtype of colorectal cancer (CRC) responds favorably to oxaliplatin-based adjuvant treatment for stage III CRC. We examined the clinical significance of single-nucleotide polymorphisms (SNPs) in enterocyte-related genes MS4A12 and CDX2 in response to adjuvant treatment for stage III CRC. PATIENTS AND METHODS: A total of 350 patients with stage III CRC were included: 274 received adjuvant treatment with surgical resection (discovery cohort) and 76 received surgery alone (control cohort). In the discovery cohort, 68 patients received FOLFOX and 206 received oral fluoropyrimidine. SNPs were analyzed by PCR-based direct sequencing. RESULTS: In the discovery cohort, the MS4A12 rs4939378 G/G variant was associated with lower 5-year survival than any A allele [70% vs. 90%, univariate: hazard ratio (HR) 2.29, 95% confidence interval (CI) 1.03-5.06, P = 0.035; multivariate: HR 2.58, 95% CI 1.15-5.76, P = 0.021]. Patients with the CDX2 rs3812863 G/G variant had better overall survival than those with any A allele, although this was not significant in multivariate analysis (5 year-survival: 95% vs. 82%, univariate: HR 0.34, 95% CI 0.12-0.97, P = 0.034; multivariate: HR 0.39, 95% CI 0.13-1.11, P = 0.078). The SNPs did not show significant association with overall survival in the control cohort, and significant interaction was observed between MS4A12 genotypes and groups (P = 0.007). CONCLUSIONS: Our findings suggest that MS4A12 and CDX2 gene polymorphisms may predict outcome in stage III CRC. However, the clinical significance of SNPs for response to oxaliplatin may differ by tumor stage.

Optical coherence tomography-based tissue dynamics imaging for longitudinal and drug response evaluation of tumor spheroids.

We present optical coherence tomography (OCT)-based tissue dynamics imaging method to visualize and quantify tissue dynamics such as subcellular motion based on statistical analysis of rapid-time-sequence OCT signals at the same location. The analyses include logarithmic intensity variance (LIV) method and two types of OCT correlation decay speed analysis (OCDS). LIV is sensitive to the magnitude of the signal fluctuations, while OCDSs including early- and late-OCDS (OCDS e and OCDS l , respectively) are sensitive to the fast and slow tissue dynamics, respectively. These methods were able to visualize and quantify the longitudinal necrotic process of a human breast adenocarcinoma spheroid and its anti-cancer drug response. Additionally, the effects of the number of OCT signals and the total acquisition time on dynamics imaging are examined. Small number of OCT signals, e.g., five or nine suffice for dynamics imaging when the total acquisition time is suitably long.

Polymorphisms within Immune Regulatory Pathways Predict Cetuximab Efficacy and Survival in Metastatic Colorectal Cancer Patients.

Cetuximab, an IgG1 EGFR-directed antibody, promotes antibody-dependent cell-mediated cytotoxicity. We hypothesized that single-nucleotide polymorphisms (SNPs) in immune regulatory pathways may predict outcomes in patients with metastatic colorectal cancer treated with cetuximab-based regimens. A total of 924 patients were included: 105 received cetuximab in IMCL-0144 and cetuximab/irinotecan in GONO-ASL608LIOM01 (training cohort), 225 FOLFIRI/cetuximab in FIRE-3 (validation cohort 1), 74 oxaliplatin/cetuximab regimens in JACCRO CC-05/06 (validation cohort 2), and 520 FOLFIRI/bevacizumab in FIRE-3 and TRIBE (control cohorts). Twelve SNPs in five genes (IDO1; PD-L1; PD-1; CTLA-4; CD24) were evaluated by PCR-based direct sequencing. We analyzed associations between genotype and clinical outcomes. In the training cohort; patients with the CD24 rs52812045 A/A genotype had a significantly shorter median PFS and OS than those with the G/G genotype (PFS 1.3 vs. 3.6 months; OS 2.3 vs. 7.8 months) in univariate (PFS HR 3.62; p = 0.001; OS HR 3.27; p = 0.0004) and multivariate (PFS HR 3.18; p = 0.009; OS HR 4.93; p = 0.001) analyses. Similarly; any A allele carriers in the JACCRO validation cohort had a significantly shorter PFS than G/G carriers (9.2 vs. 11.8 months; univariate HR 1.90; p = 0.011; multivariate HR 2.12; p = 0.018). These associations were not demonstrated in the control cohorts. CD24 genetic variants may help select patients with metastatic colorectal cancer most likely to benefit from cetuximab-based therapy.

A Novel System to Detect Circulating Tumor Cells Using Two Different Size-selective Microfilters.

BACKGROUND/AIM: Clusters of circulating tumor cells (CTCs) increase metastatic potential compared to single CTC. However, conventional technologies have been unable to generate an accurate analysis of single and cluster CTCs in the peripheral blood. We propose an effective strategy to detect and isolate both single and cluster CTCs using two size-selective microfilters. MATERIALS AND METHODS: Five ml of whole blood were collected from 10 patients with epidermal growth factor receptor mutation-positive non-small cell lung cancer. Single and cluster CTCs were identified using precision microfiltration membranes with two distinct pore sizes together with anti-EpCAM antibody labeling. RESULTS: Single and cluster CTCs were detected by simultaneously using two size-selective microfilters. The EGFR-L858R mutation was detected in the DNA from cells captured using both microfilters. CONCLUSION: Our method can be used to detect and isolate single and cluster CTCs in the whole blood and may facilitate the development of a liquid biopsy strategy.

A polymorphism in the cachexia-associated gene INHBA predicts efficacy of regorafenib in patients with refractory metastatic colorectal cancer.

Activin/myostatin signaling has a critical role not only in cachexia but also in tumor angiogenesis. Cachexia is a frequent complication among patients with advanced cancer and heavily pretreated patients. We aimed to evaluate the prognostic significance of cachexia-associated genetic variants in refractory metastatic colorectal cancer (mCRC) patients treated with regorafenib. Associations between twelve single nucleotide polymorphisms in 8 genes (INHBA, MSTN, ALK4, TGFBR1, ALK7, ACVR2B, SMAD2, FOXO3) and clinical outcome were evaluated in mCRC patients of three cohorts: a discovery cohort of 150 patients receiving regorafenib, a validation cohort of 80 patients receiving regorafenib and a control cohort of 128 receiving TAS-102. In the discovery cohort, patients with any G variant in FOXO3 rs12212067 had a significantly lower response rate (P = 0.031) and overall survival (OS) than those with a T/T in univariate analysis (4.5 vs. 7.6 months, hazard ratio [HR] = 1.63, 95% confidence interval [CI] = 1.09-2.46, P = 0.012). Among female patients, those with any G variant in INHBA rs2237432 had a significantly longer OS than those with an A/A in both univariate (7.6 vs. 4.3 months, HR = 0.57, 95%CI = 0.34-0.95, P = 0.021) and multivariable (HR = 0.53, 95%CI = 0.29-0.94, adjusted P = 0.031) analysis. This association was confirmed in female patients of the validation cohort, though without statistical significance (P = 0.059). Conversely, female patients with any G allele in the control group receiving TAS-102 did not show a longer OS. This was the first study evaluating the associations between polymorphisms in cachexia-associated genes and outcomes in refractory mCRC patients treated with regorafenib. Further studies should be conducted to confirm these associations.

Raman image-activated cell sorting.

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.

Virtual-freezing fluorescence imaging flow cytometry.

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s-1 without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.