Emulation and evaluation of tumor cell combined chemotherapy in isotropic/anisotropic collagen fiber microenvironments.

The rapid emergence of anisotropic collagen fibers in the tissue microenvironment is a critical transition point in late-stage breast cancer. Specifically, the fiber orientation facilitates the likelihood of high-speed tumor cell invasion and metastasis, which pose lethal threats to patients. Thus, based on this transition point, one key issue is how to determine and evaluate efficient combination chemotherapy treatments in late-stage cancer. In this study, we designed a collagen microarray chip containing 241 high-throughput microchambers with embedded metastatic breast cancer cell MDA-MB-231-RFP. By utilizing collagen's unique structure and hydromechanical properties, the chip constructed three-dimensional isotropic and anisotropic collagen fiber structures to emulate the tumor cell microenvironment at early and late stages. We injected different chemotherapeutic drugs into its four channels and obtained composite biochemical concentration profiles. Our results demonstrate that anisotropic collagen fibers promote cell proliferation and migration more than isotropic collagen fibers, suggesting that the geometric arrangement of fibers plays an important role in regulating cell behavior. Moreover, the presence of anisotropic collagen fibers may be a potential factor leading to the poor efficacy of combined chemotherapy in late-stage breast cancer. We investigated the efficacy of various chemotherapy drugs using cell proliferation inhibitors paclitaxel and gemcitabine and tumor cell migration inhibitors 7rh and PP2. To ensure the validity of our findings, we followed a systematic approach that involved testing the inhibitory effects of these drugs. According to our results, the drug combinations' effectiveness could be ordered as follows: paclitaxel + gemcitabine > gemcitabine + 7rh > PP2 + paclitaxel > 7rh + PP2. This study shows that the biomimetic chip system not only facilitates the creation of a realistic in vitro model for examining the cell migration mechanism in late-stage breast cancer but also has the potential to function as an effective tool for future chemotherapy assessment and personalized medicine.

Anlotinib plus docetaxel vs. docetaxel alone for advanced non-small-cell lung cancer patients who failed first-line treatment: A multicenter, randomized phase II trial.

OBJECTIVES: Given the modest efficacy of docetaxel in advanced non-small cell lung cancer (NSCLC), this study assesses the therapeutic potential and safety profile of anlotinib in combination with docetaxel compared to docetaxel monotherapy as a second-line therapy for patients with advanced NSCLC. MATERIALS AND METHODS: In this phase II study, patients with advanced NSCLC experiencing failure with first-line platinum-based regimens were randomized in a 1:1 ratio to receive either anlotinib plus docetaxel or docetaxel alone. Primary endpoint was progression-free survival (PFS), with overall survival (OS), objective response rate (ORR), disease control rate (DCR), and safety as secondary endpoints. RESULTS: A total of 83 patients were randomized. The combination of anlotinib and docetaxel significantly extended median PFS to 4.4 months compared to 1.6 months for docetaxel alone (hazard ratio [HR] = 0.38, 95 % confidence interval [CI]: 0.23-0.63, P = 0.0002), and also demonstrated superior ORR (32.5 % vs. 9.3 %, P = 0.0089) and DCR (87.5 % vs. 53.5 %, P = 0.0007). Median OS was observed at 12.0 months in the combination group vs. 10.9 months in the monotherapy group (HR = 0.82, 95 % CI: 0.47-1.43, P = 0.4803). For patients previously treated with immunotherapy, the median PFS was notably longer at 7.8 vs. 1.7 months (HR = 0.22, 95 % CI: 0.09-0.51, P = 0.0290). The incidence of grade ≥ 3 treatment-related adverse events, predominantly leukopenia (15.0 % vs. 7.0 %) and neutropenia (10.0 % vs. 5.0 %), was manageable across both groups. CONCLUSION: Anlotinib plus docetaxel offers a viable therapeutic alternative for patients with advanced NSCLC who failed first-line platinum-based treatments.

Morphological entropy encodes cellular migration strategies on multiple length scales.

