Tumor shedding and metastatic progression after tumor excision in patient-derived orthotopic xenograft models of triple-negative breast cancer

Automated Image Analysis for Characterization of Circulating Tumor Cells and Clusters Sorted by Magnetic Levitation

Magnetic levitation-based sorting technologies have revolutionized the detection and isolation of rare cells, including circulating tumor cells (CTCs) and circulating tumor cell clusters (CTCCs). Manual counting and quantification of these cells are prone to time-consuming processes, human error, and inter-observer variability, particularly challenging when heterogeneous cell types in 3D clusters are present. To overcome these challenges, we developed "Fastcount," an in-house MATLAB-based algorithm for precise, automated quantification and phenotypic characterization of CTCs and CTCCs, in both 2D and 3D. Fastcount is 120 times faster than manual counting and produces reliable results with a ±7.3% deviation compared to a trained laboratory technician. By analyzing 400 GB of fluorescence imaging data, we showed that Fastcount outperforms manual counting and commercial software when cells are aggregated in 3D or staining artifacts are present, delivering more accurate results. We further employed Fastcount for automated analysis of 3D image stacks obtained from CTCCs isolated from colorectal adenocarcinoma and renal cell carcinoma blood samples. Interestingly, we observed a highly heterogeneous spatial cellular composition within CTCCs, even among clusters from the same patient. Overall, Fastcount can be employed for various applications with lab-chip devices, such as CTC detection, CTCC analysis in 3D and cell detection in biosensors.

Assessment of Different Circulating Tumor Cell Platforms for Uveal Melanoma: Potential Impact for Future Routine Clinical Practice

Liquid biopsy and circulating tumor cell (CTC) screening has gained interest over the last two decades for detecting almost all solid malignancies. To date, the major limitation in terms of the applicability of CTC screening in daily clinical practice is the lack of reproducibility due to the high number of platforms available that use various technologies (e.g., label-dependent versus label-free detection). Only a few studies have compared different CTC platforms. The aim of this study was to compare the efficiency of four commercially available CTC platforms (Vortex (VTX-1), ClearCell FX, ISET, and Cellsearch) for the detection and identification of uveal melanoma cells (OMM 2.3 cell line). Tumor cells were seeded in RPMI medium and venous blood from healthy donors, and then processed similarly using these four platforms. Melan-A immunochemistry was performed to identify tumor cells, except when the Cellsearch device was used (automated identification). The mean overall recovery rates (with mean recovered cells) were 39.2% (19.92), 22.2% (11.31), 8.9% (4.85), and 1.1% (0.20) for the ISET, Vortex (VTX-1), ClearCell FX, and CellSearch platforms, respectively. Although paramount, the recovery rate is not sufficient to assess a CTC platform. Other parameters, such as the purpose for using a platform (diagnosis, genetics, drug sensitivity, or patient-derived xenograft models), reproducibility, purity, user-friendliness, cost-effectiveness, and ergonomics, should also be considered before they can be used in daily clinical practice and are discussed in this article.

The functional and clinical roles of liquid biopsy in patient-derived models

The liquid biopsy includes the detection of circulating tumor cells (CTCs) and CTC clusters in blood, as well as the detection of, cell-free DNA (cfDNA)/circulating tumor DNA (ctDNA) and extracellular vesicles (EVs) in the patient's body fluid. Liquid biopsy has important roles in translational research. But its clinical utility is still under investigation. Newly emerged patient-derived xenograft (PDX) and CTC-derived xenograft (CDX) faithfully recapitulate the genetic and morphological features of the donor patients' tumor and patient-derived organoid (PDO) can mostly mimic tumor growth, tumor microenvironment and its response to drugs. In this review, we describe how the development of these patient-derived models has assisted the studies of CTCs and CTC clusters in terms of tumor biological behavior exploration, genomic analysis, and drug testing, with the help of the latest technology. We then summarize the studies of EVs and cfDNA/ctDNA in PDX and PDO models in early cancer diagnosis, tumor burden monitoring, drug test and response monitoring, and molecular profiling. The challenges faced and future perspectives of research related to liquid biopsy using patient-derived models are also discussed.

