Tumor-stroma ratio (TSR) in non-small cell lung cancer (NSCLC) patients after lung resection is a prognostic factor for survival

The proportion of tumour stroma predicts response to treatment of immune checkpoint inhibitor in combination with chemotherapy in patients with stage IIIB-IV non-small cell lung cancer

AIMS

Immunotherapy has brought a new era to cancer treatment, yet we lack dependable predictors for its effectiveness. This study explores the predictive significance of intratumour stroma proportion (iTSP) for treatment success and prognosis in non-small cell lung cancer (NSCLC) patients undergoing treatment with immune check-point inhibitors (ICIs) together with chemotherapy.

METHODS AND RESULTS

We retrospectively collected data from patients with unresectable stage IIIB-IV NSCLC who were treated with first-line ICIs and chemotherapy. Each patient received a confirmed pathological diagnosis, and the pathologist evaluated the iTSP on haematoxylin and eosin (H&E)-stained sections of diagnostic tissue slides. Among the 102 H&E-stained biopsy samples, 61 (59.8%) were categorised as stroma-L (less than 50% iTSP), while 41 (40.2%) were classified as stroma-H (more than 50% iTSP). We observed that the stroma-L group exhibited a significantly better objective response rate (ORR) (72.1 versus 51.2%, P = 0.031) and deeper response depth (DpR) (-50.49 ± 28.79% versus -35.83 ± 29.91%, P = 0.015) compared to the stroma-H group. Furthermore, the stroma-L group showed longer median progression-free survival (PFS) (9.6 versus 6.0 months, P = 0.011) and overall survival (OS) (24.0 versus 12.2 months, P = 0.001) compared to the stroma-H group. Multivariate Cox proportional hazards regression analysis indicated that iTSP was a highly significant prognostic factor for both PFS [hazard ratio (HR) = 1.713; P = 0.030] and OS (HR = 2.225; P = 0.003).

CONCLUSION

Our findings indicate that a lower iTSP corresponds to improved clinical outcomes and greater DpR in individuals with stage IIIB-IV NSCLC treated with first-line ICIs and chemotherapy. The iTSP could potentially serve as a predictive biomarker for ICIs therapy response.

Tumor Characteristics and Treatment Responsiveness in Pembrolizumab-Treated Non-Small Cell Lung Carcinoma

Pembrolizumab, a widely used immune checkpoint inhibitor (ICI), has revolutionized the treatment of non-small cell lung cancer (NSCLC). Identifying unique tumor characteristics in patients likely to respond to pembrolizumab could help the clinical adjudication and development of a personalized therapeutic strategy. In this retrospective study, we reviewed the clinical data and pathological features of 84 NSCLC patients treated with pembrolizumab. We examined the correlation between the clinical and demographic characteristics and the tumor histopathologic features obtained before immunotherapy. The response to pembrolizumab therapy was evaluated via the Response Evaluation Criteria in Solid Tumors (RECIST). The clinical data and cancer tissue characteristics were assessed and compared among three groups according to the following RECIST: the responsive group (RG), the stable disease group (SD), and the progressive disease group (PD), where the RG comprised patients with either a complete response (CR) or a partial response (PR). The overall survival rate of the RG group was significantly higher than the SD and PD groups. In addition, the percentage of pre-treatment viable tumor cell content in the RG and SD groups was significantly higher. At the same time, the extracellular stroma proportion was significantly lower than that of the PD group. The number of tumor-infiltrating lymphocytes (TILs) in the RG group was significantly higher than in the PD group. There were no significant differences in tumor necrosis, the stroma composition, PD-L1 expression level (TPS 1-49% vs. ≥50%), and treatment response. In conclusion, our population of NSCLC patients who experienced positive treatment responses to pembrolizumab therapy had a better prognosis compared to patients with either SD or PD. Moreover, the relative proportions of viable tumor cells to tumor-associated lymphocytes were associated with responsiveness to treatment. It is expected that larger prospective clinical studies will further validate these findings.

Prognostic value and tumour microenvironment characteristics of the Glasgow Microenvironment Score in primary triple-negative breast cancer

AIMS

The Glasgow Microenvironment Score (GMS) reflects the tumour microenvironment (TME) status by combining inflammatory cell infiltration and the tumour-stroma percentage. This study aimed to investigate the prognostic value and TME characteristics of the GMS for patients with triple-negative breast cancer (TNBC).

METHODS

A total of 123 patients with stage I-III TNBC were enrolled in this study. The association between GMS and clinicopathological characteristics was examined using the Pearson's χ2 test or Fisher's exact test. Kaplan-Meier plots were used to compare survival among the three GMS groups. Cox regression analyses were conducted to test the HR. Microenvironment Cell Populations-counter algorithm was used to estimate the TME components of each case.

RESULTS

We found that higher GMS score tended to exhibit the lower nuclear grade (p=0.016), more positive lymph nodes (p=0.014) and later tumour, node, metastases stage (p=0.012). GMS was an independent prognostic factor for disease-free survival in TNBC, and GMS 2 showed the worst prognosis (HR=6.42, p=0.028). GMS 0 was more infiltrated with cytotoxic lymphocytes, including CD8+ T cells (p=0.037) and natural killer cells (p=0.005), while GMS 2 was enriched in more endothelial cells (p=0.014) and fibroblasts (p=0.008).

CONCLUSION

Our study suggested that the GMS is a prognostic indicator for patients with TNBC. As an accessible and effective index, the GMS may be a promising tool to help clinicians assess prognostic risk and TME for patients with TNBC.

Significance of Tumor-Stroma Ratio (TSR) in Predicting Outcomes of Malignant Tumors

Background and Objectives: The present study aimed to elucidate the distribution and the prognostic implications of tumor-stroma ratio (TSR) in various malignant tumors through a meta-analysis. Materials and Methods: This meta-analysis included 51 eligible studies with information for overall survival (OS) or disease-free survival (DFS), according to TSR. In addition, subgroup analysis was performed based on criteria for high TSR. Results: The estimated rate of high TSR was 0.605 (95% confidence interval (CI) 0.565-0.644) in overall malignant tumors. The rates of high TSR ranged from 0.276 to 0.865. The highest rate of high TSR was found in endometrial cancer (0.865, 95% CI 0.827-0.895). The estimated high TSR rates of colorectal, esophageal, and stomach cancers were 0.622, 0.529, and 0.448, respectively. In overall cases, patients with high TSR had better OS and DFS than those with low TSR (hazard ratio (HR) 0.631, 95% CI 0.542-0.734, and HR 0.564, 95% CI 0.0.476-0.669, respectively). Significant correlations with OS were found in the breast, cervical, colorectal, esophagus, head and neck, ovary, stomach, and urinary tract cancers. In addition, there were significant correlations of DFS in breast, cervical, colorectal, esophageal, larynx, lung, and stomach cancers. In endometrial cancers, high TSR was significantly correlated with worse OS and DFS. Conclusions: The rate of high TSR was different in various malignant tumors. TSR can be useful for predicting prognosis through a routine microscopic examination of malignant tumors.

Pre-clinical modelling of ROS1+ non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a heterogeneous group of diseases which accounts for 80% of newly diagnosed lung cancers. In the previous decade, a new molecular subset of NSCLC patients (around 2%) harboring rearrangements of the c-ros oncogene 1 was defined. ROS1+ NSCLC is typically diagnosed in young, nonsmoker individuals presenting an adenocarcinoma histology. Patients can benefit from tyrosine kinase inhibitors (TKIs) such as crizotinib and entrectinib, compounds initially approved to treat ALK-, MET- or NTRK- rearranged malignancies respectively. Given the low prevalence of ROS1-rearranged tumors, the use of TKIs was authorized based on pre-clinical evidence using limited experimental models, followed by basket clinical trials. After initiating targeted therapy, disease relapse is reported in approximately 50% of cases as a result of the appearance of resistance mechanisms. The restricted availability of TKIs active against resistance events critically reduces the overall survival. In this review we discuss the pre-clinical ROS1+ NSCLC models developed up to date, highlighting their strengths and limitations with respect to the unmet clinical needs. By combining gene-editing tools and novel cell culture approaches, newly developed pre-clinical models will enhance the development of next-generation tyrosine kinase inhibitors that overcome resistant tumor cell subpopulations.

