Recent advances in understanding tumor stroma-mediated chemoresistance in breast cancer

The Transcriptomic Landscapes of Appendiceal Primary and Metastatic Tumors are Distinct

BACKGROUND

Improved understanding about the pathobiology of appendiceal cancers (AC) and resulting metastasis is required for the development of novel treatments. The tumor microenvironment in AC is heterogeneous and incompletely characterized. The objective of this study was to leverage spatial high-plex technology to evaluate the transcriptomic landscape of epithelial and stromal cells in primary AC tumors, adjacent normal appendix, and corresponding peritoneal metastasis.

METHODS

A tissue microarray (TMA) containing cores from 14 unique patients having matched primary tumor, adjacent normal appendix, and peritoneal metastases was analyzed with digital spatial profiling (NanoString, GeoMx) using pancytokeratin (PCK) to delineate stroma (PCK-) from epithelium (PCK+). Then RNA sequencing was performed to measure transcript abundance separately within the stromal and epithelial compartments.

RESULTS

Transcriptomic analysis demonstrated differences between tumor and stromal compartments in both primary tumor and metastatic sites. Primary and metastatic tumor stroma (PCK-) demonstrated greater expression of ribosomal biogenesis pathways than normal appendiceal tissue. Primary and metastatic tumors were generally similar with respect to transcription. However, within the epithelial compartment (PCK+), peritoneal metastases exhibited upregulated cytoskeletal and collagen metabolism pathways/genes compared with primary tumor.

CONCLUSIONS

The study data indicated that although appendiceal peritoneal disease is transcriptionally similar to the primary tumor, potentially important distinctions exist between metastatic and primary disease. Differences appear to be driven predominantly by changes in collagen metabolism at the peritoneal site. A better understanding of both tumor and stromal compartments of metastatic disease will be essential to improving therapeutic options, specifically systemic treatment, which is characteristically ineffective.

Tumor-targeted nanosystem with hypoxia inducible factor 1α inhibition for synergistic chemo-photodynamic therapy against hypoxic tumor

Photodynamic therapy (PDT) holds an essential role in the therapy of tumors. However, PDT consumes tissue oxygen and diminishes its own efficacy by inducing tumor hypoxia through the HIF-1α/VEGF pathway. Therefore, overcoming the photodynamic exacerbation of tumor hypoxia could reverse tumor microenvironment and enhance PDT. In this study, BC-PDA/HA loaded with bufalin (BUF) and chlorin e6 (Ce6) were developed for synergistic cancer chemo-photodynamic therapy. BC-PDA/HA, modified with hyaluronic acid (HA), exhibited CD44-targeting capability and enhanced cellular uptake in vitro. Moreover, in the acidic tumor microenvironment, BC-PDA/HA could on-demand release Ce6 and BUF, inducing PDT upon 660 nm irradiation. Simultaneously, the released BUF not only served as a chemotherapeutic agent, but also inhibited HIF-1α expression, reversing the PDT-induced tumor hypoxia. Furthermore, compared to free Ce6, BC-PDA/HA enhanced tumor accumulation and retention in vivo. BC-PDA/HA could also effectively improve hypoxia and inhibit tumor angiogenesis to enhance PDT efficacy, demonstrating synergistic chemo-PDT activity. In conclusion, this work provided a novel strategy for synergistic chemo-photodynamic therapy against breast cancer.

Proteogenomic characterization of molecular and cellular targets for treatment-resistant subtypes in locally advanced cervical cancers

We report proteogenomic analysis of locally advanced cervical cancer (LACC). Exome-seq data revealed predominant alterations of keratinization-TP53 regulation and O-glycosylation-TP53 regulation axes in squamous and adeno-LACC, respectively, compared to in early-stage cervical cancer. Integrated clustering of mRNA, protein, and phosphorylation data identified six subtypes (Sub1-6) of LACC among which Sub3, 5, and 6 showed the treatment-resistant nature with poor local recurrence-free survival. Elevated immune and extracellular matrix (ECM) activation mediated by activated stroma (PDGFD and CXCL1high fibroblasts) characterized the immune-hot Sub3 enriched with MUC5AChigh epithelial cells (ECs). Increased epithelial-mesenchymal-transition (EMT) and ECM remodeling characterized the immune-cold squamous Sub5 enriched with PGK1 and CXCL10high ECs. We further demonstrated that CIC mutations could trigger EMT activation by upregulating ETV4, and the elevation of the immune checkpoint PVR and neutrophil-like myeloid-derived suppressive cells (FCN1 and FCGR3Bhigh macrophages) could cause suppression of T-cell activation in Sub5. Increased O-linked glycosylation of mucin characterized adeno-LACC Sub6 enriched with MUC5AChigh ECs. These results provide a battery of somatic mutations, cellular pathways, and cellular players that can be used to predict treatment-resistant LACC subtypes and can serve as potential therapeutic targets for these LACC subtypes.

Application of an Integrated Single-Cell and Three-Dimensional Spheroid Culture Platform for Investigating Drug Resistance Heterogeneity and Epithelial-Mesenchymal Transition (EMT) in Lung Cancer Subclones

Lung cancer is a leading cause of cancer-related mortality worldwide, largely due to its heterogeneity and intrinsic drug resistance. Malignant pleural effusions (MPEs) provide diverse tumor cell populations ideal for studying these complexities. Although chemotherapy and targeted therapies can be initially effective, subpopulations of cancer cells with phenotypic plasticity often survive treatment, eventually developing resistance. Here, we integrated single-cell isolation and three-dimensional (3D) spheroid culture to dissect subclonal heterogeneity and drug responses, aiming to inform precision medicine approaches. Using A549 lung cancer cells, we established a cisplatin-resistant line and isolated three resistant subclones (Holoclone, Meroclone, Paraclone) via single-cell sorting. In 3D spheroids, Docetaxel and Alimta displayed higher IC50 values than in 2D cultures, suggesting that 3D models better reflect clinical dosing. Additionally, MPE-derived Holoclone and Paraclone subclones exhibited distinct sensitivities to Giotrif and Capmatinib, revealing their heterogeneous drug responses. Molecular analyses confirmed elevated ABCB1, ABCG2, cancer stem cell (CSC) markers (OCT4, SOX2, CD44, CD133), and epithelial-mesenchymal transition (EMT) markers (E-cadherin downregulation, increased Vimentin, N-cadherin, Twist) in resistant subclones, correlating with enhanced migration and invasion. This integrated approach clarifies the interplay between heterogeneity, CSC/EMT phenotypes, and drug resistance, providing a valuable tool for predicting therapeutic responses and guiding personalized, combination-based lung cancer treatments.

Nomogram based on dual-energy computed tomography to predict the response to induction chemotherapy in patients with nasopharyngeal carcinoma: a two-center study

BACKGROUND

Previous studies utilizing dual-energy CT (DECT) for evaluating treatment efficacy in nasopharyngeal cancinoma (NPC) are limited. This study aimed to investigate whether the parameters from DECT can predict the response to induction chemotherapy in NPC patients in two centers.

METHODS

This two-center retrospective study included patients diagnosed with NPC who underwent contrast-enhanced DECT between March 2019 and November 2023. The clinical and DECT-derived parameters of tumor lesions were calculated to predict the response. We employed univariate and multivariate analysis to identify significant factors. Subsequently, the clinical, DECT, and clinical-DECT nomogram models were developed using independent predictors in the training cohort and validated in the test cohort. Receiver operating characteristic analysis was performed to evaluate the models' performance.

RESULTS

A total of 321 patients were included in the study, predominantly male [247 (76.9%)] with an average age of 52.04 ± 10.87 years. The training cohort (Center 1) comprised 252 patients, while the test cohort (Center 2) comprised 69 patients. Of these, 233 out of 321 patients (72.6%) were responders to induction chemotherapy. The clinical-DECT nomogram showed an AUC of 0.805 (95% CI, 0.688-0.906), outperforming both the DECT model (Extracellular volume fraction [ECVf]) (AUC, 0.706 [95% CI, 0.571-0.825]) and the clinical model (Ki67) (AUC, 0.693 [95% CI, 0.580-0.806]) in the test cohort.