Cell migration is crucial for numerous physiological and pathological processes. A cell adapts its morphology, including the overall and nuclear morphology, in response to various cues in complex microenvironments, such as topotaxis and chemotaxis during migration. Thus, the dynamics of cellular morphology can encode migration strategies, from which diverse migration mechanisms can be inferred. However, deciphering the mechanisms behind cell migration encoded in morphology dynamics remains a challenging problem. Here, we present a powerful universal metric, the Cell Morphological Entropy (CME), developed by combining parametric morphological analysis with Shannon entropy. The utility of CME, which accurately quantifies the complex cellular morphology at multiple length scales through the deviation from a perfectly circular shape, is illustrated using a variety of normal and tumor cell lines in different in vitro microenvironments. Our results show how geometric constraints affect the MDA-MB-231 cell nucleus, the emerging interactions of MCF-10A cells migrating on collagen gel, and the critical transition from proliferation to invasion in tumor spheroids. The analysis demonstrates that the CME-based approach provides an effective and physically interpretable tool to measure morphology in real-time across multiple length scales. It provides deeper insight into cell migration and contributes to the understanding of different behavioral modes and collective cell motility in more complex microenvironments.

AttnPep: A Self-Attention-Based Deep Learning Method for Peptide Identification in Shotgun Proteomics.

In shotgun proteomics, the proteome search engine analyzes mass spectra obtained by experiments, and then a peptide-spectra match (PSM) is reported for each spectrum. However, most of the PSMs identified are incorrect, and therefore various postprocessing software have been developed for reranking the peptide identifications. Yet these methods suffer from issues such as dependency on distribution, reliance on shallow models, and limited effectiveness. In this work, we propose AttnPep, a deep learning model for rescoring PSM scores that utilizes the Self-Attention module. This module helps the neural network focus on features relevant to the classification of PSMs and ignore irrelevant features. This allows AttnPep to analyze the output of different search engines and improve PSM discrimination accuracy. We considered a PSM to be correct if it achieves a q-value <0.01 and compared AttnPep with existing mainstream software PeptideProphet, Percolator, and proteoTorch. The results indicated that AttnPep found an average increase in correct PSMs of 9.29% relative to the other methods. Additionally, AttnPep was able to better distinguish between correct and incorrect PSMs and found more synthetic peptides in the complex SWATH data set.

A phase Ib/II study of cadonilimab (PD-1/CTLA-4 bispecific antibody) plus anlotinib as first-line treatment in patients with advanced non-small cell lung cancer.

BACKGROUND: Cadonilimab is a bispecific antibody that simultaneously targets programmed cell death receptor-1 and cytotoxic T lymphocyte-associated antigen-4. This study aimed to assess the safety and efficacy of cadonilimab plus anlotinib for the first-line treatment of advanced non-small cell lung cancer (NSCLC) without sensitizing EGFR/ALK/ROS1 mutations. METHODS: Patients received cadonilimab 15 mg/kg and 10 mg/kg every three weeks (Q3W) plus anlotinib at doses of 10 or 12 mg once daily for two weeks on a one-week-off schedule. The primary endpoints included safety and objective response rate (ORR). RESULTS: Sixty-nine treatment-naïve patients received cadonilimab 15 mg/kg Q3W combination (n = 49) and 10 mg/kg Q3W combination (n = 20). Treatment-related adverse events (TRAEs) were reported in 48 (98.0%) and 19 (95.0%) patients, with grade ≥3 TRAEs occurring in 29 (59.2%) and five (25.0%) patients, respectively. TRAEs leading to cadonilimab discontinuation occurred in eight (16.3%) and one (5.0%) patients in the cadonilimab 15 mg/kg Q3W and 10 mg/kg Q3W dosing groups. The confirmed ORRs were 51.0% (25/49) and 60.0% (12/20) accordingly. CONCLUSIONS: Cadonilimab 10 mg/kg Q3W plus anlotinib showed manageable safety and promising efficacy as a first-line chemo-free treatment for advanced NSCLC. GOV IDENTIFIER: NCT04646330.

Influence factors of the survival in colorectal cancer patients with second primary malignancy after surgery: A SEER database analysis.