Machine Learning Quantified Tumor-Stroma Ratio Is an Independent Prognosticator in Muscle-Invasive Bladder Cancer

Although the tumor-stroma ratio (TSR) has prognostic value in many cancers, the traditional semi-quantitative visual assessment method has inter-observer variability, making it impossible for clinical practice. We aimed to develop a machine learning (ML) algorithm for accurately quantifying TSR in hematoxylin-and-eosin (H&E)-stained whole slide images (WSI) and further investigate its prognostic effect in patients with muscle-invasive bladder cancer (MIBC). We used an optimal cell classifier previously built based on QuPath open-source software and ML algorithm for quantitative calculation of TSR. We retrospectively analyzed data from two independent cohorts to verify the prognostic significance of ML-based TSR in MIBC patients. WSIs from 133 MIBC patients were used as the discovery set to identify the optimal association of TSR with patient survival outcomes. Furthermore, we performed validation in an independent external cohort consisting of 261 MIBC patients. We demonstrated a significant prognostic association of ML-based TSR with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TSR associated with better prognosis. Uni- and multivariate Cox regression analyses showed that TSR was independently associated with overall survival (p < 0.001 for all analyses) after adjusting for clinicopathological factors including age, gender, and pathologic stage. TSR was found to be a strong prognostic factor that was not redundant with the existing staging system in different subgroup analyses (p < 0.05 for all analyses). Finally, the expression of six genes (DACH1, DEEND2A, NOTCH4, DTWD1, TAF6L, and MARCHF5) were significantly associated with TSR, revealing possible potential biological relevance. In conclusion, we developed an ML algorithm based on WSIs of MIBC patients to accurately quantify TSR and demonstrated its prognostic validity for MIBC patients in two independent cohorts. This objective quantitative method allows application in clinical practice while reducing the workload of pathologists. Thus, it might be of significant aid in promoting precise pathology services in MIBC.

Integrated spatial analysis of gene mutation and gene expression for understanding tumor diversity in formalin-fixed paraffin-embedded lung adenocarcinoma

Introduction

A deeper understanding of intratumoral heterogeneity is essential for prognosis prediction or accurate treatment plan decisions in clinical practice. However, due to the cross-links and degradation of biomolecules within formalin-fixed paraffin-embedded (FFPE) specimens, it is challenging to analyze them. In this study, we aimed to optimize the simultaneous extraction of mRNA and DNA from microdissected FFPE tissues (φ = 100 µm) and apply the method to analyze tumor diversity in lung adenocarcinoma before and after erlotinib administration.

Method

Two magnetic beads were used for the simultaneous extraction of mRNA and DNA. The decross-linking conditions were evaluated for gene mutation and gene expression analyses of microdissected FFPE tissues. Lung lymph nodes before treatment and lung adenocarcinoma after erlotinib administration were collected from the same patient and were preserved as FFPE specimens for 4 years. Gene expression and gene mutations between histologically classified regions of lung adenocarcinoma (pre-treatment tumor in lung lymph node biopsies and post-treatment tumor, normal lung, tumor stroma, and remission stroma, in resected lung tissue) were compared in a microdissection-based approach.

Results

Using the optimized simultaneous extraction of DNA and mRNA and whole-genome amplification, we detected approximately 4,000-10,000 expressed genes and the epidermal growth factor receptor (EGFR) driver gene mutations from microdissected FFPE tissues. We found the differences in the highly expressed cancer-associated genes and the positive rate of EGFR exon 19 deletions among the tumor before and after treatment and tumor stroma, even though they were collected from tumors of the same patient or close regions of the same specimen.

Conclusion

Our integrated spatial analysis method would be applied to various FFPE pathology specimens providing area-specific gene expression and gene mutation information.

Smoking-associated Downregulation of FILIP1L Enhances Lung Adenocarcinoma Progression Through Mucin Production, Inflammation, and Fibrosis

Lung adenocarcinoma (LUAD) is the major subtype in lung cancer, and cigarette smoking is essentially linked to its pathogenesis. We show that downregulation of Filamin A interacting protein 1-like (FILIP1L) is a driver of LUAD progression. Cigarette smoking causes its downregulation by promoter methylation in LUAD. Loss of FILIP1L increases xenograft growth, and, in lung-specific knockout mice, induces lung adenoma formation and mucin secretion. In syngeneic allograft tumors, reduction of FILIP1L and subsequent increase in its binding partner, prefoldin 1 (PFDN1) increases mucin secretion, proliferation, inflammation, and fibrosis. Importantly, from the RNA-sequencing analysis of these tumors, reduction of FILIP1L is associated with upregulated Wnt/β-catenin signaling, which has been implicated in proliferation of cancer cells as well as inflammation and fibrosis within the tumor microenvironment. Overall, these findings suggest that down-regulation of FILIP1L is clinically relevant in LUAD, and warrant further efforts to evaluate pharmacologic regimens that either directly or indirectly restore FILIP1L-mediated gene regulation for the treatment of these neoplasms.

Significance

This study identifies FILIP1L as a tumor suppressor in LUADs and demonstrates that downregulation of FILIP1L is a clinically relevant event in the pathogenesis and clinical course of these neoplasms.

Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

BACKGROUND

Despite the fact that tumor microenvironment (TME) and gene mutations are the main determinants of progression of the deadliest cancer in the world - lung cancer, their interrelations are not well understood. Digital pathology data provides a unique insight into the spatial composition of the TME. Various spatial metrics and machine learning approaches were proposed for prediction of either patient survival or gene mutations from this data. Still, these approaches are limited in the scope of analyzed features and in their explainability, and as such fail to transfer to clinical practice.

METHODS

Here, we generated 23,199 image patches from 26 hematoxylin-and-eosin (H&E)-stained lung cancer tissue sections and annotated them into 9 different tissue classes. Using this dataset, we trained a deep neural network ARA-CNN. Next, we applied the trained network to segment 467 lung cancer H&E images from The Cancer Genome Atlas (TCGA) database. We used the segmented images to compute human-interpretable features reflecting the heterogeneous composition of the TME, and successfully utilized them to predict patient survival and cancer gene mutations.

RESULTS

We achieved per-class AUC ranging from 0.72 to 0.99 for classifying tissue types in lung cancer with ARA-CNN. Machine learning models trained on the proposed human-interpretable features achieved a c-index of 0.723 in the task of survival prediction and AUC up to 73.5% for PDGFRB in the task of mutation classification.

CONCLUSIONS

We presented a framework that accurately predicted survival and gene mutations in lung adenocarcinoma patients based on human-interpretable features extracted from H&E slides. Our approach can provide important insights for designing novel cancer treatments, by linking the spatial structure of the TME in lung adenocarcinoma to gene mutations and patient survival. It can also expand our understanding of the effects that the TME has on tumor evolutionary processes. Our approach can be generalized to different cancer types to inform precision medicine strategies.

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.