CONCLUSIONS

Ki67 and ECVf emerged as independent predictive factors for response to induction chemotherapy in NPC patients. The proposed nomogram, incorporating ECVf, demonstrated accurate prediction of treatment response.

Omega-3 fatty acids: molecular weapons against chemoresistance in breast cancer

Breast cancer is the most commonly diagnosed type of cancer and the leading cause of cancer-related death in women worldwide. Highly targeted therapies have been developed for different subtypes of breast cancer, including hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-positive breast cancer. However, triple-negative breast cancer (TNBC) and metastatic breast cancer disease are primarily treated with chemotherapy, which improves disease-free and overall survival, but does not offer a curative solution for these aggressive forms of breast cancer. Moreover, the development of chemoresistance is a major cause of therapeutic failure in this neoplasia, leading to disease relapse and patient death. In addition, chemotherapy's adverse side effects may substantially worsen health-related quality of life. Therefore, to improve the outcome of patients with breast cancer who are undergoing chemotherapy, several therapeutic options are under investigation, including the combination of chemotherapeutic drugs with natural compounds. Omega-3 (ω-3) polyunsaturated fatty acids (PUFAs), including docosahexaenoic and eicosapentaenoic acids, have drawn attention for their antitumoral properties and their preventive activities against chemotherapy-induced toxicities in breast cancer. A literature review was conducted on PubMed using keywords related to breast cancer, omega-3, chemoresistance, and chemotherapy. This review aims to provide an overview of the molecular mechanisms driving breast cancer chemoresistance, focusing on the role of ω-3 PUFAs in these recognized cellular paths and presenting current findings on the effects of ω-3 PUFAs combined with chemotherapeutic drugs in breast cancer management.

Embedded Bioprinting of Breast Cancer-Adipose Composite Tissue Model for Patient-Specific Paracrine Interaction Analysis

The interaction between breast cancer and stromal tissues varies significantly from patient to patient, greatly impacting cancer prognosis. However, conventional models struggle to accurately replicate these patient-specific interactions. Herein, a novel breast cancer-adipose composite tissue model capable of precisely adjusting the inter-tissue interaction is developed. The composite tissue model is produced through precise embedded bioprinting of breast-cancer spheroids and live-adipose-tissue ink. This model possessed not only precisely patterned cancer spheroids but also well-preserved intrinsic extracellular matrices (ECMs) and heterogeneous cell populations of adipose tissue (AT). Evaluation results successfully demonstrated that the bioprinted composite model can precisely regulate adipokine secretion, drug resistance, and cancer-cell invasion characteristics by adjusting the distance between the cancer spheroids and adipose tissue. The utility of the model is validated using adipokine-targeted therapies (C-compound/SC600125 (SC), AG 490 (AG), and Metformin (MET)). Interestingly, the inhibition of cancer cell proliferation and invasion by these adipokine-targeted drugs nearly doubled as the tissue distance decreased. This suggests that the efficacy of the drugs can be precisely evaluated using the new model. These findings underscore the potential of the developed composite model to replicate patient-specific crosstalk, thereby offering a promising platform for the sophisticated evaluation of various breast-cancer therapies.

α-Parvin Expression in Breast Cancer Tissues: Correlation with Clinical Parameters and Prognostic Significance

Stromal cells play a critical role in the tumor microenvironment of breast cancer (BC), as they are recruited by tumor cells and regulate the metastatic spread. Though high expression of α-parvin, a member of the parvin family of actin-binding proteins, is reported to be associated with a poor prognosis and metastasis in several cancers, its role in carcinogenesis has not been thoroughly explored. Therefore, we aimed to examine the expression of α-parvin in BC patients by compartmentalizing and quantifying tissues to determine whether α-parvin can be a potential therapeutic target. We performed immunohistochemical (IHC) staining of α-parvin in BC tissues, and the IHC scores were calculated in the overall tissue, stroma, and epithelium using image analysis software. The expression of α-parvin was significantly higher in BC tissues (p = 0.0002) and BC stroma (p < 0.0001) than in normal tissues. Furthermore, all α-parvin scores were significantly positively correlated with the proliferation marker Ki67. The overall and stroma scores are associated with the tumor, (lymph) node, and metastasis (TNM) classification, stage, and grade. These results suggest that high expression of α-parvin in stroma is associated with BCs and might be a new predictive marker for diagnosing BC.

The reactive stroma response regulates the immune landscape in prostate cancer

Prostate cancer remains the most commonly diagnosed and the second leading cause of cancer-related deaths in men in the United States. The neoplastic transformation of prostate epithelia, concomitant with modulations in the stromal compartment, known as reactive stromal response, is critical for the growth, development, and progression of prostate cancer. Reactive stroma typifies an emergent response to disrupted tissue homeostasis commonly observed in wound repair and pathological conditions such as cancer. Despite the significance of reactive stroma in prostate cancer pathobiology, our understanding of the ontogeny, phenotypic and functional heterogeneity, and reactive stromal regulation of the immune microenvironment in prostate cancer remains limited. Traditionally characterized to have an immunologically "cold" tumor microenvironment, prostate cancer presents significant challenges for advancing immunotherapy compared to other solid tumors. This review explores the detrimental role of reactive stroma in prostate cancer, particularly its immunomodulatory function. Understanding the molecular characteristics and dynamic transcriptional program of the reactive stromal populations in tandem with tumor progression could offer insights into enhancing immunotherapy efficacy against prostate cancer.

Breast cancer drug resistance: Decoding the roles of Hippo pathway crosstalk

The most significant factors that lead to cancer-related death in breast cancer (BC) patients include drug resistance, migration, invasion, and metastasis. Several signaling pathways are involved in the development of BC. The different types of BC are initially sensitive to chemotherapy, and drug resistance can occur through multiple molecular mechanisms. Regardless of developing targeted Therapy, due to the heterogenic nature and complexity of drug resistance, it is a major clinical challenge with the low survival rate in BC patients. The deregulation of several signaling pathways, particularly the Hippo pathway (HP), is one of the most recent findings about the molecular mechanisms of drug resistance in BC, which are summarized in this review. Given that HP is one of the recent cancer research hotspots, this review focuses on its implication in BC drug resistance. Unraveling the different molecular basis of HP through its crosstalk with other signaling pathways, and determining the effectiveness of HP inhibitors can provide new insights into possible therapeutic strategies for overcoming chemoresistance in BC.

Stromal cell-expressed malignant gene patterns contribute to the progression of squamous cell carcinomas across different sites

Background

Squamous cell carcinomas (SCCs) across different anatomical locations possess common molecular features. Recent studies showed that stromal cells may contribute to tumor progression and metastasis of SCCs. Limited by current sequencing technology and analysis methods, it has been difficult to combine stroma expression profiles with a large number of clinical information.

Methods

With the help of transfer learning on the cell line, single-cell, and bulk tumor sequencing data, we identified and validated 2 malignant gene patterns (V1 and V5) expressed by stromal cells of SCCs from head and neck (HNSCC), lung (LUSC), cervix (CESC), esophagus, and breast.

Results

Pattern V5 reflected a novel malignant feature that explained the mixed signals of HNSCC molecular subtypes. Higher expression of pattern V5 was related to shorter PFI with gender and cancer-type specificity. The other stromal gene pattern V1 was associated with poor PFI in patients after surgery in all the three squamous cancer types (HNSCC p = 0.0055, LUSC p = 0.0292, CESC p = 0.0451). Cancer-associated fibroblasts could induce HNSCC cancer cells to express pattern V1. Adjuvant radiotherapy may weaken the effect of high V1 on recurrence and metastasis, depending on the tumor radiosensitivity.

Conclusion

Considering the prognostic value of stromal gene patterns and its universality, we suggest that the genetic subtype classification of SCCs may be improved to a new system that integrates both malignant and non-malignant components.

A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories.