Patient-derived xenograft (PDX) models, applications and challenges in cancer research

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Long Noncoding RNA NONHSAT079852.2 Contributes to GBM Recurrence by Functioning as a ceRNA for has-mir-10401-3p to Facilitate HSPA1A Upregulation

Glioblastoma multiforme (GBM) is the most common brain malignancy and major cause of high mortality in patients with GBM, and its high recurrence rate is its most prominent feature. However, the pathobiological mechanisms involved in recurrent GBM remain largely unknown. Here, whole-transcriptome sequencing (RNA-sequencing, RNA-Seq) was used in characterizing the expression profile of recurrent GBM, and the aim was to identify crucial biomarkers that contribute to GBM relapse. Differentially expressed RNAs in three recurrent GBM tissues compared with three primary GBM tissues were identified through RNA-Seq. The function and mechanism of a candidate long noncoding RNA (lncRNA) in the progression and recurrence of GBM were elucidated by performing comprehensive bioinformatics analyses, such as functional enrichment analysis, protein-protein interaction prediction, and lncRNA-miRNA-mRNA regulatory network construction, and a series of in vitro assays. As the most significantly upregulated gene identified in recurrent GBM, HSPA1A is mainly related to antigen presentation and the MAPK signaling pathway, as indicated by functional enrichment analysis. HSPA1A was predicted as the target gene of the lncRNA NONHSAT079852.2. qRT-PCR revealed that NONHSAT079852.2 was significantly elevated in recurrent GBM relative to that in primary GBM, and high NONHSAT079852.2 expression was associated with the poor overall survival rates of patients with GBM. The knockdown of NONHSAT079852.2 successfully induced tumor cell apoptosis, inhibited the proliferation, migration, invasion and the expression level of HSPA1A in glioma cells. NONHSAT079852.2 was identified to be a sponge for hsa-miR-10401-3p through luciferase reporter assay. Moreover, HSPA1A was targeted and regulated by hsa-miR-10401-3p. Collectively, the results suggested that NONHSAT079852.2 acts as a sponge of hsa-mir-10401-3p and thereby enhances HSPA1A expression, promotes tumor cell proliferation and invasion, and leads to the progression and recurrence of GBM. This study will provide new insight into the regulatory mechanisms of NONHSAT079852.2-mediated competing endogenous RNA in the pathogenesis of recurrent GBM and evidence of the potential of lncRNAs as diagnostic biomarkers or potential therapeutic targets.

Targeting the tetraspanin CD81 reduces cancer invasion and metastasis

Tetraspanins are an evolutionary conserved family of proteins involved in multiple aspects of cell physiology, including proliferation, migration and invasion, protein trafficking, and signal transduction; yet their detailed mechanism of action is unknown. Tetraspanins have no known natural ligands, but their engagement by antibodies has begun to reveal their role in cell biology. Studies of tetraspanin knockout mice and of germline mutations in humans have highlighted their role under normal and pathological conditions. Previously, we have shown that mice deficient in the tetraspanin CD81 developed fewer breast cancer metastases compared to their wild-type (WT) counterparts. Here, we show that a unique anti-human CD81 antibody (5A6) effectively halts invasion of triple-negative breast cancer (TNBC) cell lines. We demonstrate that 5A6 induces CD81 clustering at the cell membrane and we implicate JAM-A protein in the ability of this antibody to inhibit tumor cell invasion and migration. Furthermore, in a series of in vivo studies we demonstrate that this antibody inhibits metastases in xenograft models, as well as in syngeneic mice bearing a mouse tumor into which we knocked in the human CD81 epitope recognized by the 5A6 antibody.