Spread Through Air Spaces (STAS) Is an Independent Prognostic Factor in Resected Lung Squamous Cell Carcinoma

Objective: There is no histoprognostic grading for lung squamous cell carcinoma (LUSC). Different prognostic factors have been described in the recent literature and are not always studied in parallel. Our objective was to search for morphological histopathological prognostic factors in LUSC. Materials and Methods: In this single-center retrospective study of 241 patients, all patients with LUSC who underwent surgical excision over a 12-year period were included. The primary endpoint was 5-year overall survival. Results: STAS was present in 86 (35.7%) patients. The presence of Spread Through Air Spaces (STAS) was correlated with tumor location (p < 0.001), pathological stage (p = 0.039), tumor differentiation (p = 0.029), percentage of necrosis (p = 0.004), presence of vascular and/or lymphatic emboli, budding (p = 0.02), single cell invasion (p = 0.002) and tumor nest size (p = 0.005). The percentage of tumor necrosis was correlated with the overall survival at 5 years: 44.6% of patients were alive when the percentage of necrosis was ≥50%, whereas 68.5% were alive at 5 years when the necrosis was <30% (p < 0.001). When vasculolymphatic emboli were present, the percentage of survival at 5 years was 42.5% compared to 65.5% when they were absent (p = 0.002). The presence of isolated cell invasion was correlated with a lower 5-year survival rate: 51.1% in the case of presence, versus 66% in the case of absence (p = 0.02). In univariate analysis, performance status, pathological stage pT or pN, pleural invasion, histopathological subtype, percentage of tumor necrosis, vasculolymphatic invasion, single-cell invasion, budding and tumor nest size correlated with the percentage of survival at 5 years. On multivariate analysis, only STAS > 3 alveoli (HR, 2.74; 95% CI, 1.18−6.33) was related to overall survival. Conclusion: In conclusion, extensive STAS is an independent factor of poor prognosis in LUSC. STAS is correlated with the presence of other poor prognostic factors such as emboli and pleural invasion and would reflect greater tumor aggressiveness.

Predictive value of collagen in cancer

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.

Standardization of the tumor-stroma ratio scoring method for breast cancer research

Purpose

The tumor-stroma ratio (TSR) has repeatedly proven to be correlated with patient outcomes in breast cancer using large retrospective cohorts. However, studies validating the TSR often show variability in methodology, thereby hampering comparisons and uniform outcomes.

Method

This paper provides a detailed description of a simple and uniform TSR scoring method using Hematoxylin and Eosin (H&E)-stained core biopsies and resection tissue, specifically focused on breast cancer. Possible histological challenges that can be encountered during scoring including suggestions to overcome them are reported. Moreover, the procedure for TSR estimation in lymph nodes, scoring on digital images and the automatic assessment of the TSR using artificial intelligence are described.

Conclusion

Digitized scoring of tumor biopsies and resection material offers interesting future perspectives to determine patient prognosis and response to therapy. The fact that the TSR method is relatively easy, quick, and cheap, offers great potential for its implementation in routine diagnostics, but this requires high quality validation studies.

Predictive Role of Tumor-Stroma Ratio for Survival of Patients With Non-Small Cell Lung Cancer: A Meta-Analysis

Background: Role of tumor-stroma ratio (TSR) as a predictor of survival in patients with non-small cell lung cancer (NSCLC) remains not clear. A systematic review and meta-analysis was conducted to summarize current evidence for the role of TSR in NSCLC.

Methods: Relevant cohort studies were retrieved via search of Medline, Embase, and Web of Science databases. The data was combined with a random-effect model by incorporating the between-study heterogeneity. Specifically, subgroup and meta-regression analyses were performed to explore the association between TSR and survival in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC).

Results: Nine cohort studies with 2031 patients with NSCLC were eligible for the meta-analysis. Pooled results showed that compared to those stroma-poor tumor, patients with stroma rich NSCLC were associated with worse recurrence-free survival (RFS, hazard ratio [HR] = 1.52, 95% confidence interval [CI]: 1.07 to 2.16, p = 0.02) and overall survival (OS, HR = 1.48, 95% CI: 1.20 to 1.82, p < 0.001). Subgroup analyses showed that stroma-rich tumor may be associated with a worse survival of SCC (HR = 1.89 and 1.47 for PFS and OS), but a possibly favorable survival of AC (HR = 0.28 and 0.69 for PFS and OS). Results of meta-regression analysis also showed that higher proportion of patients with SCC was correlated with higher HRs for RFS (Coefficient = 0.012, p = 0.03) and OS (Coefficient = 0.014, p = 0.02) in the included patients, while higher proportion of patients with AC was correlated with lower HRs for RFS (Coefficient = −0.012, p = 0.03) and OS (Coefficient = −0.013, p = 0.04), respectively.

Conclusion: Tumor TSR could be used as a predictor of survival in patients with NSCLC. The relative proportion of patients with SCC/AC in the included NSCLC patients may be an important determinant for the association between TSR and survival in NSCLC. Stroma richness may be a predictor of poor survival in patients with lung SCC, but a predictor of better survival in patients with lung AC.

Low Tumor-to-Stroma Ratio Reflects Protective Role of Stroma against Prostate Cancer Progression

Tumor-to-stroma ratio (TSR) is a prognostic factor that expresses the relative amounts of tumor and intratumoral stroma. In this study, its clinical and molecular relevance was evaluated in prostate cancer (PCa). The feasibility of automated quantification was tested in digital scans of tissue microarrays containing 128 primary tumors from 72 PCa patients stained immunohistochemically for epithelial cell adhesion molecule (EpCAM), followed by validation in a cohort of 310 primary tumors from 209 PCa patients. In order to investigate the gene expression differences between tumors with low and high TSR, we applied multigene expression analysis (nCounter® PanCancer Progression Panel, NanoString) of 42 tissue samples. TSR scores were categorized into low (<1 TSR) and high (≥1 TSR). In the pilot cohort, 31 patients (43.1%) were categorized as low and 41 (56.9%) as high TSR score, whereas 48 (23.0%) patients from the validation cohort were classified as low TSR and 161 (77.0%) as high. In both cohorts, high TSR appeared to indicate the shorter time to biochemical recurrence in PCa patients (Log-rank test, p = 0.04 and p = 0.01 for the pilot and validation cohort, respectively). Additionally, in the multivariate analysis of the validation cohort, TSR predicted BR independent of other factors, i.e., pT, pN, and age (p = 0.04, HR 2.75, 95%CI 1.07-7.03). Our data revealed that tumors categorized into low and high TSR score show differential expression of various genes; the genes upregulated in tumors with low TSR score were mostly associated with extracellular matrix and cell adhesion regulation. Taken together, this study shows that high stroma content can play a protective role in PCa. Automatic EpCAM-based quantification of TSR might improve prognostication in personalized medicine for PCa.

Lung-Resident Mesenchymal Stem Cell Fates within Lung Cancer

Simple Summary

Lung cancer remains the leading cause of cancer-related deaths worldwide. Herein, the heterogeneous tumor stroma decisively impacts on tumor progression, therapy resistance, and, thus, poor clinical outcome. Among the numerous non-epithelial cells constructing the complex environment of lung carcinomas, mesenchymal stem cells (MSC) gained attraction being stromal precursor cells that could be recruited and ‘educated’ by lung cancer cells to adopt a tumor-associated MSC phenotype, serve as source for activated fibroblasts and presumably for vascular mural cells finally reinforcing tumor progression. Lung-resident MSCs should be considered as ‘local MSCs in stand by’ ready to be arranged within the cancer stroma.

Abstract

Lung-resident mesenchymal stem cells (LR-MSCs) are non-hematopoietic multipotent stromal cells that predominately reside adventitial within lung blood vessels. Based on their self-renewal and differentiation properties, LR-MSCs turned out to be important regulators of normal lung homeostasis. LR-MSCs exert beneficial effects mainly by local secretion of various growth factors and cytokines that in turn foster pulmonary regeneration including suppression of inflammation. At the same time, MSCs derived from various tissues of origins represent the first choice of cells for cell-based therapeutic applications in clinical medicine. Particularly for various acute as well as chronic lung diseases, the therapeutic applications of exogenous MSCs were shown to mediate beneficial effects, hereby improving lung function and survival. In contrast, endogenous MSCs of normal lungs seem not to be sufficient for lung tissue protection or repair following a pathological trigger; LR-MSCs could even contribute to initiation and/or progression of lung diseases, particularly lung cancer because of their inherent tropism to migrate towards primary tumors and metastatic sites. However, the role of endogenous LR-MSCs to be multipotent tumor-associated (stromal) precursors remains to be unraveled. Here, we summarize the recent knowledge how ‘cancer-educated’ LR-MSCs impact on lung cancer with a focus on mesenchymal stem cell fates.