Therapeutic implications of signaling pathways and tumor microenvironment interactions in esophageal cancer

Esophageal cancer (EC) is significantly influenced by the tumor microenvironment (TME) and altered signaling pathways. Downregulating these pathways in EC is essential for suppressing tumor development, preventing metastasis, and enhancing therapeutic outcomes. This approach can increase tumor sensitivity to treatments, enhance patient outcomes, and inhibit cancer cell proliferation and spread. The TME, comprising cellular and non-cellular elements surrounding the tumor, significantly influences EC's development, course, and treatment responsiveness. Understanding the complex relationships within the TME is crucial for developing successful EC treatments. Immunotherapy is a vital TME treatment for EC. However, the heterogeneity within the TME limits the application of anticancer drugs outside clinical settings. Therefore, identifying reliable microenvironmental biomarkers that can detect therapeutic responses before initiating therapy is crucial. Combining approaches focusing on EC signaling pathways with TME can enhance treatment outcomes. This integrated strategy aims to interfere with essential signaling pathways promoting cancer spread while disrupting factors encouraging tumor development. Unraveling aberrant signaling pathways and TME components can lead to more focused and efficient treatment approaches, identifying specific cellular targets for treatments. Targeting the TME and signaling pathways may reduce metastasis risk by interfering with mechanisms facilitating cancer cell invasion and dissemination. In conclusion, this integrative strategy has significant potential for improving patient outcomes and advancing EC research and therapy. This review discusses the altered signaling pathways and TME in EC, focusing on potential future therapeutics.

Integrative analysis identifies molecular features of fibroblast and the significance of fibrosis on neoadjuvant chemotherapy response in breast cancer

BACKGROUND

The molecular features of fibroblasts and the role of fibrosis in neoadjuvant chemotherapy (NAC) response and breast cancer (BRCA) prognosis remain unclear. Therefore, this study aimed to investigate the impact of interstitial fibrosis on the response and prognosis of patients with BRCA undergoing NAC treatment.

MATERIALS AND METHODS

The molecular characteristics of pathologic complete response (pCR) and non-pCR (npCR) in patients with BRCA were analyzed using multiomics analysis. A clinical cohort was collected to investigate the predictive value of fibrosis in patients with BRCA.

RESULTS

Fibrosis-related signaling pathways were significantly upregulated in patients with npCR. npCR may be associated with distinct and highly active fibroblast subtypes. Patients with high fibrosis had lower pCR rates. The fibrosis-dependent nomogram for pCR showed efficient predictive ability [training set: area under the curve [AUC]=0.871, validation set: AUC=0.792]. Patients with low fibrosis had a significantly better prognosis than those with high fibrosis, and those with a high fibrotic focus index had significantly shorter overall and recurrence-free survival. Therefore, fibrosis can be used to predict pCR. Our findings provide a basis for decision-making in the treatment of BRCA.

CONCLUSIONS

npCR is associated with a distinct and highly active fibroblast subtype. Furthermore, patients with high fibrosis have lower pCR rates and shorter long-term survival. Therefore, fibrosis can predict pCR. A nomogram that includes fibrosis can provide a basis for decision-making in the treatment of BRCA.

Polymeric nanofiber leveraged co-delivery of anti-stromal PAK1 inhibitor and paclitaxel enhances therapeutic effects in stroma-rich 3D spheroid models

The role of tumor stroma in solid tumors has been widely recognized in cancer progression, metastasis and chemoresistance. Cancer-associated fibroblasts (CAFs) play a crucial role in matrix remodeling and promoting cancer cell stemness and resistance via reciprocal crosstalk. Residual tumor tissue after surgical removal as well as unresectable tumors face therapeutic challenges to achieve curable outcome. In this study, we propose to develop a dual delivery approach by combining p21-activated kinase 1 (PAK1) inhibitor (FRAX597) to inhibit tumor stroma and chemotherapeutic agent paclitaxel (PTX) to kill cancer cells using electrospun nanofibers. First, the role of the PAK1 pathway was established in CAF differentiation, migration and contraction using relevant in vitro models. Second, polycaprolactone polymer-based nanofibers were fabricated using a uniaxial electrospinning technique to incorporate FRAX597 and/or PTX, which showed a uniform texture and a prolonged release of both drugs for 16 days. To test nanofibers, stroma-rich 3D heterospheroid models were set up which showed high resistance to PTX nanofibers compared to stroma-free homospheroids. Interestingly, nanofibers containing PTX and FRAX597 showed strong anti-tumor effects on heterospheroids by reducing the growth and viability by > 90 % compared to either of single drug-loaded nanofibers. These effects were reflected by reduced intra-spheroidal expression levels of collagen 1 and α-smooth muscle actin (α-SMA). Overall, this study provides a new therapeutic strategy to inhibit the tumor stroma using PAK1 inhibitor and thereby enhance the efficacy of chemotherapy using nanofibers as a local delivery system for unresectable or residual tumor. Use of 3D models to evaluate nanofibers highlights these models as advanced in vitro tools to study the effect of controlled release local drug delivery systems before animal studies.

Epigenetic deregulation in breast cancer microenvironment: Implications for tumor progression and therapeutic strategies

Breast cancer comprises a substantial proportion of cancer diagnoses in women and is a primary cause of cancer-related mortality. While hormone-responsive cases generally have a favorable prognosis, the aggressive nature of triple-negative breast cancer presents challenges, with intrinsic resistance to established treatments being a persistent issue. The complexity intensifies with the emergence of acquired resistance, further complicating the management of breast cancer. Epigenetic changes, encompassing DNA methylation, histone and RNA modifications, and non-coding RNAs, are acknowledged as crucial contributors to the heterogeneity of breast cancer. The unique epigenetic landscape harbored by each cellular component within the tumor microenvironment (TME) adds great diversity to the intricate regulations which influence therapeutic responses. The TME, a sophisticated ecosystem of cellular and non-cellular elements interacting with tumor cells, establishes an immunosuppressive microenvironment and fuels processes such as tumor growth, angiogenesis, and extracellular matrix remodeling. These factors contribute to challenging conditions in cancer treatment by fostering a hypoxic environment, inducing metabolic stress, and creating physical barriers to drug delivery. This article delves into the complex connections between breast cancer treatment response, underlying epigenetic changes, and vital interactions within the TME. To restore sensitivity to treatment, it emphasizes the need for combination therapies considering epigenetic changes specific to individual members of the TME. Recognizing the pivotal role of epigenetics in drug resistance and comprehending the specificities of breast TME is essential for devising more effective therapeutic strategies. The development of reliable biomarkers for patient stratification will facilitate tailored and precise treatment approaches.

Comparing extracellular volume fraction with apparent diffusion coefficient for the characterization of breast tumors

PURPOSE

To investigate the feasibility of dual-energy CT (DECT)-derived extracellular volume (ECV) fraction for characterization of breast tumors, compared to apparent diffusion coefficient (ADC) and validated against histopathological findings.

MATERIAL AND METHODS

The ECV fraction and ADC were prospectively assessed in patients with breast tumors using chest DECT and breast MRI. The diagnostic performance of ECV fraction and ADC was accessed in predicting breast histopathological subtypes and pathological complete response (pCR) status. Histopathological sections were analyzed by digital image analysis. Pearson's correlation analysis was used to correlate between DECT and histopathological ECV fractions.

RESULTS

This study included 271 patients, with 314 breast lesions (61 benign and 253 malignant). The ECV fraction and ADC showed comparable area under the curve (AUC) for distinguishing benign from malignant lesions (p = 0.123) and invasive carcinoma from ductal carcinoma in situ (p = 0.115). There were significant differences in ECV fraction between different hormone receptors and Ki67 states (p = 0.001 ∼ 0.014), while ADC values only differed among various Ki67 states (p < 0.001). The ECV fraction was lower (p = 0.007), ADC was higher (p = 0.013) in pCR than in non-pCR group, with an AUC of 0.748 and 0.730 (p = 0.887), respectively. There was a positive correlation between DECT and histopathological ECV fractions (r = 0.615, p < 0.01).

CONCLUSIONS

Routine chest DECT-derived ECV fraction is a viable quantitative imaging biomarker for predicting histopathological subtypes and pCR in patient with breast tumors, and correlated well with histopathology finding.

