Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images.

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

Prognostic significance of collagen signatures in pancreatic ductal adenocarcinoma obtained from second-harmonic generation imaging.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) ranks among the deadliest types of cancer, and it will be meaningful to search for new biomarkers with prognostic value to help clinicians tailor therapeutic strategies. METHODS: Here we tried to use an advanced optical imaging technique, multiphoton microscopy (MPM) combining second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) imaging, for the label-free detection of PDAC tissues from a cohort of 149 patients. An automated image processing method was used to extract collagen features from SHG images and the Kaplan-Meier survival analysis and Cox proportional hazards regression were used to assess the prognostic value of collagen signatures. RESULTS: SHG images clearly show the different characteristics of collagen fibers in tumor microenvironment. We gained eight collagen morphological features, and a Feature-score was derived for each patient by the combination of these features using ridge regression. Statistical analyses reveal that Feature-score is an independent factor, and can predict the overall survival of PDAC patients as well as provide well risk stratification. CONCLUSIONS: SHG imaging technique can potentially be a tool for the accurate diagnosis of PDAC, and this optical biomarker (Feature-score) may help clinicians make more approximate treatment decisions.

Exploration of the relationship between tumor-infiltrating lymphocyte score and histological grade in breast cancer.

BACKGROUND: The histological grade is an important factor in the prognosis of invasive breast cancer and is vital to accurately identify the histological grade and reclassify of Grade2 status in breast cancer patients. METHODS: In this study, data were collected from 556 invasive breast cancer patients, and then randomly divided into training cohort (n = 335) and validation cohort (n = 221). All patients were divided into actual low risk group (Grade1) and high risk group (Grade2/3) based on traditional histological grade, and tumor-infiltrating lymphocyte score (TILs-score) obtained from multiphoton images, and the TILs assessment method proposed by International Immuno-Oncology Biomarker Working Group (TILs-WG) were also used to differentiate between high risk group and low risk group of histological grade in patients with invasive breast cancer. Furthermore, TILs-score was used to reclassify Grade2 (G2) into G2 /Low risk and G2/High risk. The coefficients for each TILs in the training cohort were retrieved using ridge regression and TILs-score was created based on the coefficients of the three kinds of TILs. RESULTS: Statistical analysis shows that TILs-score is significantly correlated with histological grade, and is an independent predictor of histological grade (odds ratio [OR], 2.548; 95%CI, 1.648-3.941; P < 0.0001), but TILs-WG is not an independent predictive factor for grade (P > 0.05 in the univariate analysis). Moreover, the risk of G2/High risk group is higher than that of G2/Low risk group, and the survival rate of patients with G2/Low risk is similar to that of Grade1, while the survival rate of patients with G2/High risk is even worse than that of patients with G3. CONCLUSION: Our results suggest that TILs-score can be used to predict the histological grade of breast cancer and potentially to guide the therapeutic management of breast cancer patients.

Research progress on the role of cationic amino acid transporter (CAT) family members in malignant tumors and immune microenvironment.

Amino acids are essential for the survival of all living organisms and living cells. Amino acid transporters mediate the transport and absorption of amino acids, and the dysfunction of these proteins can induce human diseases. Cationic amino acid transporters (CAT family, SLC7A1-4, and SLC7A14) are considered to be a group of transmembrane transporters, of which SLC7A1-3 are essential for arginine transport in mammals. Numerous studies have shown that CAT family-mediated arginine transport is involved in signal crosstalk between malignant tumor cells and immune cells, especially T cells. The modulation of extracellular arginine concentration has entered a number of clinical trials and achieved certain therapeutic effects. Here, we review the role of CAT family on tumor cells and immune infiltrating cells in malignant tumors and explore the therapeutic strategies to interfere with extracellular arginine concentration, to elaborate its application prospects. CAT family members may be used as biomarkers for certain cancer entities and might be included in new ideas for immunotherapy of malignant tumors.

Analytical solution of the transient temperature profile in gain medium of passively Q-switched microchip laser.

The transient temperature evolution in the gain medium of a continuous wave (CW) end-pumped passively Q-switched microchip (PQSM) laser is analyzed. By approximating the time-dependent population inversion density as a sawtooth function of time and treating the time-dependent pump absorption of a CW end-pumped PQSM laser as the superposition of an infinite series of short pumping pulses, the analytical expressions of transient temperature evolution and distribution in the gain medium for four- and three-level laser systems, respectively, are given. These analytical solutions are applied to evaluate the transient temperature evolution and distribution in the gain medium of CW end-pumped PQSM Nd:YAG and Yb:YAG lasers.

High expression of SLC7A1 in high-grade serous ovarian cancer promotes tumor progression and is involved in MAPK/ERK pathway and EMT.

Our previous studies have shown that upregulation of SLC7A1 in epithelial ovarian cancer (EOC) tumor cells significantly increases cancer cell proliferation, migration, and cisplatin resistance; however, the molecular mechanism by which SLC7A1 functions in EOC remains unknown. In later studies, we found that SLC7A1 is also highly expressed in the interstitial portion of high-grade serous ovarian cancer (HGSOC), but the significance of this high expression in the interstitial remains unclear. Here, we showed the Interstitial high expression of SLC7A1 in HGSOC by immunohistochemistry. SLC7A1 enriched in cancer-associated fibroblasts (CAFs) was upregulated by TGF-ß1. Transwell assay, scratch assay, cck8 assay and cell adhesion assay showed that SLC7A1 highly expressed in CAFs promoted tumor cells invasion, migration and metastasis in vitro. The effect of SLC7A1 on MAPK and EMT pathway proteins in ovarian cancer (OC) was verified by RNA sequencing and western blotting. Overexpression of SLC7A1 in OC is involved in MAPK/ ERK pathway and EMT. In general, in HGSOC, CAFs overexpressing SLC7A1 supported the migration and invasion of tumor cells; SLC7A1 is highly expressed in ovarian cancer and is involved in ERK phosphorylation and EMT signaling in MAPK signaling pathway. This suggests that SLC7A1 may be a potential therapeutic target for OC metastasis.