Assessment of Histological Features in Squamous Cell Carcinoma Involving Head and Neck Skin and Mucosa

BACKGROUND

squamous cell carcinoma (SCC) is the second most common type of malignancy worldwide. Skin and mucosa of the head and neck areas are the most frequently affected. An aggressive behavior in SCC is not easily detected, and despite all efforts, mortality in these types of cancer did not show major improvements during recent decades. In this study, we aim to determine the role of histological features available through standard pathology assessment in SCC and their relation with tumor behavior and patients' survival.

METHOD

in a group of one hundred patients diagnosed with SCC involving the head and neck areas, we assessed the presence of four histological features (tumor/stroma ratio, immune infiltration at the front of invasion, tumor-budding activity, and tumor necrosis), their correlations with tumor type (mucosal or cutaneous), tumor clinicopathological characteristics, and their prognostic potential.

RESULTS

the comparison between histological features in cutaneous versus mucosal SCC reveals no significant differences for any of the four parameters assessed. We found significant correlations between tumor/stroma ratio and lymphatic metastasis (p = 0.0275), perineural invasion (p = 0.0006), and clinical staging (p = 0.0116). Immune infiltration at the front of invasion revealed similar correlations with lymph node involvement (p = 0.002), perineural invasion (p = 0.0138), and clinical staging (p = 0.0043). Tumor budding and tumor necrosis correlated with the size of the tumor (p = 0.0077 and p = 0.0004) and the clinical staging (p = 0.0039 and p = 0.0143). In addition, tumor budding was significantly correlated with perineural invasion (p = 0.0454). In mucosal SCC, patients with improved outcome revealed high values for the tumor/stroma ratio (p = 0.0159) and immune infiltration at the front of invasion (p = 0.0274). However, the multivariate analysis did not confirm their independent prognostic roles.

CONCLUSIONS

extended histological assessments that include features such as tumor/stroma ratio, immune infiltration at the front of invasion, tumor budding, and tumor necrosis can be an easy, accessible method to collect additional information on tumor aggressiveness in skin and mucosa SCC affecting the head and neck areas.

Apoptosis mapping in space and time of 3D tumor ecosystems reveals transmissibility of cytotoxic cancer death

The emerging tumor-on-chip (ToC) approaches allow to address biomedical questions out of reach with classical cell culture techniques: in biomimetic 3D hydrogels they partially reconstitute ex vivo the complexity of the tumor microenvironment and the cellular dynamics involving multiple cell types (cancer cells, immune cells, fibroblasts, etc.). However, a clear bottleneck is the extraction and interpretation of the rich biological information contained, sometime hidden, in the cell co-culture videos. In this work, we develop and apply novel video analysis algorithms to automatically measure the cytotoxic effects on human cancer cells (lung and breast) induced either by doxorubicin chemotherapy drug or by autologous tumor-infiltrating cytotoxic T lymphocytes (CTL). A live fluorescent dye (red) is used to selectively pre-stain the cancer cells before co-cultures and a live fluorescent reporter for caspase activity (green) is used to monitor apoptotic cell death. The here described open-source computational method, named STAMP (spatiotemporal apoptosis mapper), extracts the temporal kinetics and the spatial maps of cancer death, by localizing and tracking cancer cells in the red channel, and by counting the red to green transition signals, over 2-3 days. The robustness and versatility of the method is demonstrated by its application to different cell models and co-culture combinations. Noteworthy, this approach reveals the strong contribution of primary cancer-associated fibroblasts (CAFs) to breast cancer chemo-resistance, proving to be a powerful strategy to investigate intercellular cross-talks and drug resistance mechanisms. Moreover, we defined a new parameter, the 'potential of death induction', which is computed in time and in space to quantify the impact of dying cells on neighbor cells. We found that, contrary to natural death, cancer death induced by chemotherapy or by CTL is transmissible, in that it promotes the death of nearby cancer cells, suggesting the release of diffusible factors which amplify the initial cytotoxic stimulus.

p62-Induced Cancer-Associated Fibroblast Activation via the Nrf2-ATF6 Pathway Promotes Lung Tumorigenesis

Cancer-associated fibroblasts (CAFs) are important in tumor progression. The autophagy adaptor protein, p62/SQSTM1/Sequestosome-1, is up-regulated in tumors, but down-regulated in CAFs in the early stages of lung adenocarcinoma. We investigated whether p62-induced autophagy might control CAF activation. Under CAF-inducing conditions, like hypoxia or cancer cell co-cultures, p62 ablation or autophagy inhibition with hydroxychloroquine (HCQ) impaired CAF activation and reduced transforming growth factor beta (TGFβ) production, which impeded tumor growth. During CAF activation, p62-induced autophagy up-regulated the expression of the anti-oxidant signaling protein, nuclear factor erythroid 2-related factor 2 (Nrf2), and the ER-stress response regulator, activating transcription factor 6 (ATF6). Genetically or pharmacologically inhibiting the Nrf2-ATF6 pathway totally blocked CAF activation and tumor progression. These results demonstrate that p62 is a key modulator of primary lung adenocarcinoma progression. Thus, targeting the p62-Nrf2 autophagy signaling pathway might be a novel, stroma-focused, cancer prevention and/or treatment strategy.

The prognostic value of tumor-stromal ratio combined with TNM staging system in esophagus squamous cell carcinoma

Background: Tumor stroma is a crucial component of the tumor environment that interacted with tumor cells and modulated tumor cell proliferation, immune evasion, and metastasis. Tumor-stromal ratio (TSR) has been confirmed as an influential independent prognostic factor for diverse types of cancer, but it was seldom discussed in esophagus squamous cell carcinoma (ESCC). Methods: In present study, pathological sections from the most invasive part of the ESCC of 270 patients were analyzed for their TSR by visual inspection and software. The TSR was combined with the TNM staging system to further explain its predictive value of prognosis. The 57 cases ESCC from TCGA database also were included as an independently validated cohort. Results: Our results indicated that TSR was a robust prognostic factor for ESCC patients. TSR by visual inspection was dependable to reflect the stroma percent of the tumor compared to software calculation. Compared with stroma-low groups, the risk of death increased by 153.1% for patients in the stroma-high group [HR=2.531 (95%CI 1.657-3.867), P<0.001]. The results of ROC analysis in two cohorts indicated that TSNM staging system had better resolving ability with the largest area under the curve [0.698 95%CI (0.635-0.760), 0.691 95%CI (0.555-0.807)], compare to TNM. The novel TSNM staging system revealed strong predictive performance (P<0.001). Conclusion: TSR was a reliable dependent indicator for ESCC prognosis. The TSNM staging system has a better discriminative ability than the conventional TNM staging system, especially for III stage patients.

Secretome of Activated Fibroblasts Induced by Exosomes for the Discovery of Biomarkers in Non-Small Cell Lung Cancer

Molecules involved in crosstalk between tumor cells and fibroblasts play vital roles in tumor progression. Extracellular matrix proteins, whose abundance is altered after being affected by tumor-derived exosomes, possess considerable promise as biomarkers for diagnosis or prognosis. In this study, quantitative proteomics is employed to determine the abundance of proteins secreted by normal fibroblasts and exosome-activated fibroblasts, which first identify differentially secreted proteins affected by lung cancer cell-derived exosomes. Based on the differentially secreted proteins and multiple independent datasets comprising 1897 patient samples with non-small cell lung carcinoma or other lung diseases, a diagnostic marker is identified that can effectively distinguish tumor tissues from normal tissue, as well as tumor-associated stroma from normal stroma, and a five-gene prognostic signature is presented with independent prognostic impact to identify patients who may require further adjuvant therapy after surgical resection. In addition, the secretome provides novel potential targets for clinical treatment.