Clinicopathological features and prognostic analysis of HER2 low and fibrotic focus in HER2-negative breast cancer

OBJECTIVE

The aim of this study is to evaluate the clinicopathological features and prognostic significance of HER2 low, fibrotic focus (FF), and tumor-infiltrating lymphocytes (TILs) in patients with HER2-negative breast cancer.

METHODS

We retrospectively reviewed the data of 293 patients with HER2-negative, stage I-II, invasive breast cancer of non-specific types. The HER2-negative cases were classified into HER2 low and HER2 0. Digital analysis of hematoxylin-eosin stained whole slide images was used to evaluate the FF expression. TILs were also evaluated using the Whole Slide Image. Furthermore, the association between HER2 low, FF, and TILs as well as their prognostic significance were analyzed.

RESULTS

The study cohort included 178 cases (60.8%) with HER2 low and 115 cases (39.2%) with HER2 0. Older age, lower Nottingham histological grade (NHG), estrogen receptor (ER) positivity, progesterone receptor (PR) positivity, and hormone receptor (HR) positivity were all associated with HER2 low. FF was correlated with older age, intermediate and low NHG, vascular invasion, HR positivity, HER2 low status, high Ki67 expression, and low TILs. Univariate survival analysis showed that FF was significantly associated with shorter progression-free survival (PFS). Stratified analysis indicated that in the HR-negative and HR-positive groups, HER2 status and TILs did not affect PFS. DFS was longer in patients without FF compared to those with FF in the HR-positive (hazard ratio [HR] = 0.313) and HER2 low (HR = 0.272) groups. DFS was also significantly longer in patients without FF compared to those with FF in the HR-negative (HR = 0.069) and HER2 0 groups (HR = 0.129).

CONCLUSION

The results indicated that the HER2 low status and the TILs expression did not impact prognosis. However, patients with FF exhibited distinct biological characteristics and prognostic significance, particularly in the HR-negative and HER2 0 groups. This provides a rationale for accurate diagnosis and treatment of HER2-negative breast cancer.

The diverse effects of cisplatin on tumor microenvironment: Insights and challenges for the delivery of cisplatin by nanoparticles

Cisplatin is a well-known platinum-based chemotherapy medication that is widely utilized for some malignancies. Despite the direct cytotoxic consequences of cisplatin on tumor cells, studies in the recent decade have revealed that cisplatin can also affect different cells and their secretions in the tumor microenvironment (TME). Cisplatin has complex impacts on the TME, which may contribute to its anti-tumor activity or drug resistance mechanisms. These regulatory effects of cisplatin play a paramount function in tumor growth, invasion, and metastasis. This paper aims to review the diverse impacts of cisplatin and nanoparticles loaded with cisplatin on cancer cells and also non-cancerous cells in TME. The impacts of cisplatin on immune cells, tumor stroma, cancer cells, and also hypoxia will be discussed in the current review. Furthermore, we emphasize the challenges and prospects of using cisplatin in combination with other adjuvants and therapeutic modalities that target TME. We also discuss the potential synergistic effects of cisplatin with immune checkpoint inhibitors (ICIs) and other agents with anticancer potentials such as polyphenols and photosensitizers. Furthermore, the potential of nanoparticles for targeting TME and better delivery of cisplatin into tumors will be discussed.

Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation

The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts ranging from cancers to chronic inflammations, as evidenced by many studies. Quantifying fibrillar collagen organization has become a powerful approach for characterizing the topology of collagen fibers and studying the role of collagen fibers in disease progression. We present a deep learning-based pipeline to quantify collagen fibers' topological properties in microscopy-based collagen images from pathological tissue samples. Our method leverages deep neural networks to extract collagen fiber centerlines and deep generative models to create synthetic training data, addressing the current shortage of large-scale annotations. As a part of this effort, we have created and annotated a collagen fiber centerline dataset, with the hope of facilitating further research in this field. Quantitative measurements such as fiber orientation, alignment, density, and length can be derived based on the centerline extraction results. Our pipeline comprises three stages. Initially, a variational autoencoder is trained to generate synthetic centerlines possessing controllable topological properties. Subsequently, a conditional generative adversarial network synthesizes realistic collagen fiber images from the synthetic centerlines, yielding a synthetic training set of image-centerline pairs. Finally, we train a collagen fiber centerline extraction network using both the original and synthetic data. Evaluation using collagen fiber images from pancreas, liver, and breast cancer samples collected via second-harmonic generation microscopy demonstrates our pipeline's superiority over several popular fiber centerline extraction tools. Incorporating synthetic data into training further enhances the network's generalizability. Our code is available at https://github.com/uw-loci/collagen-fiber-metrics.

Oncofetal reprogramming in tumor development and progression: novel insights into cancer therapy

Emerging evidence indicates that cancer cells can mimic characteristics of embryonic development, promoting their development and progression. Cancer cells share features with embryonic development, characterized by robust proliferation and differentiation regulated by signaling pathways such as Wnt, Notch, hedgehog, and Hippo signaling. In certain phase, these cells also mimic embryonic diapause and fertilized egg implantation to evade treatments or immune elimination and promote metastasis. Additionally, the upregulation of ATP-binding cassette (ABC) transporters, including multidrug resistance protein 1 (MDR1), multidrug resistance-associated protein 1 (MRP1), and breast cancer-resistant protein (BCRP), in drug-resistant cancer cells, analogous to their role in placental development, may facilitate chemotherapy efflux, further resulting in treatment resistance. In this review, we concentrate on the underlying mechanisms that contribute to tumor development and progression from the perspective of embryonic development, encompassing the dysregulation of developmental signaling pathways, the emergence of dormant cancer cells, immune microenvironment remodeling, and the hyperactivation of ABC transporters. Furthermore, we synthesize and emphasize the connections between cancer hallmarks and embryonic development, offering novel insights for the development of innovative cancer treatment strategies.

AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer

Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker. The proposed BRACE marker is derived from AI based assessment of heterogeneity in BC at a detailed level using the power of deep learning. The prognostic ability of the marker is validated in two well-annotated cohorts (Cohort-A/Nottingham: n = 2122 and Cohort-B/Coventry: n = 311) on early-stage luminal/HER2-negative BC patients treated with endocrine therapy and with long-term follow-up. The BRACE marker is able to stratify patients for both distant metastasis free survival (p = 0.001, C-index: 0.73) and BC specific survival (p < 0.0001, C-index: 0.84) showing comparable prediction accuracy to Nottingham Prognostic Index and Magee scores, which are both derived from manual histopathological assessment, to identify luminal BC patients that may be likely to benefit from adjuvant chemotherapy.

Tumorigenic effects of human mesenchymal stromal cells and fibroblasts on bladder cancer cells

Background

Patients with muscle-invasive bladder cancer face a poor prognosis due to rapid disease progression and chemoresistance. Thus, there is an urgent need for a new therapeutic treatment. The tumor microenvironment (TME) has crucial roles in tumor development, growth, progression, and therapy resistance. TME cells may also survive standard treatment of care and fire up disease recurrence. However, whether specific TME components have tumor-promoting or tumor-inhibitory properties depends on cell type and cancer entity. Thus, a deeper understanding of the interaction mechanisms between the TME and cancer cells is needed to develop new cancer treatment approaches that overcome therapy resistance. Little is known about the function and interaction between mesenchymal stromal cells (MSC) or fibroblasts (FB) as TME components and bladder cancer cells.

Methods

We investigated the functional impact of conditioned media (CM) from primary cultures of different donors of MSC or FB on urothelial carcinoma cell lines (UCC) representing advanced disease stages, namely, BFTC-905, VMCUB-1, and UMUC-3. Underlying mechanisms were identified by RNA sequencing and protein analyses of cancer cells and of conditioned media by oncoarrays.

Results

Both FB- and MSC-CM had tumor-promoting effects on UCC. In some experiments, the impact of MSC-CM was more pronounced. CM augmented the aggressive phenotype of UCC, particularly of those with epithelial phenotype. Proliferation and migratory and invasive capacity were significantly increased; cisplatin sensitivity was reduced. RNA sequencing identified underlying mechanisms and molecules contributing to the observed phenotype changes. NRF2 and NF-κB signaling was affected, contributing to improved cisplatin detoxification. Likewise, interferon type I signaling was downregulated and regulators of epithelial mesenchymal transition (EMT) were increased. Altered protein abundance of CXCR4, hyaluronan receptor CD44, or TGFβ-signaling was induced by CM in cancer cells and may contribute to phenotypical changes. CM contained high levels of CCL2/MCP-1, MMPs, and interleukins which are well known for their impact on other cancer entities.

