The ratio of cancer cells to stroma after induction therapy in the treatment of non-small cell lung cancer

Serum THBS2 is a potential biomarker for the diagnosis of non-small cell lung cancer

OBJECTIVE

This study primarily aimed to analyze the levels of THBS2 in the serum of patients diagnosed with non-small cell lung cancer (NSCLC), and subsequently evaluate its potential as a diagnostic biomarker for NSCLC.

METHODS

Serum samples were collected from 150 diagnosed NSCLC patients and 150 healthy individuals. The THBS2 concentration in these samples was determined using an enzyme-linked immunosorbent assay (ELISA). The study also investigated the correlation between THBS2 levels and various clinicopathological characteristics in NSCLC patients. The diagnostic sensitivity and specificity of serum THBS2 for NSCLC were assessed using receiver operating characteristic (ROC) curves and their corresponding area under the curve (AUC).

RESULTS

Serum THBS2 levels in NSCLC patients were significantly elevated compared to those in healthy individuals. THBS2 levels showed a significant correlation with tumor differentiation grade, tumor size, TNM stage, lymph node metastasis, and distant metastasis. No significant correlation was identified between serum THBS2 levels and other parameters such as gender, age, height, weight, BMI, smoking history, and tumor histological type. At a cutoff value of 7.62 ng/mL, THBS2 could effectively differentiate NSCLC patients from healthy individuals, with a sensitivity of 85.31% and a specificity of 88.92%. The AUC for NSCLC diagnosis using THBS2 was 0.812, significantly surpassing the performance of traditional tumor markers tested, including CEA (0.728), and CYFRA 21‑1 (0.685).

CONCLUSIONS

Elevated serum THBS2 levels in NSCLC patients suggest its potential as a novel and reliable diagnostic biomarker for NSCLC. Its superior diagnostic performance could potentially outperform traditional tumor markers, leading to improved patient outcomes.

Cancer-associated Fibroblasts in Bladder Cancer: Origin, Biology, and Therapeutic Opportunities

CONTEXT

Bladder cancer (BLCA) is a highly prevalent tumour and a health problem worldwide, especially among men. Recent work has highlighted the relevance of the tumour microenvironment (TME) in cancer biology with translational implications. Cancer-associated fibroblasts (CAFs) are a prominent, heterogeneous population of cells in the TME. CAFs have been associated with tumour development, progression, and poor prognosis in several neoplasms. However, their role in BLCA has not yet been exploited deeply.

OBJECTIVE

To review the role of CAFs in BLCA biology and provide an understanding of CAF origin, subtypes, markers, and phenotypic and functional characteristics to improve patient management.

EVIDENCE ACQUISITION

A PubMed search was performed to review manuscripts published using the terms "cancer associated fibroblast" and "bladder cancer" or "urothelial cancer". All abstracts were reviewed, and the full content of all relevant manuscripts was analysed. In addition, selected manuscripts on CAFs in other tumours were considered.

EVIDENCE SYNTHESIS

CAFs have been studied less extensively in BLCA than in other tumours. Thanks to new techniques, such as single-cell RNA-seq and spatial transcriptomics, it is now possible to accurately map and molecularly define the phenotype of fibroblasts in normal bladder and BLCA. Bulk transcriptomic analyses have revealed the existence of subtypes among both non-muscle-invasive and muscle-invasive BLCA; these subtypes display distinct features regarding their CAF content. We provide a higher-resolution map of the phenotypic diversity of CAFs in these tumour subtypes. Preclinical studies and recent promising clinical trials leverage on this knowledge through the combined targeting of CAFs or their effectors and the immune microenvironment.

CONCLUSIONS

Current knowledge of BLCA CAFs and the TME is being increasingly applied to improve BLCA therapy. There is a need to acquire a deeper understanding of CAF biology in BLCA.

PATIENT SUMMARY

Tumour cells are surrounded by nontumoural cells that contribute to the determination of the behaviour of cancers. Among them are cancer-associated fibroblasts. The "neighbourhoods" established through these cellular interactions can now be studied with much greater resolution. Understanding these features of tumours will contribute to the designing of more effective therapies, especially in relationship to bladder cancer immunotherapy.