The survival rate is significantly reduced in patients with colorectal cancer (CRC) who developing a second primary malignancy (SPM), and however, little has known about the factors that contribute to the mortality of SPMs among CRC survivors. This study aims to explore the influence factors in both the all-cause and cancer-specific mortality of patients with SPMs after CRC surgery. Data of adult CRC patients with SPMs were extracted from the Surveillance, Epidemiology, and End Results (SEER) database in this retrospective cohort study. The associations between potential influence factors and all-cause mortality and cancer-specific mortality were explored using univariate and multivariate Cox proportional hazards analyses. The evaluation indexes were hazard ratios (HRs), and 95% confidence intervals (CIs). We also drew pie charts to respectively reflect the distributions of SPMs sites and time interval in study population. A total of 1202 (56.14%) patients died for all-cause, and 464 (21.67%) died due to CRC. The results showed that after adjusting for covariates, age, sex, marital status, T stage of CRC, second primary cancer site, stage of SPMs, grade of SPMs, TNM stage of SPMs, and time interval were associated with all-cause mortality, while marital status, stage of CRC, T stage of CRC, chemotherapy, second primary cancer site, stage of SPMs, grade of SPMs, TNM stage of SPMs, and time interval were associated with cancer-specific mortality in patients with CRC. In addition, colon (23.5%) was the most common site of SPMs, followed by digestive system (19.0%), and the time interval between CRC and SPMs in most patients was over 5 years (28.4%). Our findings may assist clinicians to identify high-risk patients for SPMs after CRC surgery. Also, the postoperative long-term follow-up and close attention on the key systems where the SPMs may occur are of great necessary in patients with CRC.

Phosphorylation of PPDPF via IL6-JAK2 activates the Wnt/ß-catenin pathway in colorectal cancer.

Inflammation plays an important role in the initiation and progression of colorectal cancer (CRC) and leads to ß-catenin accumulation in colitis-related CRC. However, the mechanism remains largely unknown. Here, pancreatic progenitor cell differentiation and proliferation factor (PPDPF) is found to be upregulated in CRC and significantly correlated with tumor-node-metastasis (TNM) stages and survival time. Knockout of PPDPF in the intestinal epithelium shortens crypts, decreases the number of stem cells, and inhibits the growth of organoids and the occurrence of azoxymethane (AOM)/dextran sodium sulfate (DSS)-induced CRC. Mechanistically, PPDPF is found to interact with Casein kinase 1α (CK1α), thereby disrupting its binding to Axin, disassociating the ß-catenin destruction complex, decreasing the phosphorylation of ß-catenin, and activating the Wnt/ß-catenin pathway. Furthermore, interleukin 6 (IL6)/Janus kinase 2 (JAK2)-mediated inflammatory signals lead to phosphorylation of PPDPF at Tyr16 and Tyr17, stabilizing the protein. In summary, this study demonstrates that PPDPF is a key molecule in CRC carcinogenesis and progression that connects inflammatory signals to the Wnt/ß-catenin signaling pathway, providing a potential novel therapeutic target.

3D collagen microchamber arrays for combined chemotherapy effect evaluation on cancer cell numbers and migration.

Breast cancer metastasis involves complex mechanisms, particularly when patients are undergoing chemotherapy. In tissues, tumor cells encounter cell-cell interactions, cell-microenvironment interactions, complex nutrient, and drug gradients. Currently, two-dimensional cell culture systems and animal models are challenging to observe and analyze cell responses to microenvironments with various physical and bio-chemical conditions, and microfluidic technology has been systematically developed to address this dilemma. In this study, we have constructed a combined chemotherapy evaluation chip (CCEC) based on microfluidic technology. The chip possesses 192 diamond-shaped microchambers containing MDA-MB-231-RFP cells, and each microchamber is composed of collagen to mimic breast cancer and its surrounding microenvironment. In addition, by adding medium containing different drugs to the medium channels of CCEC, composite drug (paclitaxel+gemcitabine+7rh and paclitaxel+fluorouracil+PP2) concentration gradients, and single drug (paclitaxel, gemcitabine, 7rh, fluorouracil, PP2) concentration gradients have been established in the five collagen regions, respectively, so that each localized microchamber in the regions has a unique drug microenvironment. In this way, we evaluated the composite and single chemotherapy efficacy on the same chip by statistically analyzing their effects on the numbers and migration of the cell. The quantitative results in CCECs reveal that the inhibition effects on the numbers and migration of MDA-MB-231-RFP cell under the composite drug gradients are more optimal than those of the single drugs. Besides, the cancer cell inhibition effect between the groups composed of two drugs has also been compared, that is the paclitaxel+gemcitabine, paclitaxel+fluorouracil, and paclitaxel+PP2 have better cell numbers and migration inhibition effects than paclitaxel+7rh. The results indicate that the bio-mimetic and high-throughput combined chemotherapy evaluation platform can serve as a more efficient and accurate tool for preclinical drug development and screening.