Conclusions

The CM of two different TME components had overlapping tumor-promoting effects and increased chemoresistance. We identified underlying mechanisms and molecules contributing to the aggressiveness of bladder cancer cells. These need to be further investigated for targeting the TME to improve cancer therapy.

Deconvolution of cancer cell states by the XDec-SM method

Proper characterization of cancer cell states within the tumor microenvironment is a key to accurately identifying matching experimental models and the development of precision therapies. To reconstruct this information from bulk RNA-seq profiles, we developed the XDec Simplex Mapping (XDec-SM) reference-optional deconvolution method that maps tumors and the states of constituent cells onto a biologically interpretable low-dimensional space. The method identifies gene sets informative for deconvolution from relevant single-cell profiling data when such profiles are available. When applied to breast tumors in The Cancer Genome Atlas (TCGA), XDec-SM infers the identity of constituent cell types and their proportions. XDec-SM also infers cancer cells states within individual tumors that associate with DNA methylation patterns, driver somatic mutations, pathway activation and metabolic coupling between stromal and breast cancer cells. By projecting tumors, cancer cell lines, and PDX models onto the same map, we identify in vitro and in vivo models with matching cancer cell states. Map position is also predictive of therapy response, thus opening the prospects for precision therapy informed by experiments in model systems matched to tumors in vivo by cancer cell state.

Molecular signaling network and therapeutic developments in breast cancer brain metastasis

Breast cancer (BC) is one of the most frequently diagnosed cancers in women worldwide. It has surpassed lung cancer as the leading cause of cancer-related death. Breast cancer brain metastasis (BCBM) is becoming a major clinical concern that is commonly associated with ER-ve and HER2+ve subtypes of BC patients. Metastatic lesions in the brain originate when the cancer cells detach from a primary breast tumor and establish metastatic lesions and infiltrate near and distant organs via systemic blood circulation by traversing the BBB. The colonization of BC cells in the brain involves a complex interplay in the tumor microenvironment (TME), metastatic cells, and brain cells like endothelial cells, microglia, and astrocytes. BCBM is a significant cause of morbidity and mortality and presents a challenge to developing successful cancer therapy. In this review, we discuss the molecular mechanism of BCBM and novel therapeutic strategies for patients with brain metastatic BC.

The covert symphony: cellular and molecular accomplices in breast cancer metastasis

Breast cancer has emerged as the most commonly diagnosed cancer and primary cause of cancer-related deaths among women worldwide. Although significant progress has been made in targeting the primary tumor, the effectiveness of systemic treatments to prevent metastasis remains limited. Metastatic disease continues to be the predominant factor leading to fatality in the majority of breast cancer patients. The existence of a prolonged latency period between initial treatment and eventual recurrence in certain patients indicates that tumors can both adapt to and interact with the systemic environment of the host, facilitating and sustaining the progression of the disease. In order to identify potential therapeutic interventions for metastasis, it will be crucial to gain a comprehensive framework surrounding the mechanisms driving the growth, survival, and spread of tumor cells, as well as their interaction with supporting cells of the microenvironment. This review aims to consolidate recent discoveries concerning critical aspects of breast cancer metastasis, encompassing the intricate network of cells, molecules, and physical factors that contribute to metastasis, as well as the molecular mechanisms governing cancer dormancy.

WDR76 regulates 5-fluorouracil sensitivity in colon cancer via HRAS

BACKGROUND

WD repeat domain 76 (WDR76) has been reported in multiple tumors, while without relation to chemotherapy resistance. 5-fluorouracil (5-FU) is widely adopted in treating colon cancer. However, the resistance of WDR76 and 5-FU in colon cancer remains unclear.

METHODS

Limma package in R software was employed to analyze the differentially expressed genes. Western blot or quantitative real-time PCR (qRT-PCR) were run to assessed the gene expression. The cytotoxic effect was determined according to cell viability assay, colony formation assay in vitro. Cell apoptosis was assayed using flow cytometry. GSEA analysis was performed to identify pathways related to the target gene. Xenografted mice model was employed to evaluate the tumor growth.

RESULTS

Bioinformatic analysis revealed the higher expression of WDR76 in 5-FU sensitive colon cancer cells compared to resistant colon cancer cells, accompanied by the decreased mRNA expression of WDR76 in 5-FU resistant colon cancer cells. The overexpressed WDR76 resulted in the apoptosis and the downregulated colony numbers in 5-FU resistant colon cancer cells, leading to the elevated sensitivity of 5-FU. Meanwhile, knockdown of WDR76 enhances the resistance of 5-FU in colon cancer both in vitro and vivo, which was reversed by a specific inhibitor of HRAS, Kobe006. An important molecular mechanism of 5-FU resistance lies the degradation of HRAS induced by WDR76.

CONCLUSION

Our findings demonstrated a role of WDR76 as a promising target for reversing the resistance of colon cancer to 5-FU.

The novel treatments based on tissue engineering, cell therapy and nanotechnology for cutaneous leishmaniasis

Cutaneous leishmaniasis (CL) is a global public health issue. Conventional treatments have substantial costs, side effects, and parasite resistance. Due to easy application and inexpensive cost, topical treatment is the optimal approach for CL. It could be used alone or with systemic treatments. Electrospun fibers as drug release systems in treating skin lesions have various advantages such as adjustable drug release rate, maintaining appropriate humidity and temperature, gas exchange, plasticity at the lesion site, similarity with the skin extracellular matrix (ECM) and drug delivery with high efficiency. Hydrogels are valuable scaffolds in the treatment of skin lesions. The important features of hydrogels include preserving unstable drugs from degradation, absorption of wound secretions, high biocompatibility, improving the re-epithelialization of the wound and preventing the formation of scars. One of the issues in local drug delivery systems for the skin is the low permeability of drugs in the skin. Polymeric scaffolds that are designed as microneedle patches can penetrate the skin and overcome this challenge. Also, drug delivery using nanocarriers increases the effectiveness of drugs in lower and more tolerable doses and reduces the toxicity of drugs. The application of cell therapy in the treatment of parasitic and infectious diseases has been widely investigated. The complexity of leishmaniasis treatment requires identifying new treatment options like cell therapy to overcome the disease. Topics investigated in this study include drug delivery systems based on tissue engineering scaffolds, nanotechnology and cell therapy-based studies to reduce the complications of CL.

Secretome of Stromal Cancer-Associated Fibroblasts (CAFs): Relevance in Cancer

The cancer secretome reflects the assortment of proteins released by cancer cells. Investigating cell secretomes not only provides a deeper knowledge of the healthy and transformed state but also helps in the discovery of novel biomarkers. Secretomes of cancer cells have been studied in the past, however, the secretome contribution of stromal cells needs to be studied. Cancer-associated fibroblasts (CAFs) are one of the predominantly present cell populations in the tumor microenvironment (TME). CAFs play key role in functions associated with matrix deposition and remodeling, reciprocal exchange of nutrients, and molecular interactions and signaling with neighboring cells in the TME. Investigating CAFs secretomes or CAFs-secreted factors would help in identifying novel CAF-specific biomarkers, unique druggable targets, and an improved understanding for personalized cancer diagnosis and prognosis. In this review, we have tried to include all studies available in PubMed with the keywords "CAFs Secretome". We aim to provide a comprehensive summary of the studies investigating role of the CAF secretome on cancer development, progression, and therapeutic outcome. However, challenges associated with this process have also been addressed in the later sections. We have highlighted the functions and clinical relevance of secretome analysis in stromal CAF-rich cancer types. This review specifically discusses the secretome of stromal CAFs in cancers. A deeper understanding of the components of the CAF secretome and their interactions with cancer cells will help in the identification of personalized biomarkers and a more precise treatment plan.