Concurrent Comparison of the Prognostic Values of Tumor Budding, Tumor Stroma Ratio, Tumor Infiltrating Pattern and Lymphocyte-to-Monocyte Ratio in Colorectal Cancer Patients

Objectives: Tumor budding (TB), tumor stroma ratio (TSR), tumor infiltrating pattern (TIP), and preoperative lymphocyte-to-monocyte ratio (LMR) were previously reported to be useful prognostic factors in colorectal cancer (CRC); however, the correlation among these markers and their individual prognostic potency have not been extensively studied. Methods: A cohort of 147 stage I-IV CRC patients was obtained retrospectively, and the patients were divided into subgroups based on low or high TB/TSR/LMR, TIPa (expansile + intermediate) and TIPb (infiltrative) values. The differences in relapse-free survival (RFS) and overall survival (OS) intervals among these subgroups were determined by Kaplan-Meier analysis followed by log-rank tests. The Cox proportional hazard model was applied for the univariate and multivariate analysis of RFS and OS rates. Results:TB, TIP, and LMR, but not TSR, are useful markers for predicting patient survival. Patients with a poor histological grade and large tumor diameter were more likely to present with high TB, TIPb, and low LMR values; in addition, those with advanced T, N, and TNM stages and elevated preoperative CA199 levels had high TB and TIPb levels. TB, TIP, and LMR were significant prognostic factors for the RFS (TB: HR [hazard ratio] = 2.28, 95% CI = 1.30-4.00, P < .01; TIP: HR = 2.60, 95% CI = 1.46-4.60, P < .01; LMR: HR = 0.79, 95% CI = 0.65-0.96, P = .02) and OS (TB: HR = 2.43, 95% CI = 1.32-4.48, P < .01; TIP: HR = 2.49, 95% CI = 1.34-4.63, P < .01; LMR: HR = 0.79, 95% CI = 0.64-0.98, P = .03) intervals. In addition, TB and LMR were independent prognostic factors for the RFS interval (TB: HR = 1.80, 95% CI = 1.01-3.19, P = .05; LMR: HR = 0.80, 95% CI = 0.67-0.96, P = .01), but only LMR was an independent factor for OS rates (HR = 0.80, 95% CI = 0.65-0.98, P = .03). Conclusion: Although TB, TIP, and LMR are useful prognostic markers for CRC, the LMR is likely to be the only independent prognostic factor for both RFS and OS outcomes in practice.

CD109 regulates in vivo tumor invasion in lung adenocarcinoma through TGF-β signaling

Stromal invasion is considered an important prognostic factor in patients with lung adenocarcinoma. The mechanisms underlying the formation of tumor stroma and stromal invasion have been studied in the lung; however, they are still unclear. CD109 is a glycosylphosphatidylinositol-anchored glycoprotein highly expressed in several types of human malignant tumors including lung cancers. In this study, we investigated the in vivo functions of CD109 protein in malignant lung tumors. Initially, we identified an association between higher expression of CD109 protein in human lung adenocarcinoma and a significantly worse prognosis, according to immunohistochemical analysis. We also showed that CD109 deficiency significantly reduced the area of stromal invasive lesions in a genetically engineered CD109-deficient lung adenocarcinoma mouse model, which correlated with the results observed in human lung adenocarcinoma. Furthermore, we identified latent TGF-β binding protein-1 (LTBP1) as a CD109-interacting protein using mass spectrometry and confirmed their interaction by co-immunoprecipitation. Importantly, increased CD109 expression enhanced stromal TGF-β activation in the presence of LTBP1. Therefore, these data suggest the significance of the regulation of TGF-β signaling through CD109 and LTBP1 interaction in tumor stroma and also reveal the importance of CD109 expression levels in promoting lung cancer cell proliferation, migration, and invasion, and thus predicting the outcome of patients suffering from lung adenocarcinoma. Therefore, CD109 protein could be a potential therapeutic target for this disease.

The prognostic value of the tumor-stroma ratio in squamous cell lung cancer, a cohort study

OBJECTIVES

The tumor-stroma ratio (TSR) is based on the relative amount of stroma in the primary tumor and has proven to be an independent prognostic factor in various solid tumors. The prognosis of patients and adjuvant treatment decision making in lung squamous cell carcinomas (SqCC) is based on the TNM classification. Currently, no other prognostic biomarkers are available. In this study we evaluated the prognostic value of the TSR in lung SqCC.

MATERIAL AND METHODS

Patients undergoing lung surgery because of lung SqCC between 2000 and 2018 at the Leiden University Medical Center were included. The TSR was scored on hematoxylin & eosin stained tissue sections. Based on the amount of tumor-stroma, two groups were defined: ≤50% was classified as a stroma-low tumor and >50% as stroma-high. The prognostic value of the TSR was determined with survival analysis.

RESULTS

A total of 174 stage I-III patients were included. Of them, 79 (45%) were stroma-low and 95 (55%) stroma-high. Separately analyzed for tumor stages, the TSR showed to be an independent prognostic biomarker in stage II (n = 68) for 5-year overall survival (HR=3.0; 95% CI, 1.1-8.6; p = 0.035) and 5-year disease free survival (DFS) (HR=3.6; 95% CI, 1.3-9.9; p = 0.014). Patients with a stroma-high tumor had a worse 5-year DFS in the whole cohort (HR 1.6; 95% CI, 1.0-2.4; p = 0.048), but no independent prognostic value was found.

CONCLUSION

In stage II lung SqCC patients, stroma-low tumors have a better prognosis compared to stroma-high tumors. Moreover, adjuvant chemotherapy could be spared for these stroma-low patients.

Mesenchymal stem cells promote metastasis through activation of an ABL-MMP9 signaling axis in lung cancer cells

Mesenchymal stem cells (MSCs) are recruited and activated by solid tumors and play a role in tumor progression and metastasis. Here we show that MSCs promote metastasis in a panel of non-small cell lung cancer (NSCLC) cells. MSCs elicit transcriptional alterations in lung cancer cells leading to increased expression of factors implicated in the epithelial-to-mesenchymal transition (EMT) and secreted proteins including matrix metalloproteinase-9 (MMP9). MSCs enhance secretion of enzymatically active MMP9 in a panel of lung adenocarcinoma cells. High expression of MMP9 is linked to low survival rates in lung adenocarcinoma patients. Notably, we found that ABL tyrosine kinases are activated in MSC-primed lung cancer cells and functional ABL kinases are required for MSC-induced MMP9 expression, secretion and proteolytic activity. Importantly, ABL kinases are required for MSC-induced NSCLC metastasis. These data reveal an actionable target for inhibiting MSC-induced metastatic activity of lung adenocarcinoma cells through disruption of an ABL kinase-MMP9 signaling axis activated in MSC-primed lung cancer cells.

Low-dose radiation treatment enhances systemic antitumor immune responses by overcoming the inhibitory stroma

Background

Despite some successes with checkpoint inhibitors for treating cancer, most patients remain refractory to treatment, possibly due to the inhibitory nature of the tumor stroma that impedes the function and entry of effector cells. We devised a new technique of combining immunotherapy with radiotherapy (XRT), more specifically low-dose XRT, to overcome the stroma and maximize systemic outcomes.

Methods

We bilaterally established 344SQ lung adenocarcinoma tumors in 129Sv/Ev mice. Primary and secondary tumors were irradiated with either high-dose or low-dose of XRT with systemic anti-programmed cell death protein 1 and anti-cytotoxic T-lymphocyte associated protein 4 administration. Survival and tumor growth were monitored for the various groups, and secondary tumors were phenotyped by flow cytometry for immune populations. Tumor growth factor-beta (TGF-β) cytokine levels were assessed locally after low-dose XRT, and specific immune-cell depletion experiments were conducted to identify the major contributors to the observed systemic antitumor effect.