Rh-endostatin plus camrelizumab and chemotherapy in first-line treatment of advanced non-small cell lung cancer: A multicenter retrospective study.

BACKGROUND: Clinical evidence of immune checkpoint inhibitors combined with antiangiogenic drugs in patients with advanced non-small cell lung cancer (NSCLC) was limited. Recombinant human endostatin (rh-endostatin), an antiangiogenic drug, and camrelizumab, an anti-PD-1 antibody, have been approved for the treatment of advanced NSCLC in China. This study aimed to investigate the efficacy and safety of rh-endostatin plus camrelizumab and chemotherapy in the treatment of advanced NSCLC. METHODS: Eligible patients were enrolled and received camrelizumab (200 mg, day 1) every 3 weeks and continuous intravenous infusion of rh-endostatin (70 mg/day, days 1-3) and cisplatin combined with pemetrexed (for adenocarcinoma) or paclitaxel (for NSCLC other than adenocarcinoma) every 3 weeks. Primary endpoint was progression-free survival (PFS). Secondary endpoints were objective response rate (ORR), disease control rate (DCR), overall survival (OS), and safety profiles. RESULTS: Overall, 27 patients were included, and 25 patients were eligible for efficacy evaluation. For these 25 patients, ORR was 48.15% (13/27) and DCR was 85.19% (23/27). With a median follow-up of 10.37 months, the median PFS was 8.9 (95% CI: 4.23-13.57) months. Median OS was not reached. Overall, 96.3% of patients experienced at least one treatment-related adverse event, and grade 3 TRAEs occurred in 9 (33.3%) patients. No unexpected AEs were observed. CONCLUSION: Rh-endostatin plus camrelizumab and chemotherapy showed favorable efficacy and safety profile in patients with advanced NSCLC, representing a promising treatment regimen for these patients.

The efficacy and safety of immune checkpoint inhibitors combined with chemotherapy or anti-angiogenic therapy as a second-line or later treatment option for advanced non-small cell lung cancer: a retrospective comparative cohort study.

Background: Although immune checkpoint inhibitor (ICI) monotherapy remains the standard of second-line treatment for patients with advanced non-small cell lung cancer (NSCLC) , the objective response rate (ORR) is low. There is an urgent need to increase the response population of second-line immunotherapy, and ICI combination therapy may be a possible option. However, the evidence is insufficient. Methods: We retrospectively collected the medical records of patients who received ICI monotherapy or ICI combination therapy as a second-line or later treatment option. We further analysed baseline clinical characteristics, evaluated treatment efficacy, assessed treatment-related adverse events (AEs) and followed up survival. The outcome variables assessed in the study were ORR, disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and AEs. Results: A total of 145 patients were ultimately enrolled in this study, including the ICI monotherapy group (n=63) and ICI combination therapy group (n=82). The ICI combination therapy group was further divided into the ICI/chemotherapy group (n=57) and ICI/anti-angiogenic therapy group (n=25). The baseline was comparable among the three subgroups. The ICI combination therapy groups showed a higher ORR (29.3% vs. 11.1%, P=0.008) and DCR (85.4% vs. 61.9%, P=0.001) and a longer PFS (6.77 vs. 3.47 months, P<0.001) and OS (18.60 vs. 8.47 months, P<0.001) than the ICI monotherapy group. The ICI/chemotherapy group showed a significantly higher ORR (31.6% vs. 11.1%, P=0.006) and DCR (84.2% vs. 61.9%, P=0.006) and a longer PFS (6.37 vs. 3.47 months, P<0.001) and OS (18.60 vs. 8.47 months, P<0.001) than the ICI monotherapy group. The ICI/anti-angiogenic therapy group showed a significantly higher DCR (88.0% vs. 61.9%, P=0.021) and a longer PFS (8.17 vs. 3.47 months, P<0.001) and OS (19.20 vs. 8.47 months, P=0.005) than the ICI monotherapy group. Neither of the combined ICI therapy groups showed a significant increase in the incidence of AEs compared to the ICI monotherapy group. Conclusions: ICI combined with chemotherapy or anti-angiogenic therapy as second-line or later treatment demonstrated superiority over ICI monotherapy in advanced NSCLC patients without prior immunotherapy. These results provide a potentially superior treatment strategy and require verification in prospective clinical trials.

