Collagen fiber features and COL1A1: are they associated with elastic parameters in breast lesions, and can COL1A1 predict axillary lymph node metastasis?

The association between tumor-stromal collagen features and the clinical outcomes of patients with breast cancer: a systematic review

BACKGROUND

The tumor microenvironment (TME), particularly the extracellular matrix (ECM), plays a crucial role in regulating breast cancer progression. Among ECM components, collagen type I-accounting for over 90% of fibrillar collagen in the human body-is the primary structural component of the tumor ECM. It critically modulates tumor cell behavior, influencing migration, invasion, and therapy resistance. The structural organization of collagen type I fibers can significantly impact clinical outcomes.

METHODS

This systematic review aimed to assess the association between tumor-stromal collagen type I characteristics and clinical outcomes in breast cancer. A comprehensive search strategy identified studies from major databases, which were appraised using quality assessment tools. Data on collagen quantity, morphology, alignment, and organization were extracted and analyzed to explore their relationship with survival, metastasis, therapy resistance, and clinical characteristics of breast cancer.

RESULTS

Our analysis revealed that increased collagen density-particularly with an organized/aligned fiber orientation-was strongly associated with poor prognosis. Specifically, increased intratumoral collagen quantity was linked to reduced overall survival (HR = 7.84, p = 0.031). Stage III tumors exhibiting elevated collagen uniformity showed higher metastasis rates (p = 0.004), and HER2⁺ tumors with high collagen content correlated with resistance to HER2-targeted therapies (p < 0.05). Furthermore, higher collagen curviness was associated with better outcomes, including a reduced recurrence risk (HR = 0.77, p < 0.001). Subtype-specific trends emerged as ER/PR-negative tumors more frequently exhibited a perpendicular collagen arrangement (p = 0.02), whereas ER/PR-positive tumors showed elevated COL1A1 expression (p < 0.0001). Despite these patterns, the heterogeneity of study methodologies and the complexity of the tumor microenvironment highlight the need for unified frameworks to advance clinical translation.

CONCLUSIONS

This review highlights the prognostic significance of tumor-stromal collagen characteristics in breast cancer, suggesting that future research should focus on the molecular mechanisms underlying collagen remodeling and its potential as a cancer biomarker and therapeutic target.

Mechanistic role of stromal cancer-associated fibroblasts in tumorigenesis and brain metastasis: Highlighting drug resistance and targeted therapy

Brain metastases remain a major clinical challenge due to their high resistance to conventional and targeted therapies. Cancer-associated fibroblasts are the most common cellular component of the brain metastases tumor microenvironment. They significantly impact the tumor microenvironment because they promote cancer cell invasion, enhance metastasis, boost immune evasion, and contribute to drug resistance. We searched the PubMed and Google Scholar databases and included 99 studies to summarize the present review. Based on the searched articles, the present review emphasizes that biomarkers including PDGFR-β, α-SMA, and collagen I can identify metastatic brain cancer-associated fibroblasts, which lead to a poor prognosis and recurrence. In addition, cancer-associated fibroblasts can cause resistance to therapy by modifying the extracellular matrix (e.g., collagen I, fibronectin), secreting growth factors (e.g., TGF-β, HGF, IL-6), causing immunological evasion (e.g., Tregs, MDSCs), secreting exosomes (e.g., miRNAs), metabolic reprogramming, stemness induction, and plasticity. We also describe the molecular mechanisms by which cancer-associated fibroblasts confer drug resistance in brain metastases, such as extracellular matrix restoration, immunological evasion, metabolic reprogramming, etc. We also cover prospective therapeutic options for overcoming medication resistance, such as cancer-associated fibroblasts depletion, paracrine signaling blockage, metabolic inhibitors, and cancer-associated fibroblasts-targeted immunotherapies. Targeting cancer-associated fibroblasts in addition to existing medications may improve cancer treatment efficacy and survival rates for individuals with brain metastases. However, more research is required to better understand their role in metastatic brain tumors.

Shear Wave Elastography: A Non-Invasive Approach for Assessing TGF-β1/MAPK Signaling Molecules and EMT in Breast Cancer

Background

This study investigated the relationship between Shear Wave Elastography (SWE), TGF-β1/MAPK signaling molecules, and epithelial-to-mesenchymal transition (EMT) in breast lesions, exploring the feasibility of SWE in early EMT identification for breast cancer.