Results

Through our preclinical and clinical studies, we observed that when tumor burden was high, there was a necessity of combining high-dose XRT to ‘prime’ T cells at the primary tumor site, with low-dose XRT directed to secondary (metastatic) tumors to ‘modulate the stroma’. Low-dose XRT improved the antitumor outcomes of checkpoint inhibitors by favoring M1 macrophage polarization, enhancing natural killer (NK) cell infiltration, and reducing TGF-β levels. Depletion of CD4⁺ T cells and NK cells abrogated the observed antitumor effect.

Conclusion

Our data extend the benefits of low-dose XRT to reprogram the tumor environment and improve the infiltration and function of effector immune cells into secondary tumors.

Quantification of aortic valve area: comparison of different methods of echocardiography with 3-D scan of the excised valve

Accurate determination of severity of aortic valve stenosis (AS) by aortic valve area (AVA) is essential for choosing the best treatment strategy. We compared AVA quantified by 4 different in vivo echocardiographic methods with AVA measured by 3D ex vivo scanning of the excised AV. The data on 38 patients who underwent aortic valve replacement were assessed. The AVA was determined by 4 echocardiographic methods of planimetry in 2D transesophageal echocardiography [planimetry (2D-TEE)], plainemetry by multiplanar reconstruction approach in 3D transesophageal echocardiography [MPR (3D-TEE)], and two continuity equation (CE) approaches; conventional CE (2D-TTE) in which left ventricular outflow tract [LVOT] area derived by LVOT diameter obtained in 2D transthoracic echocardiography and CE (3D-TEE) in which LVOT area obtained by 3D MPR. After the surgical removal of the AV, AVA was determined by 3D ex vivo scanning. Lowest AVA mean difference with 3D ex vivo scanning was found between CE (2D-TTE), followed by CE (3D-TEE). Planimetry (2D-TEE) in male patients as well as severely and non-severely calcified valves revealed a significant higher AVA mean difference with 3D ex vivo scanning than CE (2D-TTE) and CE (3D-TEE) methods. However, with a nonsignificant effect, CE (2D-TTE) and planimetry (2D-TEE) had the least mean difference with 3D ex vivo scanning possibly due to less frequent bicuspid AV in females. CE (2D-TTE) was more accurate than other methods of AVA calculation. Moreover, CE (3D-TEE) and MPR (3D-TEE) methods had acceptable accuracy in comparison with planimetry (2D-TEE) for definition of AS severity.

Increased RAB31 Expression in Cancer-Associated Fibroblasts Promotes Colon Cancer Progression Through HGF-MET Signaling

RAB family proteins participate in the dynamic regulation of cellular membrane compartments and are dysregulated in a variety of tumor types, which may alter the biological properties of cancer cells such as proliferation, migration, and invasion. In our previous study, we found that Ras-related protein Rab-31 (RAB31) expression was increased in late-stage colorectal cancer (CRC). The role of RAB31 has never been investigated in CRC. In this study, we found that expression of RAB31 in the tumor stroma but not cancer cells of colon cancer predicted poor survival. RAB31 can be detected in primary cancer-associated fibroblasts (CAFs) and paired normal fibroblasts. Conditioned medium (CM) from RAB31 overexpressing CAFs significantly promoted migration of colon cancer cell lines in vitro and in vivo. This process may be mediated by paracrine action of hepatocyte growth factor (HGF), which was increased in the CM of RAB31-overexpressing CAFs. Blockade of HGF/MET signaling by drug inhibition, knockdown of mesenchymal to epithelial transition factor (MET) in RKO, or antibody neutralization of HGF abolished migration of RKO cells mediated by RAB31 expression in CAFs. We propose that in colon cancer, increased RAB31 expression in CAFs may contribute to tumor progression by regulating the secretion of HGF in the tumor stroma.

A Novel Nomogram Based on Immune Scores for Predicting Survival in Patients with Early-Stage Non-Small Cell Lung Cancer (NSCLC)

Background

The role of immune parameters in the prognosis of lung cancer has attracted more and more attention. However, studies of the association between immune scores and prognosis of lung cancer are scarce. The goal of our research was to investigate the correlation between immune scores and overall survival (OS) of early-stage non-small cell lung cancer (NSCLC).

Material/Methods

All data regarding patient immune and stromal scores, clinicopathological features, and survival was obtained from the TCGA datasets. Univariable and multivariable Cox regression analyses were utilized to recognize risk factors associated with OS. Afterward, a prognostic nomogram was constructed for predicting 3- and 5-year OS of stage I and II NSCLC patients. Calibration curves and receiver operating characteristic (ROC) were performed to assess the predictive accuracy of the nomogram. Kaplan-Meier methodology was also applied for the survival analysis.

Results

In total, 764 NSCLC (stage I–II) patients were analyzed, and all patients were classified into 3 groups based on immune scores. Results showed that patients with medium-immune scores had significantly worse OS (hazard ratio=1.73, 95% confidence interval: 1.22–2.46) compared with those with low- and high immune scores. Area under the ROC curves (AUC) values for 3- and 5-year OS were 0.65 and 0.64, respectively. Calibration plots demonstrated good consistency in the probability of OS between nomogram predictions and actual observations.

Conclusions

Medium-immune scores are correlated with unsatisfactory prognosis in NSCLC (stage I–II) patients. In addition, the prognostic nomogram may be helpful in predicting OS for stage I and II NSCLC patients.

Prognostic Significance of the Tumor-Stromal Ratio in Invasive Breast Cancer and a Proposal of a New Ts-TNM Staging System

Background

Previous studies have demonstrated that the tumor-stromal ratio (TSR) was an independent prognostic factor in several types of carcinomas. This study aimed at exploring the prognostic significance of the TSR in invasive breast cancer using immunohistochemistry (IHC)-stained tissue microarrays (TMAs) and integrating the TSR into the traditional tumor-node-metastasis (TNM) staging system.

Methods

The prepared 7 TMAs containing 240 patients with 480 invasive BC specimens were stained with cytokeratin (CK) by the IHC staining method. The ratio of tumor cells and stromal cells was visually assessed. TSR > 1 and TSR ≤ 1 were categorized as the high TSR (low stroma) and low TSR (high stroma) groups, respectively, and the prognostic value of the TSR at 5-year disease-free survival (5-DFS) was analyzed. A new Ts-TNM (tumor stroma-tumor-node-metastasis) staging system was established and assessed.

Results

IHC staining of CK could specifically label tumor cells with clear contrast, making it easy to manually assess TSR. High TSR (low stroma) and low TSR (high stroma) were observed in 52.5% (n = 126) and 47.5 (n = 114) of the cases, according to the division of value 1. A Kaplan-Meier analysis showed that patients in the low TSR group had a worse 5-DFS compared with patients in the high TSR group (P=0.022). Multivariable analysis indicated that the T stage (P=0.014), N status (P < 0.001), histological grade (P < 0.001), estrogen receptor status (P=0.015), and TSR (P=0.011) were independent prognostic factors of invasive BC patients. The new Ts-TNM staging system combining TSR, tumor staging, lymph node status, and metastasis staging was established. The receiver operating characteristic (ROC) curve analysis demonstrated that the ability of the Ts-TNM staging system to predict recurrence was not lower than that of the TNM staging system.

Conclusions

This study confirms that the TSR is a prognostic indicator for invasive breast cancer. The Ts-TNM staging system containing stromal and tumor information may optimize risk stratification for invasive breast cancer.