RANKL Promotes Chemotherapy Resistance in Breast Cancer Cells Through STAT3 Mediated Autophagy Induction

BACKGROUND

This study was to investigate the functional role and mechanism of receptor activator of nuclear factor-kappa B ligand (RANKL) associated autophagy and chemoresistance in breast cancer.

MATERIALS AND METHODS

Cell Counting Kit-8 (CCK-8) assay was used to detect the cell viability. Real-time polymerase chain reaction (PCR) was used for determining the relative mRNA levels of key genes and protein expression was assessed by Western blotting. Immunofluorescence was performed to evaluate the changes in the autophagy flux. Short hairpin (shRNA) was used to knockdown the expression of the target genes in breast cancer cells. Based on The Cancer Genome Atlas (TCGA) database, we explored the expression of receptor activator of nuclear factor-kappa B (RANK), autophagy and signal transducer and activator of transcription 3 (STAT3) signaling associated genes and analyzed their correlation with the prognosis of breast cancer patients.

RESULTS

The findings showed that receptor activator of nuclear factor-kappa B ligand (RANKL), the ligand of RANK, could effectively enhance the chemoresistance potential of breast cancer cells. Our results showed that RANKL induced autophagy and enhanced the expression of autophagy associated genes in breast cancer cells. The knockdown of RANK suppressed RANKL mediated autophagy induction in these cells. Furthermore, the inhibition of autophagy suppressed RANKL mediated chemoresistance in breast cancer cells. We found STAT3 signaling pathway was involved in RANKL-induced autophagy. Analysis of the expression of RANK, and autophagy and STAT3 signaling associated genes in breast cancer tissues showed that the expression of autophagy and STAT3 signaling associated genes was correlated with the prognosis of breast cancer patients.

CONCLUSION

The present study suggests that the RANKL/RANK axis may potentially mediate chemoresistance in breast cancer cells by inducing autophagy through the STAT3 signaling pathway.

Cancer-Associated Adipocytes and Breast Cancer: Intertwining in the Tumor Microenvironment and Challenges for Cancer Therapy

Adipocytes are the main components in breast tissue, and cancer-associated adipocytes (CAAs) are one of the most important components in the tumor microenvironment of breast cancer (BC). Bidirectional regulation was found between CAAs and BC cells. BC facilitates the dedifferentiation of adjacent adipocytes to form CAAs with morphological and biological changes. CAAs increase the secretion of multiple cytokines and adipokines to promote the tumorigenesis, progression, and metastasis of BC by remodeling the extracellular matrix, changing aromatase expression, and metabolic reprogramming, and shaping the tumor immune microenvironment. CAAs are also associated with the therapeutic response of BC and provide potential targets in BC therapy. The present review provides a comprehensive description of the crosstalk between CAAs and BC and discusses the potential strategies to target CAAs to overcome BC treatment resistance.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential.

Cancer-associated fibroblasts induce growth and radioresistance of breast cancer cells through paracrine IL-6

In breast cancer, the most numerous stromal cells are cancer-associated fibroblasts (CAFs), which are associated with disease progression and chemoresistance. However, few studies have explored the function of CAFs in breast cancer cell radiosensitivity. Here, CAF-derived conditioned media was observed to induce breast cancer cell growth and radioresistance. CAFs secrete interleukin 6 (IL-6) which activates signal transducer and activator of transcription 3 (STAT3) signaling pathway, thus promoting the growth and radioresistance of breast cancer cells. Treatment with an inhibitor of STAT3 or an IL-6 neutralizing antibody blocked the growth and radioresistance induced by CAFs. In in vivo mouse models, tocilizumab (an IL-6 receptor monoclonal antibody) abrogated CAF-induced growth and radioresistance. Moreover, in breast cancer, a poor response to radiotherapy was associated with IL-6 and p-STAT3 expression. These results indicated that IL-6 mediates cross-talk between breast cancer cells and CAFs in the tumor microenvironment. Our results identified the IL-6/STAT3 signaling pathway as an important therapeutic target in breast cancer radiotherapy.

MAST: a hybrid Multi-Agent Spatio-Temporal model of tumor microenvironment informed using a data-driven approach

Motivation

Recently, several computational modeling approaches, such as agent-based models, have been applied to study the interaction dynamics between immune and tumor cells in human cancer. However, each tumor is characterized by a specific and unique tumor microenvironment, emphasizing the need for specialized and personalized studies of each cancer scenario.

Results

We present MAST, a hybrid Multi-Agent Spatio-Temporal model which can be informed using a data-driven approach to simulate unique tumor subtypes and tumor-immune dynamics starting from high-throughput sequencing data. It captures essential components of the tumor microenvironment by coupling a discrete agent-based model with a continuous partial differential equations-based model.The application to real data of human colorectal cancer tissue investigating the spatio-temporal evolution and emergent properties of four simulated human colorectal cancer subtypes, along with their agreement with current biological knowledge of tumors and clinical outcome endpoints in a patient cohort, endorse the validity of our approach.

Availability and implementation

MAST, implemented in Python language, is freely available with an open-source license through GitLab (https://gitlab.com/sysbiobig/mast), and a Docker image is provided to ease its deployment. The submitted software version and test data are available in Zenodo at https://dx.doi.org/10.5281/zenodo.7267745.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Mesenchymal-endothelial nexus in breast cancer spheroids induces vasculogenesis and local invasion in a CAM model

Interplay between non-cancerous cells (immune, fibroblasts, mesenchymal stromal cells (MSC), and endothelial cells (EC)) has been identified as vital in driving tumor progression. As studying such interactions in vivo is challenging, ex vivo systems that can recapitulate in vivo scenarios can aid in unraveling the factors impacting tumorigenesis and metastasis. Using the synthetic tumor microenvironment mimics (STEMs)-a spheroid system composed of breast cancer cells (BCC) with defined human MSC and EC fractions, here we show that EC organization into vascular structures is BC phenotype dependent, and independent of ERα expression in epithelial cancer cells, and involves MSC-mediated Notch1 signaling. In a 3D-bioprinted model system to mimic local invasion, MDA STEMs collectively respond to serum gradient and form invading cell clusters. STEMs grown on chick chorioallantoic membrane undergo local invasion to form CAM tumors that can anastomose with host vasculature and bear the typical hallmarks of human BC and this process requires both EC and MSC. This study provides a framework for developing well-defined in vitro systems, including patient-derived xenografts that recapitulate in vivo events, to investigate heterotypic cell interactions in tumors, to identify factors promoting tumor metastasis-related events, and possibly drug screening in the context of personalized medicine.

Targeting the tumor stroma for cancer therapy

Tumors are comprised of both cancer cells and surrounding stromal components. As an essential part of the tumor microenvironment, the tumor stroma is highly dynamic, heterogeneous and commonly tumor-type specific, and it mainly includes noncellular compositions such as the extracellular matrix and the unique cancer-associated vascular system as well as a wide variety of cellular components including activated cancer-associated fibroblasts, mesenchymal stromal cells, pericytes. All these elements operate with each other in a coordinated fashion and collectively promote cancer initiation, progression, metastasis and therapeutic resistance. Over the past few decades, numerous studies have been conducted to study the interaction and crosstalk between stromal components and neoplastic cells. Meanwhile, we have also witnessed an exponential increase in the investigation and recognition of the critical roles of tumor stroma in solid tumors. A series of clinical trials targeting the tumor stroma have been launched continually. In this review, we introduce and discuss current advances in the understanding of various stromal elements and their roles in cancers. We also elaborate on potential novel approaches for tumor-stroma-based therapeutic targeting, with the aim to promote the leap from bench to bedside.