Methods

117 breast lesions in 107 patients from July to November 2023 were consecutively enrolled. SWE was performed preoperatively, and elastic parameters were documented. Immunohistochemistry (IHC) assessed the expression levels of TGF-β1, p38 MAPK, p-p38 MAPK, ERK1/2, p-ERK1/2, ERK5, p-ERK5, JNK, p-JNK, E-cadherin, β-catenin, N-cadherin, and Vimentin. Correlations between SWE parameters and biomarkers were analysed, and their diagnostic efficacy for axillary lymph node metastasis (LNM) was evaluated.

Results

Among 117 breast lesions, 53 were classified as benign and 64 as malignant (25 exhibiting axillary LNM). Optimal SWE thresholds for distinguishing benign from malignant lesions were Emax = 106.7 kPa, Emean = 62.9 kPa, Emin = 22.5 kPa, Eratio = 3.4, and Esd = 21.2 kPa. For LNM prediction, cut-offs were Emax = 170.1 kPa, Emean = 118.5 kPa, and Eratio = 10.5. TGF-β1 and E-cadherin showed significant predictive value for LNM (AUCs: 0.774 and 0.704, respectively). E-cadherin negatively correlated with SWE parameters, while TGF-β1 and MAPK molecules (p38 MAPK, p-p38 MAPK) showed positive correlations. Lesions with "stiff rim sign" had significantly lower E-cadherin expression but elevated levels of TGF-β1 (P<0.001). Additionally, Vimentin, p38 MAPK and p-p38 MAPK levels were higher in the occurrence of the "stiff rim sign" (P all <0.05).

Conclusion

TGF-β1, p38 MAPK, and E-cadherin demonstrated strong diagnostic capabilities and correlated with SWE parameters. SWE offers a promising non-invasive approach for assessing prognosis by identifying EMT characteristics at an earlier stage in breast cancer.

From ductal carcinoma in situ to invasive breast cancer: the prognostic value of the extracellular microenvironment

Ductal carcinoma in situ (DCIS) is a noninvasive breast disease that variably progresses to invasive breast cancer (IBC). Given the unpredictability of this progression, most DCIS patients are aggressively managed similar to IBC patients. Undoubtedly, this treatment paradigm places many DCIS patients at risk of overtreatment and its significant consequences. Historically, prognostic modeling has included the assessment of clinicopathological features and genomic markers. Although these provide valuable insights into tumor biology, they remain insufficient to predict which DCIS patients will progress to IBC. Contemporary work has begun to focus on the microenvironment surrounding the ductal cells for molecular patterns that might predict progression. In this review, extracellular microenvironment alterations occurring with the malignant transformation from DCIS to IBC are detailed. Not only do changes in collagen abundance, organization, and localization mediate the transition to IBC, but also the discrete post-translational regulation of collagen fibers is understood to promote invasion. Other extracellular matrix proteins, such as matrix metalloproteases, decorin, and tenascin C, have been characterized for their role in invasive transformation and further demonstrate the prognostic value of the extracellular matrix. Importantly, these extracellular matrix proteins influence immune cells and fibroblasts toward pro-tumorigenic phenotypes. Thus, the progressive changes in the extracellular microenvironment play a key role in invasion and provide promise for prognostic development.

Development and Characterization of 3-Dimensional Cell Culture Models of Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare malignancy of the adrenal cortex that is associated with a poor prognosis. Developing effective treatment options for ACC is challenging owing to the current lack of representative preclinical models. This study addressed this limitation by developing and characterizing 3-dimensional (3D) cell cultures incorporating the ACC cell lines, MUC-1, HAC15, and H295R in a type I collagen matrix. ACC tissue samples were analyzed by immunohistochemistry to determine the presence of type I collagen in the tumor microenvironment. Cell viability and proliferation were assessed using flow cytometry and confocal microscopy. mRNA expression of steroidogenic enzymes and steroid secretion was analyzed by comparing the 3D and monolayer cell culture models. All cells were successfully cultured in a type I collagen matrix, which is highly expressed in the ACC tumor microenvironment and showed optimal viability until day 7. All 3 models showed increased metabolic and proliferative activity over time. Three-dimensional cell cultures were steroidogenic and demonstrated increased resistance to the gold standard chemotherapy, mitotane, compared with monolayer. The use of these models may lead to an improved understanding of disease pathology and provide a better representative platform for testing and screening of potential therapies.

The correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis

Objective

This study aimed to explore the correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis.

Method

A total of 196 patients with surgically confirmed breast cancer between September 2019 and December 2023 were included. Data on preoperative B-mode ultrasound (US), color Doppler, and shear wave elastography (SWE) features of breast cancer masses were collected and analyzed to determine their correlation with axillary lymph node metastasis. The area under the receiver operating characteristic curve (AUC) of B-mode US, color Doppler, SWE, and the multi-mode predictive model for evaluating axillary lymph node metastasis were compared.