Extracellular matrix alterations in low-grade lung adenocarcinoma compared with normal lung tissue by imaging mass spectrometry

Lung adenocarcinoma (LUAD) is the second most common cancer, affecting both men and women. Fibrosis is a hallmark of LUAD occurring throughout progression with excess production of extracellular matrix (ECM) components that lead to metastatic cell processes. Understanding the ECM cues that drive LUAD progression has been limited due to a lack of tools that can access and report on ECM components within the complex tumor microenvironment. Here, we test whether low-grade LUAD can be distinguished from normal lung tissue using a novel ECM imaging mass spectrometry (ECM IMS) approach. ECM IMS analysis of a tissue microarray with 20 low-grade LUAD tissues and 20 normal lung samples from 10 patients revealed 25 peptides that could discriminate between normal and low-grade LUAD using area under the receiver-operating curve (AUC) ≥0.7, P value ≤.001. Principal component analysis demonstrated that 62.4% of the variance could be explained by sample origin from normal or low-grade tumor tissue. Additional work performed on a wedge resection with moderately differentiated LUAD demonstrated that the ECM IMS analytical approach could distinguish LUAD spectral features from spectral features of normal adjacent lung tissue. Conventional liquid chromatography with tandem mass spectrometry (LC-MS/MS) proteomics demonstrated that specific sites of hydroxylation of proline (HYP) were a main collagen post translational modification that was readily detected in LUAD. A distinct peptide from collagen 3A1 modified by HYP was increased 3.5 fold in low-grade LUAD compared with normal lung tissue (AUC 0.914, P value <.001). This suggests that regulation of collagen proline hydroxylation could be an important process during early LUAD fibrotic deposition. ECM IMS is a useful tool that may be used to define fibrotic deposition in low-grade LUAD.

The prognostic value of the tumor-stroma ratio is most discriminative in patients with grade III or triple-negative breast cancer

The tumor-stroma ratio (TSR) was evaluated as a promising parameter for breast cancer prognostication in clinically relevant subgroups of patients. The TSR was assessed on hematoxylin and eosin-stained tissue slides of 1,794 breast cancer patients from the Nottingham City Hospital. An independent second cohort of 737 patients from the Netherlands Cancer Institute to Antoni van Leeuwenhoek was used for evaluation. In the Nottingham Breast Cancer series, the TSR was an independent prognostic parameter for recurrence-free survival (RFS; HR 1.35, 95% CI 1.10-1.66, p = 0.004). The interaction term was statistically significant for grade and triple-negative status. Multivariate Cox regression analysis showed a more pronounced effect of the TSR for RFS in grade III tumors (HR 1.89, 95% CI 1.43-2.51, p < 0.001) and triple-negative tumors (HR 1.86, 95% CI 1.10-3.14, p = 0.020). Comparable hazard ratios and confidence intervals were observed for grade and triple-negative status in the ONCOPOOL study. The prognostic value of TSR was not modified by age, tumor size, histology, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor 2 status or lymph node status. In conclusion, patients with a stroma-high tumor had a worse prognosis compared to patients with a stroma-low tumor. The prognostic value of the TSR is most discriminative in grade III tumors and triple-negative tumors. The TSR was not modified by other clinically relevant parameters making it a potential factor to be included for improved risk stratification.

A new strategy to confirm the identity of tumour tissues using single-nucleotide polymorphisms and next-generation sequencing

With growing cancer morbidity, forensics cases in which archived tumour tissues can be used as biological samples are increasing, and an effective method to identify the body source of tumour tissues is needed. Single nucleotide polymorphisms (SNPs) may be a promising biomarker to identify the source of tumour tissues because of their low mutation rate and small amplicon size. Next-generation sequencing techniques offers the ability to detect hundreds of SNPs in a single run. The Precision ID Identity Panel (Thermo Fisher Scientific, Waltham, MA, USA) detects 90 autosomal SNPs for individual identification and 34 lineage-informative SNPs on Y chromosome using the Ion PGM system (Thermo Fisher Scientific). In this study, we evaluated performance of the panel for individual identification of tumour tissues. One hundred and fifty pairs of tumour tissues and corresponding normal tissues were analysed. Loss of heterozygosity was detected only in tumour tissues. The identity-by-state (IBS) scoring system was adopted to identify the body source of tumour tissues. The IBS score, as well as the number of loci with 2 alleles (A₂), 1 allele (A₁) and 0 alleles (A₀) shared, were analysed within each tumour-normal pair, unrelated individual pairs, parent-offspring pairs and full-sibling pairs. According to the probability distribution, threshold of A₂ in the range of 69 to 89 could achieve accuracy > 99% in identifying the source of tumour tissues. Thus, we developed a new strategy (process and criteria) to identify the source of tumour tissues that could be used in practice.

Whole-Slide Image Analysis Reveals Quantitative Landscape of Tumor-Immune Microenvironment in Colorectal Cancers

PURPOSE

Despite the well-known prognostic value of the tumor-immune microenvironment (TIME) in colorectal cancers, objective and readily applicable methods for quantifying tumor-infiltrating lymphocytes (TIL) and the tumor-stroma ratio (TSR) are not yet available.

EXPERIMENTAL DESIGN

We established an open-source software-based analytic pipeline for quantifying TILs and the TSR from whole-slide images obtained after CD3 and CD8 IHC staining. Using a random forest classifier, the method separately quantified intraepithelial TILs (iTIL) and stromal TILs (sTIL). We applied this method to discovery and validation cohorts of 578 and 283 stage III or high-risk stage II colorectal cancers patients, respectively, who were subjected to curative surgical resection and oxlaliplatin-based adjuvant chemotherapy.

RESULTS

Automatic quantification of iTILs and sTILs showed a moderate concordance with that obtained after visual inspection by a pathologist. The K-means-based consensus clustering of 197 TIME parameters that showed robustness against interobserver variations caused colorectal cancers to be grouped into five distinctive subgroups, reminiscent of those for consensus molecular subtypes (CMS1-4 and mixed/intermediate group). In accordance with the original CMS report, the CMS4-like subgroup (cluster 4) was significantly associated with a worse 5-year relapse-free survival and proved to be an independent prognostic factor. The clinicopathologic and prognostic features of the TIME subgroups have been validated in an independent validation cohort.

CONCLUSIONS

Machine-learning-based image analysis can be useful for extracting quantitative information about the TIME, using whole-slide histopathologic images. This information can classify colorectal cancers into clinicopathologically relevant subgroups without performing a molecular analysis of the tumors.

Adjustment of Microvessel Area by Stromal Area to Improve Survival Prediction in Non-Small Cell Lung Cancer

Background: Sustained tumor growth and metastasis require sufficient blood supply, and microvessel area (MVA) has been reported that is related to prognosis of cancer patients. However, tumor cells may not be nourished enough by blood vessels when the cells are separated from vessels by thick stroma. Therefore we investigated whether stroma-area normalized MVA (SnMVA) is a more important prognostic factor than MVA.

Materials and Methods: 100 NSCLC patients who underwent resection between July 2011 and October 2012 were randomly selected. We determined the MVA of the tumor tissues by anti-CD31 immunostaining of microvessels. Stroma-area normalized MVA (SnMVA) was a ratio of MVA to stromal area. Correlation of MVA and SnMVA with overall survival (OS) or progression-free survival (PFS) was assessed using multivariate analysis.

Results: Median MVA was 0.0228 (range, 0.00393 to 0.172), and median SnMVA was 0.0441 × 10^-6 (range, 0.00393 × 10^-6 to 0.259 × 10^-6). There was no significant difference in OS between groups of different MVA (HR 0.58, 95%CI 0.28 to 1.19, p = 0.148). In contrast, the risk of death was significantly decreased in high SnMVA group (at or below the median) than in group with low SnMVA (HR 0.47, 95%CI 0.23 to 0.97, p = 0.046). Furthermore, in multivariate analysis, high SnMVA, but not MVA, was an independent prognostic factor after adjusting for age, sex, tumor stage and other factors. OS was significantly associated with SnMVA in six of seven subgroup analysis, but with MVA in only three.

Conclusions: Our study showed that the NSCLC patients with high SnMVA had higher OS. And SnMVA is a prognostic factor with greater accuracy than MVA. Since stroma exists widely in a variety of cancer tissues, we infer that SnMVA may also predict the prognostic of other types of cancers.