Minimal Residual Disease, Metastasis and Immunity

Progression from localized to metastatic disease requires cancer cells spreading to distant organs through the bloodstream. Only a small proportion of these circulating tumor cells (CTCs) survives dissemination due to anoikis, shear forces and elimination by the immune system. However, all metastases originate from CTCs capable of surviving and extravasating into distant tissue to re-initiate a tumor. Metastasis initiation is not always immediate as disseminated tumor cells (DTCs) may enter a non-dividing state of cell dormancy. Cancer dormancy is a reversible condition that can be maintained for many years without being clinically detectable. Subsequently, late disease relapses are thought to be due to cancer cells ultimately escaping from dormant state. Cancer dormancy is usually associated with minimal residual disease (MRD), where DTCs persist after intended curative therapy. Thus, MRD is commonly regarded as an indicator of poor prognosis in all cancers. In this review, we examine the current understanding of MRD and immunity during cancer progression to metastasis and discuss clinical perspectives for oncology.

Oral Methioninase Inhibits Recurrence in a PDOX Mouse Model of Aggressive Triple-negative Breast Cancer

BACKGROUND/AIM

The aim of the study was to use a triple-negative breast cancer (TNBC) patient-derived orthotopic xenograft (PDOX) model to examine the efficacy of oral recombinant methioninase (o-rMETase) against this recalcitrant disease.

MATERIALS AND METHODS

The TNBC tumor from a patient was implanted in the right 4^th inguinal mammary fat pad of nude mice. Two weeks later, the mice underwent tumorectomy with grossly-negative surgical margins. Two days after tumorectomy the mice were divided in two groups: one control and one treated with o-rMETase.

RESULTS

Tumors recurred in all mice. On day 11, the mean recurrent tumor volumes were 936.7 mm³ in the control group and 450.9 mm³ in the o-rMETase group (p<0.05). On day 15, the mean recurrent tumor volumes were 3392.5 mm³ in the control group and 1603.5 mm³ in the o-rMETase group. The mean recurrent tumor weights were 2.1 g in the control group and 1.1 g in the o-rMETase group on day 15.

CONCLUSION

o-rMETase is an effective adjuvant treatment for aggressive TNBC.

Effects of Cancer Stem Cells in Triple-Negative Breast Cancer and Brain Metastasis: Challenges and Solutions

A higher propensity of developing brain metastasis exists in triple-negative breast cancer (TNBC). Upon comparing the metastatic patterns of all breast cancer subtypes, patients with TNBC exhibited increased risks of the brain being the initial metastatic site, early brain metastasis development, and shortest brain metastasis-related survival. Notably, the development of brain metastasis differs from that at other sites owing to the brain-unique microvasculature (blood brain barrier (BBB)) and intracerebral microenvironment. Studies of brain metastases from TNBC have revealed the poorest treatment response, mostly because of the relatively backward strategies to target vast disease heterogeneity and poor brain efficacy. Moreover, TNBC is highly associated with the existence of cancer stem cells (CSCs), which contribute to circulating cancer cell survival before BBB extravasation, evasion from immune surveillance, and plasticity in adaptation to the brain-specific microenvironment. We summarized recent literature regarding molecules and pathways and reviewed the effects of CSC biology during the formation of brain metastasis in TNBC. Along with the concept of individualized cancer therapy, certain strategies, namely the patient-derived xenograft model to overcome the lack of treatment-relevant TNBC classification and techniques in BBB disruption to enhance brain efficacy has been proposed in the hope of achieving treatment success.

Biomarkers in Triple-Negative Breast Cancer: State-of-the-Art and Future Perspectives

Triple-negative breast cancer (TNBC) is a heterogeneous group of tumors characterized by aggressive behavior, high risk of distant recurrence, and poor survival. Chemotherapy is still the main therapeutic approach for this subgroup of patients, therefore, progress in the treatment of TNBC remains an important challenge. Data derived from molecular technologies have identified TNBCs with different gene expression and mutation profiles that may help developing targeted therapies. So far, however, only a few of these have shown to improve the prognosis and outcomes of TNBC patients. Robust predictive biomarkers to accelerate clinical progress are needed. Herein, we review prognostic and predictive biomarkers in TNBC, discuss the current evidence supporting their use, and look at the future of this research field.