Perivascular epithelioid cell tumor of the lung: A case report and literature review.

The perivascular epithelioid cell tumor (PEComa) is a rare tumor of interstitial origin characterized by several immunological and muscle cell markers. The clear cell sugar tumor (CCST) of the lung is a type of PEComa defined by thin cell walls and high levels of glycogen in the cytoplasm. We herein reported the case of a 48-year-old male with a recurrence of lung CCST. The preoperative diagnosis of the lung mass was performed by percutaneous needle biopsy. During the thoracoscopic resection, multiple adhesions in the thoracic cavity were described. The tumor invaded the chest wall, and the boundaries between the tumor and surrounding normal tissues were unclear. The mediastinal lymph nodes were significantly enlarged. No relevant gene mutations were detected. After concomitant chemoradiotherapy, the patient's condition was stable. We also conducted a literature review and discussed the overall findings.

Abnormal Aggregation of Invasive Cancer Cells Induced by Collective Polarization and ECM-Mediated Mechanical Coupling in Coculture Systems.

Studies on pattern formation in coculture cell systems can provide insights into many physiological and pathological processes. Here, we investigate how the extracellular matrix (ECM) may influence the patterning in coculture systems. The model coculture system we use is composed of highly motile invasive breast cancer cells, initially mixed with inert nonmetastatic cells on a 2D substrate and covered with a Matrigel layer introduced to mimic ECM. We observe that the invasive cells exhibit persistent centripetal motion and yield abnormal aggregation, rather than random spreading, due to a "collective pulling" effect resulting from ECM-mediated transmission of active contractile forces generated by the polarized migration of the invasive cells along the vertical direction. The mechanism we report may open a new window for the understanding of biological processes that involve multiple types of cells.

Paradoxical effects of DNA tumor virus oncogenes on epithelium-derived tumor cell fate during tumor progression and chemotherapy response.

Epstein-Barr virus (EBV) and human papillomavirus (HPV) infection is the risk factors for nasopharyngeal carcinoma and cervical carcinoma, respectively. However, clinical analyses demonstrate that EBV or HPV is associated with improved response of patients, although underlying mechanism remains unclear. Here, we reported that the oncoproteins of DNA viruses, such as LMP1 of EBV and E7 of HPV, inhibit PERK activity in cancer cells via the interaction of the viral oncoproteins with PERK through a conserved motif. Inhibition of PERK led to increased level of reactive oxygen species (ROS) that promoted tumor and enhanced the efficacy of chemotherapy in vivo. Consistently, disruption of viral oncoprotein-PERK interactions attenuated tumor growth and chemotherapy in both cancer cells and tumor-bearing mouse models. Our findings uncovered a paradoxical effect of DNA tumor virus oncoproteins on tumors and highlighted that targeting PERK might be an attractive strategy for the treatment of NPC and cervical carcinoma.

It doesn't always pay to be fit: success landscapes.

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.

KCNJ5 Somatic Mutations in Aldosterone-Producing Adenoma Are Associated with a Greater Recovery of Arterial Stiffness.