Results

Among the 196 patients, 70 had positive axillary lymph nodes, while 126 had negative axillary lymph nodes. There was no significant difference in the color features between the negative and positive axillary lymph node groups. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were identified as independent risk factors to predict axillary lymph node metastasis according to binary logistic regression analysis. The AUC of the predictive model based on these independent risk factors was 0.803 (95% CI: 0.739-0.867), which was significantly higher than that of B-mode US or SWE alone.

Conclusion

Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were found to be valuable for predicting axillary lymph node metastasis in patients with breast cancer. The predictive model developed in this study, combining the multi-mode ultrasonographic features of breast cancer masses, could serve as a noninvasive and convenient method to predict axillary lymph node status. This approach could aid in clinical decision-making and individualized treatment to improve the prognosis of breast cancer patients.

Differentially expressed extracellular matrix genes functionally separate ameloblastoma from odontogenic keratocyst

BACKGROUND

Ameloblastoma and odontogenic keratocyst (OKC) are odontogenic tumors that develop from remnants of odontogenic epithelium. Both display locally invasive growth characteristics and high predilection for recurrence after surgical removal. Most ameloblastomas harbor BRAFV600E mutation while OKCs are associated with PATCH1 gene mutation but distinctive indicators of ameloblastoma growth characteristics relative to OKC are still unclear. The aim of this study was to assess hub genes that underlie ameloblastoma growth characteristics using bioinformatic analysis, ameloblastoma samples and mouse xenografts of human epithelial-derived ameloblastoma cells.

METHODS

RNA expression profiles were extracted from GSE186489 gene expression dataset acquired from Gene Expression Ominibus (GEO) database. Galaxy and iDEP online analysis tools were used to identify differentially expressed genes that were further characterized by gene ontology (GO) and pathway analysis using ShineyGO. The protein-protein interaction (PPI) network was constructed for significantly upregulated differentially expressed genes using online database STRING. The PPI network visualization was performed using Cytoscape and hub gene identification with cytoHubba. Top ten nodes were selected using maximum neighborhood component, degree and closeness algorithms and analysis of overlap was performed to confirm the hub genes. Epithelial-derived ameloblastoma cells from conventional ameloblastoma were transplanted into immunocompromised mice to recreate ameloblastoma in vivo based on the mouse xenograft model. The top 3 hub genes FN1, COL I and IGF-1 were validated by immunostaining and quantitative analysis of staining intensities to ameloblastoma, OKC samples and mouse ameloblastoma xenografts tissues.

RESULTS

Seven hub genes were identified among which FN1, COL1A1/COL1A2 and IGF-1 are associated with extracellular matrix organization, collagen binding, cell adhesion and cell surface interaction. These were further validated by positive immunoreactivity within the stroma of ameloblastoma samples but both ameloblastoma xenograft and OKC displayed only FN1 and IGF-1 immunoreactivity while COL 1 was unreactive. The expression levels of both FN1 and IGF-1 were much lower in OKC relative to ameloblastoma.

CONCLUSION

This study further validates a differentially upregulated expression of matrix proteins FN1, COL I and IGF-1 in ameloblastoma relative to OKC. It suggests that differential stromal architecture and growth characteristics of ameloblastoma relative to OKC could be an interplay of differentially upregulated genes in ameloblastoma.

Unveiling Potential Therapeutic Targets for Breast Cancer Recurrence: Differentially Expressed Genes and Pathways in Post-Surgery Patients

Various intrinsic and extrinsic factors, including genetic changes and environmental factors, have been reported to contribute to tumor recurrence. However, insufficient information about the significantly dysregulated genes and pathways responsible for cancer recurrence, even after surgical removal of tumors and chemotherapy. The aim of this research is to find out the fundamental genes linked with progression of cancer that may play a critical role in breast cancer recurrence. To achieve this, a microarray dataset of Affymetrix Human Genome U133 Plus 2.0 Array platform was used to identify downregulated and upregulated genes that associated with tumor recurrence in post-surgery patients. The study includes 20 specimen, 10 samples extracted at the time of diagnosis and 10 samples taken 30 minutes post-surgery and chemotherapy. Genes that stand out from the rest in their level of expression were further subjected to subsequent functional enrichment analysis and hub genes identification to pinpoint the key genes associated with recurrence. Results revealed that significantly overexpressed genes were found to be enriched in cancer progression-associated signaling pathways, for example, Wnt pathway and proteoglycans in cancer. Moreover, the identified key hub genes (COL1A1, IGF1, COL1A2, DCN, LUM, MMP2, JUN, CXCL12, THBS2, and LOX) majorly found to play a role in gene expression regulation, dysregulated immune system, epithelial-to-mesenchymal transition, and extracellular matrix remodeling thus promoting the development of cancer and increasing the chances of recurrence after surgery and chemotherapy. The findings have uncovered key therapeutic targets associated with tumor recurrence through potential ECM-related genes whose overexpression may significantly contribute to tumorigenesis in breast cancer survivors by epithelial-to-mesenchymal transition and targeting them may improve the chances of better survival breast cancer patients and increase the quality of life by reducing the chances of recurrence. However, the study is solely bioinformatics-based; therefore, future study will be experimental validations to bring forth these key genes as potential therapeutic targets.