Identify the immune characteristics and immunotherapy value of CD93 in the pan-cancer based on the public data sets

CD93 is a transmembrane receptor that is mainly expressed on endothelial cells. A recent study found that upregulated CD93 in tumor vessels is essential for tumor angiogenesis in several cancers. However, the underlying mechanisms are largely unexplored. Our present research systematically analyzed the characteristics of CD93 in tumor immunotherapy among 33 cancers. CD93 levels and co-expression of CD93 on cancer and stromal cells were detected using public databases and multiple immunofluorescence staining. The Kaplan-Meier (KM) analysis identified the predictive role of CD93 in these cancer types. The survival differences between CD93 mutants and WT, CNV groups, and methylation were also investigated. The immune landscape of CD93 in the tumor microenvironment was analyzed using the SangerBox, TIMER 2.0, and single-cell sequencing. The immunotherapy value of CD93 was predicted through public databases. CD93 mRNA and protein levels differed significantly between cancer samples and adjacent control tissues in multiply cancer types. CD93 mRNA expression associated with patient prognosis in many cancers. The correlation of CD93 levels with mutational status of other gene in these cancers was also analyzed. CD93 levels significantly positively related to three scores (immune, stromal, and extimate), immune infiltrates, immune checkpoints, and neoantigen expression.. Additionally, single-cell sequencing revealed that CD93 is predominantly co-expressed on tumor and stromal cells, such as endothelial cells, cancer-associated fibroblasts (CAFs), neutrophils, T cells, macrophages, M1 and M2 macrophages. Several immune-related signaling pathways were enriched based on CD93 expression, including immune cells activation and migration, focal adhesion, leukocyte transendothelial migration, oxidative phosphorylation, and complement. Multiple immunofluorescence staining displayed the relationship between CD93 expression and CD8, CD68, and CD163 in these cancers. Finally, the treatment response of CD93 in many immunotherapy cohorts and sensitive small molecules was predicted from the public datasets. CD93 expression is closely associated with clinical prognosis and immune infiltrates in a variety of tumors. Targeting CD93-related signaling pathways in the tumor microenvironment may be a novel therapeutic strategy for tumor immunotherapy.

Tumor-derived miR-130b-3p induces cancer-associated fibroblast activation by targeting SPIN90 in luminal A breast cancer

Cancer-associated fibroblasts (CAFs) in the tumor microenvironment (TME) interact closely with cancer cells to promote tumor development. Downregulation of SPIN90 in CAFs has been reported to facilitate breast cancer progression, but the underlying mechanism has not been elucidated. Here, we demonstrate that miR-130b-3p directly downregulates SPIN90 in stromal fibroblasts, leading to their differentiation into CAFs. As the decrease of SPIN90 in CAFs was shown to be more prominent in estrogen receptor (ER)-positive breast tumors in this study, miR-130b-3p was selected by bioinformatics analysis of data from patients with ER-positive breast cancer. Ectopic expression of miR-130b-3p in fibroblasts accelerated their differentiation to CAFs that promote cancer cell motility; this was associated with SPIN90 downregulation. We also found that miR-130b-3p was generated in luminal A-type cancer cells and activated fibroblasts after being secreted via exosomes from cancer cells. Finally, miR-130b-3p increased in SPIN90-downregulated tumor stroma of luminal A breast cancer patients and MCF7 cell-xenograft model mice. Our data demonstrate that miR-130b-3p is a key modulator that downregulates SPIN90 in breast CAFs. The inverse correlation between miR-130b-3p and SPIN90 in tumor stroma suggests that the miR-130b-3p/SPIN90 axis is clinically significant for CAF activation during breast cancer progression.

Evaluation of Hematologic Parameters in Patients with COVID-19 Following Mesenchymal Stem Cell Therapy

At present, severe acute respiratory syndrome coronavirus 2 is spreading and has caused over 188 million confirmed patients and more than 4,059,101 deaths. Currently, several clinical trials are done using mesenchymal stem cell (MSC) therapy in patients with coronavirus disease 2019 (COVID-19). These cells have shown safety and effectiveness, implying a promising clinical application in patients with COVID-19. Studies have shown that abnormalities in hematological measures such as white blood cells count, neutrophilia, elevated neutrophil to lymphocyte ratio, inflammatory markers, and lactate dehydrogenase can be used to assess the severity of COVID-19 disease and the response to therapy following MSC treatment. Our study has aimed to review the role of hematological factors in determination of responsiveness to MSC therapy and disease severity in COVID-19 patients.

End-to-End diagnosis of breast biopsy images with transformers

Diagnostic disagreements among pathologists occur throughout the spectrum of benign to malignant lesions. A computer-aided diagnostic system capable of reducing uncertainties would have important clinical impact. To develop a computer-aided diagnosis method for classifying breast biopsy images into a range of diagnostic categories (benign, atypia, ductal carcinoma in situ, and invasive breast cancer), we introduce a transformer-based hollistic attention network called HATNet. Unlike state-of-the-art histopathological image classification systems that use a two pronged approach, i.e., they first learn local representations using a multi-instance learning framework and then combine these local representations to produce image-level decisions, HATNet streamlines the histopathological image classification pipeline and shows how to learn representations from gigapixel size images end-to-end. HATNet extends the bag-of-words approach and uses self-attention to encode global information, allowing it to learn representations from clinically relevant tissue structures without any explicit supervision. It outperforms the previous best network Y-Net, which uses supervision in the form of tissue-level segmentation masks, by 8%. Importantly, our analysis reveals that HATNet learns representations from clinically relevant structures, and it matches the classification accuracy of 87 U.S. pathologists for this challenging test set.

Effects of iron modulation on mesenchymal stem cell-induced drug resistance in estrogen receptor-positive breast cancer

Patients with estrogen receptor-positive (ER+) breast cancer, the most common subtype, remain at risk for lethal metastatic disease years after diagnosis. Recurrence arises partly because tumor cells in bone marrow become resistant to estrogen-targeted therapy. Here, we utilized a co-culture model of bone marrow mesenchymal stem cells (MSCs) and ER+ breast cancer cells to recapitulate interactions of cancer cells in bone marrow niches. ER+ breast cancer cells in direct contact with MSCs acquire cancer stem-like (CSC) phenotypes with increased resistance to standard antiestrogenic drugs. We confirmed that co-culture with MSCs increased labile iron in breast cancer cells, a phenotype associated with CSCs and disease progression. Clinically approved iron chelators and in-house lysosomal iron-targeting compounds restored sensitivity to antiestrogenic therapy. These findings establish iron modulation as a mechanism to reverse MSC-induced drug resistance and suggest iron modulation in combination with estrogen-targeted therapy as a promising, translatable strategy to treat ER+ breast cancer.

Agent-based computational modeling of glioblastoma predicts that stromal density is central to oncolytic virus efficacy

Oncolytic viruses (OVs) are emerging cancer immunotherapy. Despite notable successes in the treatment of some tumors, OV therapy for central nervous system cancers has failed to show efficacy. We used an ex vivo tumor model developed from human glioblastoma tissue to evaluate the infiltration of herpes simplex OV rQNestin (oHSV-1) into glioblastoma tumors. We next leveraged our data to develop a computational, model of glioblastoma dynamics that accounts for cellular interactions within the tumor. Using our computational model, we found that low stromal density was highly predictive of oHSV-1 therapeutic success, suggesting that the efficacy of oHSV-1 in glioblastoma may be determined by stromal-to-tumor cell regional density. We validated these findings in heterogenous patient samples from brain metastatic adenocarcinoma. Our integrated modeling strategy can be applied to suggest mechanisms of therapeutic responses for central nervous system cancers and to facilitate the successful translation of OVs into the clinic.

Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score

Background

Oncotype DX Recurrence Score (RS) has been widely used to predict chemotherapy benefits in patients with estrogen receptor-positive breast cancer. Studies showed that the features used in Magee equations correlate with RS. We aimed to examine whether deep learning (DL)-based histology image analyses can enhance such correlations.

Methods

We retrieved 382 cases with RS diagnosed between 2011 and 2015 from the Emory University and the Ohio State University. All patients received surgery. DL models were developed to detect nuclei of tumor cells and tumor-infiltrating lymphocytes (TILs) and segment tumor cell nuclei in hematoxylin and eosin (H&E) stained histopathology whole slide images (WSIs). Based on the DL-based analysis, we derived image features from WSIs, such as tumor cell number, TIL number variance, and nuclear grades. The entire patient cohorts were divided into one training set (125 cases) and two validation sets (82 and 175 cases) based on the data sources and WSI resolutions. The training set was used to train the linear regression models to predict RS. For prediction performance comparison, we used independent variables from Magee features alone or the combination of WSI-derived image and Magee features.