Primary aldosteronism is the most common form of secondary hypertension and induces various cardiovascular injuries. In aldosterone-producing adenoma (APA), the impact of KCNJ5 somatic mutations on arterial stiffness excluding the influence of confounding factors is uncertain. We enrolled 213 APA patients who were scheduled to undergo adrenalectomy. KCNJ5 gene sequencing of APA was performed. After propensity score matching (PSM) for age, sex, body mass index, blood pressure, number of hypertensive medications, and hypertension duration, there were 66 patients in each group with and without KCNJ5 mutations. The mutation carriers had a higher aldosterone level and lower log transformed brachial-ankle pulse wave velocity (baPWV) than the non-carriers before PSM, but no difference in log baPWV after PSM. One year after adrenalectomy, the mutation carriers had greater decreases in log plasma aldosterone concentration, log aldosterone-renin activity ratio, and log baPWV than the non-carriers after PSM. Only the mutation carriers had a significant decrease in log baPWV after surgery both before and after PSM. KCNJ5 mutations were not correlated with baseline baPWV after PSM but were significantly correlated with ∆baPWV after surgery both before and after PSM. Conclusively, APA patients with KCNJ5 mutations had a greater regression in arterial stiffness after adrenalectomy than those without mutations.

Immune-related genes and gene sets for predicting the response to anti-programmed death 1 therapy in patients with primary or metastatic non-small cell lung cancer.

Although antibodies targeting the immune checkpoint protein programmed death-1 (PD-1) exert therapeutic effects in patients with primary or metastatic non-small cell lung cancer (NSCLC), the majority of patients exhibit partial or complete resistance to anti-PD1 treatment. Thus, the aim of the present study was to identify reliable biomarkers for predicting the response to anti-PD-1 therapy. The present study analyzed tumor specimens isolated from 24 patients (13 with primary and 11 with metastatic NSCLC) prior to treatment with approved PD1-targeting antibodies. The expression profile of 395 immune-related genes was examined using RNA immune-oncology panel sequencing. The results demonstrated that six immune-related differently expressed genes (DEGs), including HLA-F-AS1, NCF1, RORC, DMBT1, KLRF1 and IL-18, and five DEGs, including HLA-A, HLA-DPA1, TNFSF18, IFI6 and PTK7, may be used as single biomarkers for predicting the efficacy of anti-PD-1 treatment in patients with primary and with metastatic NSCLC, respectively. In addition, two DEG sets comprising either six (HLA-F-AS1, NCF1, RORC, DMBT1, KLRF and IL-18) or two (HLA-A and TNFSF18) DEGs as potential combination biomarkers for predicting the efficacy of anti-PD-1 therapy in patients with NSCLC. Patients with a calculated expression level of the DEG sets >6.501 (primary NSCLC) or >6.741 (metastatic NSCLC) may benefit from the anti-PD-1 therapy. Overall, these findings provided a basis for the identification of additional biomarkers for predicting the response to anti-PD-1 treatment.

Biological gel-based microchamber array for tumor cell proliferation and migration studies in well-controlled biochemical gradients.

Breast cancer metastasis is a complex process controlled by multiple factors, including various cell-cell interactions, cell-environment coupling, and oxygen, nutrient and drug gradients that are intimately related to the heterogeneous breast tissue structure. In this study, we constructed a high-throughput in vitro biochip system containing an array of 642 microchambers arranged in a checkerboard configuration, with each chamber embedded in a composite extracellular matrix (ECM) composed of engineered collagen and Matrigel to mimic local heterogeneous environment in vivo. In addition, a controllable complex tetragonal chemical concentration profile can be achieved by imposing chemical compounds at the four boundaries of the chip, leading to distinct local nutrient and/or drug gradients in the individual microchambers. Here, the microchamber array with composite ECM (MACECM) device aims to simulate multiple tumor cell niches composed of both breast epithelial cells (MCF-10A-GFP) and metastatic breast cancer cells (MDA-MB-231-RFP), which enables systematic studies of cell responses to a variety of biochemical conditions. The results obtained from the MACECM studies indicate that discoidin domain receptor 1 (DDR1) inhibitor 7rh and matrix metalloproteinase inhibitor batimastat, in association with epidermal growth factor (EGF) had no significant effects on the growth of MCF-10A-GFP cells, but had significant effects on DDR1 expression and the related migratory behavior of MDA-MB-231-RFP cells. The MACECM design not only enables the construction of a more realistic in vitro model for investigating cancer cell migration mechanisms but also has considerable potential for further development as a platform for next-generation high-throughput and therapeutic screening (e.g., anti-cancer drug evaluation) and personalized medicine.