Determinants and Functions of CAFs Secretome During Cancer Progression and Therapy

Multiple lines of evidence are indicating that cancer development and malignant progression are not exclusively epithelial cancer cell-autonomous processes but may also depend on crosstalk with the surrounding tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are abundantly represented in the TME and are continuously interacting with cancer cells. CAFs are regulating key mechanisms during progression to metastasis and response to treatment by enhancing cancer cells survival and aggressiveness. The latest advances in CAFs biology are pointing to CAFs-secreted factors as druggable targets and companion tools for cancer diagnosis and prognosis. Especially, extensive research conducted in the recent years has underscored the potential of several cytokines as actionable biomarkers that are currently evaluated in the clinical setting. In this review, we explore the current understanding of CAFs secretome determinants and functions to discuss their clinical implication in oncology.

Review of cancer-associated fibroblasts and their microenvironment in post-chemotherapy recurrence

Cancer tissue comprises not only cancer cells, but also several types of non-cancerous cells, such as cancer-associated fibroblasts. These fibroblasts directly and/or indirectly communicate with the cancer cells and other types of stromal cells, to create a specific tumor microenvironment. Cytotoxic chemotherapy plays a central role in treating cancer; however, tumor re-progression (recurrence) is a significant problem for cancer patients. Cytotoxic anticancer drugs act on fibroblasts as well as cancer cells and, after chemotherapy, all surviving cells are in contact with one another in the local environment. Therefore, an understanding of the molecular interactions between surviving cancer cells and fibroblasts is necessary to prevent tumor re-progression and to sustain the effect of cytotoxic agents. After chemotherapy, the number of fibroblasts may increase, some of which are identifiable as tumor-promoting. In this review, we discuss the significance of cancer-associated fibroblasts in tumor re-progression after chemotherapy, and the potential value of targeting them to enhance clinical outcomes.

Enhanced prognostic stratification of neoadjuvant treated lung squamous cell carcinoma by computationally-guided tumor regression scoring

INTRODUCTION

The amount of residual tumor burden after neoadjuvant chemotherapy is an important prognosticator, but for non-small cell lung carcinoma (NSCLC), no official regression scoring system is yet established. Computationally derived histological regression scores could provide unbiased and quantitative readouts to complement the clinical assessment of treatment response.

METHODS

Histopathologic tumor regression was microscopically assessed on whole cases in a neoadjuvant chemotherapy-treated cohort (NAC, n = 55 patients) of lung squamous cell carcinomas (LSCC). For each patient, the slide showing the least pathologic regression was selected for subsequent computational analysis and histological features were quantified: percentage of vital tumor cells (cTu.Percentage), total surface covered by vital tumor cells (cTu.Area), area of the largest vital tumor fragment (cTu.Size.max), and total number of vital tumor fragments (cTu.Fragments). A chemo-naïve LSCC cohort (CN, n = 104) was used for reference. For 23 of the 55 patients [¹⁸F]-Fluorodeoxyglucose (FDG) PET/CT measurements of maximum standard uptake value (SUV_max), background subtracted lesion activity (BSL) and background subtracted volume (BSV) were correlated with pathologic regression. Survival analysis was carried out using Cox regression and receiver operating characteristic (ROC) curve analysis using a 3-years cutoff.

RESULTS

All computational regression parameters significantly correlated with relative changes of BSV FDG PET/CT values after neoadjuvant chemotherapy. ROC curve analysis of histological parameters of NAC patients showed that cTu.Percentage was the most accurate prognosticator of overall survival (ROC curve AUC = 0.77, p-value = 0.001, Cox regression HR = 3.6, p = 0.001, variable cutoff < = 30 %).

CONCLUSIONS

This study demonstrates the prognostic relevance of computer-derived histopathologic scores. Additionally, the analysis carried out on slides displaying the least pathologic regression correlated with overall pathologic response and PET/CT values. This might improve the objective histopathologic assessment of tumor response in neoadjuvant setting.