Results

The Pearson's correlation coefficients between the actual RS and predicted RS by DL-based analysis were 0.7058 (p-value = 1.32 × 10-13) and 0.5041 (p-value = 1.15 × 10-12) for the validation sets 1 and 2, respectively. The adjusted R 2 values using Magee features alone are 0.3442 and 0.2167 in the two validation sets, respectively. In contrast, the adjusted R 2 values were enhanced to 0.4431 and 0.2182 when WSI-derived imaging features were jointly used with Magee features.

Conclusion

Our results suggest that DL-based digital pathological features can enhance Magee feature correlation with RS.

Proposal of an automated tumor-stromal ratio assessment algorithm and a nomogram for prognosis in early-stage invasive breast cancer

BACKGROUND

The tumor-stromal ratio (TSR) has been verified to be a prognostic factor in many solid tumors. In most studies, it was manually assessed on routinely stained H&E slides. This study aimed to assess the TSR using image analysis algorithms developed by the Qupath software, and integrate the TSR into a nomogram for prediction of the survival in invasive breast cancer (BC) patients.

METHODS

A modified TSR assessment algorithm based on the recognition of tumor and stroma tissues was developed using the Qupath software. The TSR of 234 invasive BC specimens in H&E-stained tissue microarrays (TMAs) were assessed with the algorithm and categorized as stroma-low or stroma-high. The consistency of TSR estimation between Qupath prediction and pathologist annotation was analyzed. Univariable and multivariable analyses were applied to select potential risk factors and a nomogram for predicting survival in invasive BC patients was constructed and validated. An extra TMA containing 110 specimens was obtained to validate the conclusion as an independent cohort.

RESULTS

In the discovery cohort, stroma-low and stroma-high were identified in 43.6% and 56.4% cases, respectively. Good concordance was observed between the pathologist annotated and Qupath predicted TSR. The Kaplan-Meier curve showed that stroma-high patients were associated with worse 5-DFS compared to stroma-low patients (p = 0.007). Multivariable analysis identified age, T stage, N status, histological grade, ER status, HER-2 gene, and TSR as potential risk predictors, which were included in the nomogram. The nomogram was well calibrated and showed a favorable predictive value for the recurrence of BC. Kaplan-Meier curves showed that the nomogram had a better risk stratification capability than the TNM staging system. In the external validation of the nomogram, the results were further validated.

CONCLUSIONS

Based on H&E-stained TMAs, this study successfully developed image analysis algorithms for TSR assessment and constructed a nomogram for predicting survival in invasive BC.

Targeting Akt/NF-κB/p53 Pathway and Apoptosis Inducing Potential of 1,2-Benzenedicarboxylic Acid, Bis (2-Methyl Propyl) Ester Isolated from Onosma bracteata Wall. against Human Osteosarcoma (MG-63) Cells

Onosma bracteata Wall. is an important medicinal and immunity-enhancing herbs. This plant is commonly used in the preparation of traditional Ayurvedic drugs to treat numerous diseases. Inspired by the medicinal properties of this plant, the present study aimed to investigate the antiproliferative potential and the primary molecular mechanisms of the apoptotic induction against human osteosarcoma (MG-63) cells. Among all the fractions isolated from O. bracteata, ethyl acetate fraction (Obea) showed good antioxidant activity in superoxide radical scavenging assay and lipid peroxidation assay with an EC50 value of 95.12 and 80.67 µg/mL, respectively. Silica gel column chromatography of ethyl acetate (Obea) fraction of O. bracteata yielded a pure compound, which was characterized by NMR, FTIR, and HR-MS analysis and was identified as 1,2-benzene dicarboxylic acid, bis (2-methyl propyl) ester (BDCe fraction). BDCe fraction was evaluated for the antiproliferative potential against human osteosarcoma MG-63, human neuroblastoma IMR-32, and human lung carcinoma A549 cell lines by MTT assay and exhibited GI50 values of 37.53 μM, 56.05 μM, and 47.12 μM, respectively. In Mg-63 cells, the BDCe fraction increased the level of ROS and simultaneously decreased the mitochondria membrane potential (MMP) potential by arresting cells at the G0/G1 phase, suggesting the initiation of apoptosis. Western blotting analysis revealed the upregulation of p53, caspase3, and caspase9 while the expressions of p-NF-κB, p-Akt and Bcl-xl were decreased. RT-qPCR studies also showed upregulation in the expression of p53 and caspase3 and downregulation in the expression of CDK2, Bcl-2 and Cyclin E genes. Molecular docking analysis displayed the interaction between BDCe fraction with p53 (−151.13 kcal/mol) and CDK1 (−133.96 kcal/mol). The results of the present work suggest that the BDCe fraction has chemopreventive properties against osteosarcoma (MG-63) cells through the induction of cell cycle arrest and apoptosis via Akt/NF-κB/p53 pathways. This study contributes to the understanding of the utilization of BDCe fraction in osteosarcoma treatment.

Establishment of a Cell Necroptosis Index to Predict Prognosis and Drug Sensitivity for Patients With Triple-Negative Breast Cancer

Background: Necroptosis has been an alternatively identified mechanism of programmed cancer cell death, which plays a significant role in cancer. However, research about necroptosis-related long noncoding RNAs (lncRNAs) in cancer are still few. Moreover, the potentially prognostic value of necroptosis-related lncRNAs and their correlation with the immune microenvironment remains unclear. The present study aimed to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship to immune microenvironment in triple-negative breast cancer (TNBC).

Methods: The RNA expression matrix of patients with TNBC was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Finally, 107 patients of GSE58812, 159 patients of TCGA, and 143 patients of GSE96058 were included. Necroptosis-related lncRNAs were screened by Cox regression and Pearson correlation analysis with necroptosis-related genes. By LASSO regression analysis, nine necroptosis-related lncRNAs were employed, and a cell necroptosis index (CNI) was established; then, we evaluated its prognostic value, clinical significance, pathways, immune infiltration, and chemotherapeutics efficacy.

Results: Based on the CNI value, the TNBC patients were divided into high- and low-CNI groups, and the patients with high CNI had worse prognosis, more lymph node metastasis, and larger tumor (p < 0.05). The receiver operating characteristic (ROC) analysis showed that the signature performed well. The result of the infiltration proportion of different immune cell infiltration further explained that TNBC patients with high CNI had low immunogenicity, leading to poor therapeutic outcomes. Moreover, we found significant differences of the IC50 values of various chemotherapeutic drugs in the two CNI groups, which might provide a reference to make a personalized chemotherapy for them.

Conclusion: The novel prognostic marker CNI could not only precisely predict the survival probability of patients with TNBC but also demonstrate a potential role in antitumor immunity and drug sensitivity.

TIMP-1-expressing breast tumor spheroids for the evaluation of drug penetration and efficacy

Abundance of stromal cells and extracellular matrix (ECM) is observed in breast cancer, acting as a barrier for drug penetration and presenting a key issue for developing efficient therapeutics. In this study, we aimed to develop a three-dimensional (3D) multicellular tumor model comprising cancer and stromal cells that could effectively mimic the drug resistance properties of breast cancer. Three different types of spheroid models were designed by co-culturing breast cancer cells (MDA-MB-231) with three different types of stromal cells: human adipose-derived stromal cells (hASCs), human bone marrow stromal cells, or human dermal fibroblasts. Compared with other models, in the hASC co-culture model, tissue inhibitor of metalloproteinases-1 (TIMP-1) was highly expressed and the activity of matrix metalloproteinases was decreased, resulting in a higher ECM deposition on the spheroid surfaces. This spheroid model showed less drug penetration and treatment efficacy than the other models. TIMP-1 silencing in hASCs reduced ECM protein expression and increased drug penetration and vulnerability. A quantitative structure-activity relationship study using multiple linear regression drew linear relationships between the chemical properties of drugs and experimentally determined permeability values. Drugs that did not match the drug-likeness rules exhibited lower permeability in the 3D tumor model. Taken together, our findings indicate that this 3D multicellular tumor model may be used as a reliable platform for efficiently screening therapeutics agents for solid tumors.