Deriving time-varying cellular motility parameters via wavelet analysis.

Cell migration, which is regulated by intracellular signaling pathways (ICSP) and extracellular matrix (ECM), plays an indispensable role in many physiological and pathological process such as normal tissue development and cancer metastasis. However, there is a lack of rigorous and quantitative tools for analyzing the time-varying characteristics of cell migration in heterogeneous microenvironment, resulted from, e.g. the time-dependent local stiffness due to microstructural remodeling by migrating cells. Here, we develop a wavelet-analysis approach to derive the time-dependent motility parameters from cell migration trajectories, based on the time-varying persistent random walk model. In particular, the wavelet denoising and wavelet transform are employed to analyze migration velocities and obtain the wavelet power spectrum. Subsequently, the time-dependent motility parameters are derived via Lorentzian power spectrum. Our results based on synthetic data indicate the superiority of the method for estimating the intrinsic transient motility parameters, robust against a variety of stochastic noises. We also carry out a systematic parameter study and elaborate the effects of parameter selection on the performance of the method. Moreover, we demonstrate the utility of our approach via analyzing experimental data ofin vitrocell migration in distinct microenvironments, including the migration of MDA-MB-231 cells in confined micro-channel arrays and correlated migration of MCF-10A cells due to ECM-mediated mechanical coupling. Our analysis shows that our approach can be as a powerful tool to accurately derive the time-dependent motility parameters, and further analyze the time-dependent characteristics of cell migration regulated by complex microenvironment.

Dynamically Re-Organized Collagen Fiber Bundles Transmit Mechanical Signals and Induce Strongly Correlated Cell Migration and Self-Organization.

Correlated cell migration in fibrous extracellular matrix (ECM) is important in many biological processes. During migration, cells can remodel the ECM, leading to the formation of mesoscale structures such as fiber bundles. However, how such mesoscale structures regulate correlated single-cells migration remains to be elucidated. Here, using a quasi-3D in vitro model, we investigate how collagen fiber bundles are dynamically re-organized and guide cell migration. By combining laser ablation technique with 3D tracking and active-particle simulations, we definitively show that only the re-organized fiber bundles that carry significant tensile forces can guide strongly correlated cell migration, providing for the first time a direct experimental evidence supporting that matrix-transmitted long-range forces can regulate cell migration and self-organization. This force regulation mechanism can provide new insights for studies on cellular dynamics, fabrication or selection of biomedical materials in tissue repairing, and many other biomedical applications.

Novel cytosensor for accurate detection of circulating tumor cells based on a dual-recognition strategy and BSA@Ag@Ir metallic-organic nanoclusters.

Herein, based on a dual-recognition strategy and BSA@Ag@Ir metallic-organic nanoclusters (BSA@Ag@Ir MONs), a highly specific and sensitive cytosensor was developed for detecting circulating tumor cells (CTCs). To amplify current signal, novel BSA@Ag@Ir MONs with outstanding catalytic activity and huge specific surface area were synthesized, and conjugated with hairpin DNA strands as signal probes. Orion carbon black 40 (Ocb40)//AuNPs were firstly used to modify electrode to increase its conductivity and surface area. Moreover, the dual recognition strategy based on DNA proximity effect was designed to improve the specificity of cytosensor. When two capture probes respectively bound to two adjacent membrane markers of target cells, the probes could form the associative toehold through the proximity effect to capture the signal probes. Only CTCs simultaneously expressing two membrane markers could be captured and generate current responses. The developed cytosensor could detect CTCs in the range of 3 - 3 × 106 cells mL-1 with a detection limit of 1 cell mL-1. Notably, the cytosensor could accurately identify CTCs even in whole blood. Therefore, this cytosensor has great potential for application in biological science, biomedical engineering and personalized medicine.