Changes in the expression of cell interaction-related pathways during brain metastasis in lung adenocarcinoma: Gene expression and immunohistochemical analysis

BACKGROUND

Brain metastasis (BM) is a prevalent prognostic event in the development of lung adenocarcinoma (LUAD) with a poor prognosis. Alterations in gene or protein expression during various phases of BM remain unclear.

METHODS

We performed gene expression and pathway analyses using a metastasis-related gene panel on 12 lung tissues from patients with confirmed BM, 12 lung tissues from patients without BM, and 12 matched brain tissues from patients with confirmed BM during follow-up after LUAD surgery. The results of the gene expression analysis were validated by immunohistochemistry.

RESULTS

Cell interaction-related pathways (such as focal adhesion, extracellular matrix-receptor interaction, and proteoglycans in cancer) showed the greatest differences among the three groups. Expression of the cell interaction-related pathway was highest in the lung sample of BM group and lowest in the matched brain tissue. Using a machine learning model, a signature of 20 genes from cell interaction-related pathways accurately predicted BM (area under the curve score of 0.792 and an accuracy rate of 0.875). Immunohistochemical analysis showed higher expression of proteins associated with cell interaction-related genes and a mesenchymal phenotype in the lung sample of BM group than in those without BM or matched brain tissue.

CONCLUSIONS

LUAD acquires the characteristics of the cell interaction-related pathway that leads to the development of BM, with a significant decrease in expression following brain colonization.

The value of microvascular Doppler ultrasound technique, qualitative or quantitative shear-wave elastography of breast lesions for predicting axillary nodal burden in patients with breast cancer

Background

The status of the axillary lymph node (ALN) in patients with breast cancer can critically inform clinical decision-making and prognosis. Preoperative evaluation of limited nodal burden (0-2 metastatic ALNs) and high nodal burden (≥3 metastatic ALNs) is vital for individual treatment in patients with breast cancer. Thus, this study aimed to evaluate the value of Angio-PLUS (AP; Aixplorer, SuperSonic Imagine) and the qualitative and quantitative shear-wave elastography (SWE) of breast lesions to predict limited or high axillary nodal burden and to develop a model for predicting limited or high axillary nodal burden.

Methods

From March 2020 to November 2022, a total of 232 consecutive patients with breast cancer comprising 232 breast lesions were enrolled retrospectively from Yueyang Central Hospital. The sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), accuracy, and area under the receiver operating characteristic curve (AUC) of AP, qualitative SWE, quantitative SWE, and the predictive model for evaluating limited or high axillary nodal burden were compared.

Results

There was no significant difference in AP patterns between the limited nodal burden group and high nodal burden group. The best cutoff values of Emin (the minimal value of the first Q-box), Emean (the mean value of the first Q-box), Emax (the maximum value of the first Q-box), Eratio (ratio of the first Q-Box and the second Q-Box) and standard deviation for predicting limited or high nodal burden were 80.85 KPa, 133.45 KPa, 153.40 KPa, 9.95, and 19.25 KPa, respectively. The Emax had the highest AUC, and its sensitivity, specificity, PPV, NPV, accuracy, and AUC were 71.64%, 56.36%, 40.00%, 83.04%, 60.78%, and 0.640 [95% confidence interval (CI): 0.575-0.702], respectively. The sensitivity, specificity, PPV, NPV, accuracy, and AUC of seven color patterns for qualitative SWE were 71.64%, 74.55%, 53.33%, 86.62%, 73.71%, and 0.731 (95% CI: 0.669-0.787), respectively, which was significantly higher than all the other quantitative SWE parameters. ALN evaluation in ultrasound and qualitative SWE were independent risk factors for predicting limited or high nodal burden according to a binary logistics regression analysis. The AUC of the predictive model based on independent risk factors was 0.820 (95% CI: 0.765-0.867), which was significantly higher than that of the other independent risk factors.