Injectable bio-multifunctional hyaluronic acid-based hydrogels loaded with poly ADP-ribose polymerase inhibitors for ovarian cancer therapy.

The recent use of PARP inhibitors (PARPi) in the maintenance treatment of ovarian tumor has significantly improved the survival rates of cancer patients. However, the current oral administration of PARP inhibitors fails to realize optimal therapeutic effects due to the low bioavailability in cancerous tissues, and often leads to a range of systemic adverse effects including hematologic toxicities, digestive system reactions, and neurotoxicities. Therefore, the demand for an advanced drug delivery system that can ensure effective drug administration while minimizing these unfavorable reactions is pressing. Injectable hydrogel emerges as a promising solution for local administration with the capability of sustainable drug release. In this study, we developed an injectable hydrogel made from aminated hyaluronic acid and aldehyde-functionalized pluronic127 via Schiff base reaction. This hydrogel exhibits excellent injectability with short gelation time and remarkable self-healing ability, and is applied to load niraparib. The drug-loaded hydrogel (HP@Nir hydrogel) releases drugs sustainably as tested in vitro as well as displays significant anti-proliferation and anti-migratory properties on human epithelial ovarian cancer cell line. Notably, HP@Nir hydrogel effectively suppresses the growth of ovarian cancer, without significant adverse reactions as demonstrated in animal studies. Additionally, the developed hydrogel is gradually degraded in vivo for around 20 d, while maintaining good biocompatibility. Overall, the injectable hydrogel loaded with niraparib provides a secure and efficient strategy for the treatment and management of ovarian cancer.

Prognostic significance of collagen signatures at breast tumor boundary obtained by combining multiphoton imaging and imaging analysis.

PURPOSE: Collagen features in breast tumor microenvironment is closely associated with the prognosis of patients. We aim to explore the prognostic significance of collagen features at breast tumor border by combining multiphoton imaging and imaging analysis. METHODS: We used multiphoton microscopy (MPM) to label-freely image human breast tumor samples and then constructed an automatic classification model based on deep learning to identify collagen signatures from multiphoton images. We recognized three kinds of collagen signatures at tumor boundary (CSTB I-III) in a small-scale, and furthermore obtained a CSTB score for each patient based on the combined CSTB I-III by using the ridge regression analysis. The prognostic performance of CSTB score is assessed by the area under the receiver operating characteristic curve (AUC), Cox proportional hazard regression analysis, as well as Kaplan-Meier survival analysis. RESULTS: As an independent prognostic factor, statistical results reveal that the prognostic performance of CSTB score is better than that of the clinical model combining three independent prognostic indicators, molecular subtype, tumor size, and lymph nodal metastasis (AUC, Training dataset: 0.773 vs. 0.749; External validation: 0.753 vs. 0.724; HR, Training dataset: 4.18 vs. 3.92; External validation: 4.98 vs. 4.16), and as an auxiliary indicator, it can greatly improve the accuracy of prognostic prediction. And furthermore, a nomogram combining the CSTB score with the clinical model is established for prognosis prediction and clinical decision making. CONCLUSION: This standardized and automated imaging prognosticator may convince pathologists to adopt it as a prognostic factor, thereby customizing more effective treatment plans for patients.

Combining the guidelines and multiphoton imaging methods to improve the prognostic value of tumor-infiltrating lymphocytes in breast cancer.

Multiphoton microscopy (MPM) was introduced to label-freely obtain tumor-infiltrating lymphocytes (TILs) images from a total of 611 patients, and the prognostic value of TILs in breast cancer was assessed by the MPM method (TILs-MPM) and guidelines method proposed by the International Immuno-Oncology Biomarker Working Group (TILs-WG), respectively. Moreover, the clinical (CLI) model, TILs-WG + TILs-MPM model, and full model (CLI + TILs-WG + TILs-MPM) were developed to investigate the prognostic value of TILs. The results show that TILs-WG performs better in estrogen receptor (ER)-negative subgroup, and TILs-MPM is comparable with TILs-WG in the ER-negative subgroup, but has the best performance in the ER-positive subgroup. Furthermore, the TILs-WG + TILs-MPM model can significantly improve the prognostic power compared with the TILs-WG model, and the full model has excellent performance, with high area under the curve (AUC) and hazard ratio (HR) in both ER-positive, ER-negative subgroups, and the complete cohort. Our results suggest that the combination of TILs-WG with TILs-MPM model can greatly improve the prognostic value of TILs.

Collagen signature as a novel biomarker to predict axillary lymph node metastasis in breast cancer using multiphoton microscopy.

Accurate identification of axillary lymph node (ALN) status is crucial for tumor staging procedure and decision making. This retrospective study of 898 participants from two institutions was conducted. The aim of this study is to evaluate the diagnostic performance of clinical parameters combined with collagen signatures (tumor-associated collagen signatures [TACS] and the TACS corresponding microscopic features [TCMF]) in predicting the probability of ALN metastasis in patients with breast cancer. These findings suggest that TACS and TCMF in the breast tumor microenvironment are both novel and independent biomarkers for the estimation of ALN metastasis. The nomogram based on independent clinical parameters combined with TACS and TCMF yields good diagnostic performance in predicting ALN status.