Conclusions

The seven color patterns in the qualitative SWE of breast lesions were valuable for predicting limited or high nodal burden for patients with breast cancer. Compared with quantitative SWE, qualitative SWE exhibited a better diagnostic performance. Breast lesions present no findings, vertical stripes, and spot patterns were important indicators for limited nodal burden. The predictive model developed in this study could be a simple, noninvasive, and convenient method for predicting limited or high nodal burden, which would be beneficial for clinical decision-making and individual treatment to improve prognosis.

FEATURES OF COL1A1 EXPRESSION IN BREAST CANCER TISSUE OF YOUNG PATIENTS

BACKGROUND

In the last decades, the incidence of breast cancer (BCa) in young women has been increasing steadily. The quantitative indicators of expression of collagen, which play important role in stromal microenvironment, and their association with the age and survival rates of BCa patients have not been yet definitively clarified.

AIM

To investigate the relationship between the COL1A1 gene expression at the mRNA and protein levels in BCa tissue and the clinicopatological features and survival rates of BCa patients of different age groups.

MATERIALS AND METHODS

The study was conducted on the clinical material of 50 patients with stage I-III BCa. COL1A1 gene expression at the mRNA and protein levels in BCa tissue were studied using the real-time PCR and immunohistochemical methods, as well as the bioinformatic analysis (UALCAN and Kaplan - Meier Plotter databases).

RESULTS

The bioinformatic analysis showed that BCa tissue is characterized by 6.0 times (p < 0.05) higher level of COL1A1 mRNA compared to normal breast tissue. The correlation of COL1A1 expression at the mRNA and protein levels with the molecular subtype of neoplasms was demonstrated. According to Kaplan - Meier Plotter database, a low level of expression of COL1A1 protein level in BCa tissue is associated with lower rates of relapse-free survival of patients. The ex vivo study of the clinical material revealed a decrease in COL1A1 protein expression in tumor tissue of young patients with BCa of T3 category (p < 0.0374), low differentiation grade (p < 0.0163) and basal molecular subtype (p < 0.0001). A correlation between the expression of COL1A1 at the mRNA and protein levels and the expression status of estrogen receptors (p < 0.0001) and progesterone receptors (p < 0.0040) was established. The relapse-free 3-year survival rate of young BCa patients is significantly lower in the presence of a low COL1A1 optical density index in the tumor tissue.

CONCLUSIONS

The identified relationship between COL1A1 expression and such indicators of BCa malignancy as tumor size, differentiation grade, molecular subtype, receptor status, and the recurrencefree survival of patients indicates the prospects of its use to predict the aggressiveness of the BCa course in young patients.

Collagen code in tumor microenvironment: Functions, molecular mechanisms, and therapeutic implications

The tumor microenvironment (TME) is crucial in cancer progression, and the extracellular matrix (ECM) is an important TME component. Collagen is a major ECM component that contributes to tumor cell infiltration, expansion, and distant metastasis during cancer progression. Recent studies reported that collagen is deposited in the TME to form a collagen wall along which tumor cells can infiltrate and prevent drugs from working on the tumor cells. Collagen-tumor cell interaction is complex and requires the activation of multiple signaling pathways for biochemical and mechanical signaling interventions. In this review, we examine the effect of collagen deposition in the TME on tumor progression and discuss the interaction between collagen and tumor cells. This review aims to illustrate the functions and mechanisms of collagen in tumor progression in the TME and its role in tumor therapy. The findings indicated collagen in the TME appears to be a better target for cancer therapy.

Exploring the Potential Role of Circulating microRNAs as Biomarkers for Predicting Clinical Response to Neoadjuvant Therapy in Breast Cancer

Breast cancer (BC) is a leading cause of cancer-related deaths among women worldwide. Neoadjuvant therapy (NAT) is increasingly being used to reduce tumor burden prior to surgical resection. However, current techniques for assessing tumor response have significant limitations. Additionally, drug resistance is commonly observed, raising a need to identify biomarkers that can predict treatment sensitivity and survival outcomes. Circulating microRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and have been shown to play a significant role in cancer progression as tumor inducers or suppressors. The expression of circulating miRNAs has been found to be significantly altered in breast cancer patients. Moreover, recent studies have suggested that circulating miRNAs can serve as non-invasive biomarkers for predicting response to NAT. Therefore, this review provides a brief overview of recent studies that have demonstrated the potential of circulating miRNAs as biomarkers for predicting the clinical response to NAT in BC patients. The findings of this review will strengthen future research on developing miRNA-based biomarkers and their translation into medical practice, which could significantly improve the clinical management of BC patients undergoing NAT.