Development of a Cross-Reactive Monoclonal Antibody for Detecting the Tumor Stroma

Here, we document the discovery of a monoclonal antibody that selectively binds to both human and murine fibroblast activation protein alpha (FAP), a serine protease that is overexpressed on cancer-associated fibroblasts (CAFs), making it an attractive therapeutic target for the aiding and abetting tumor microenvironment. The lead antibody, B12, was identified from a naïve murine single-chain variable fragment antibody phage display library screened against recombinant human FAP on magnetic beads. The heavy and light chains of B12 were cloned into full-length human immunoglobulin 1 (IgG) vectors and expressed as a chimeric monoclonal antibody (B12 IgG). We engineered a drug-resistant prostate cancer cell line, CWR-R1-EnzR, to express human FAP for antibody characterization and validation (R1-EnzR^FAP). B12 IgG selectively bound to the R1-EnzR^FAP cells by flow cytometry and was internalized in vitro by confocal microscopy. B12 IgG was further evaluated as a near-infrared (NIR) optical imaging probe in R1-EnzR^FAP and parental xenograft models. High tumor uptake and retention of the NIR probe was observed in the R1-EnzR^FAP xenografts, and endogenous expression of murine stromal origin FAP was detected in the parental xenografts. Ex vivo evaluation of these models by immunohistochemistry documented B12 IgG localization to both human and murine FAP-expressing cells.

Intratumoral heterogeneity as measured using the tumor-stroma ratio and PET texture analyses in females with lung adenocarcinomas differs from that of males with lung adenocarcinomas or squamous cell carcinomas

We compared intratumoral stromal proportions and positron emission tomography (PET) textural features between females and males with lung adenocarcinoma (ADC) or squamous cell carcinoma (SCC).We retrospectively evaluated 167 consecutive patients (male 122, female 45) who underwent pretreatment fluorodeoxyglucose PET/CT and surgical resection. The tumor-stroma ratios (TSRs) of primary tumors were estimated on hematoxylin-and-eosin-stained histological sections, and higher-order textural features were extracted on PET. We compared the histological and PET features between the sexes.More females than males had ADC. Age and pathological tumor size did not significantly differ between females and males. Females with ADC had more stroma-rich tumors than males with ADC (P = .016) or SCC (P = .047). In addition, some PET textural features significantly differed between females with ADC and males with ADC and SCC; short run emphasis, long run emphasis, coarseness, strength, short-zone emphasis, zone percentage and high-intensity large-zone percentage were the commonly differed textural features. However, the TSRs and PET textural features did not significantly differ between males with ADC or SCC.Intratumoral heterogeneity in females with lung ADC differs from that in males with lung ADC or SCC.

Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural Networks

The tumor-stroma ratio (TSR) reflected on hematoxylin and eosin (H&E)-stained histological images is a potential prognostic factor for survival. Automatic image processing techniques that allow for high-throughput and precise discrimination of tumor epithelium and stroma are required to elevate the prognostic significance of the TSR. As a variant of deep learning techniques, transfer learning leverages nature-images features learned by deep convolutional neural networks (CNNs) to relieve the requirement of deep CNNs for immense sample size when handling biomedical classification problems. Herein we studied different transfer learning strategies for accurately distinguishing epithelial and stromal regions of H&E-stained histological images acquired from either breast or ovarian cancer tissue. We compared the performance of important deep CNNs as either a feature extractor or as an architecture for fine-tuning with target images. Moreover, we addressed the current contradictory issue about whether the higher-level features would generalize worse than lower-level ones because they are more specific to the source-image domain. Under our experimental setting, the transfer learning approach achieved an accuracy of 90.2 (vs. 91.1 for fine tuning) with GoogLeNet, suggesting the feasibility of using it in assisting pathology-based binary classification problems. Our results also show that the superiority of the lower-level or the higher-level features over the other ones was determined by the architecture of deep CNNs.

The prognostic value of tumour-stroma ratio in primary breast cancer with special attention to triple-negative tumours: a review

Purpose

There is a strong need to improve the prognostication of breast cancer patients in order to prevent over- and undertreatment, especially when considering adjuvant chemotherapy. Tumour stroma characteristics might be valuable in predicting disease progression.

Methods

Studies regarding the prognostic value of tumour–stroma ratio (TSR) in breast cancer are evaluated.

Results

A high stromal content is related to a relatively poor prognosis. The most pronounced prognostic effect of this parameter seems to be observed in the triple-negative breast cancer (TNBC) subtype.

Conclusions

TSR assessment might represent a simple, fast and reproducible prognostic factor at no extra costs, and could possibly be incorporated into routine pathological diagnostics. Despite these advantages, a robust clinical validation of this parameter has yet to be established in prospective studies.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-4987-4) contains supplementary material, which is available to authorized users.

Treating EGFR-Mutated Oncogene-Addicted Advanced Non-Small-Cell Lung Cancer in the Era of Economic Crisis in Greece: Challenges and Opportunities

PURPOSE

Because of the profound financial crisis that commenced in Greece in 2010, severe cuts in health care spending and other restriction measures led to significant delays in the reimbursement of novel antineoplastic agents. In 2011, the Hellenic Society of Medical Oncology initiated a program of early access to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors for the treatment of patients with advanced, EGFR-mutant non-small-cell lung cancer (NSCLC). We evaluated treatment patterns and clinical outcomes in patients with EGFR-mutant or wild-type disease treated at a large center in Greece throughout the period of financial crisis.

PATIENTS AND METHODS

From 2011 through 2015, 252 patients with newly diagnosed advanced NSCLC were treated at the Department of Medical Oncology of the Papageorgiou Hospital, a tertiary cancer center in northern Greece. We retrospectively reviewed patient medical records to obtain clinicopathologic characteristics, EGFR mutation status, and follow-up data. The primary end point was time to treatment failure.

RESULTS

Of the 198 evaluable patients, 25 (12%) had EGFR mutations. All patients with EGFR mutations except one received treatment with an EGFR tyrosine kinase inhibitor. Median times to treatment failure for patients with EGFR-mutant and wild-type disease were 15.8 and 7.1 months, respectively (hazard ratio, 0.58; 95% CI, 0.35 to 0.95; P = .031). There was no difference in overall survival between the two groups ( P = .293). No deviation from treatment guidelines or discontinuation of treatment regimens occurred because of logistic reasons or drug shortages.

CONCLUSION

Despite restrictions in the reimbursement policy and accompanying controls in the use of high-cost medicines, the national program enabled treatment of patients with EGFR-mutant NSCLC according to established guidelines. Therefore, the clinical outcomes of such patients treated in Greece during the economic crisis were in accordance with international standards.

Collagen type I induces EGFR-TKI resistance in EGFR-mutated cancer cells by mTOR activation through Akt-independent pathway

Primary resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) is a serious problem in lung adenocarcinoma patients harboring EGFR mutations. The aim of this study was to examine whether and how collagen type I (Col I), the most abundantly deposited matrix in tumor stroma, affects EGFR-TKI sensitivity in EGFR-mutant cells. We evaluated the EGFR-TKI sensitivity of EGFR-mutated cancer cells cultured with Col I. Changes in the activation of downstream signaling molecules of EGFR were analyzed. We also examined the association between the Col I expression in tumor stroma in surgical specimens and EGFR-TKI response of postoperative recurrence patients with EGFR mutations. Compared to cancer cells without Col I, the survival rate of cancer cells cultured with Col I was significantly higher after EGFR-TKI treatment. In cancer cells cultured with and without Col I, EGFR-TKI suppressed the levels of phosphorylated (p-)EGFR, p-ERK1/2, and p-Akt. When compared to cancer cells without Col I, expression of p-P70S6K, a hallmark of mTOR activation, was dramatically upregulated in cancer cells with Col I. This activation was maintained even after EGFR-TKI treatment. Simultaneous treatment with EGFR-TKI and mTOR inhibitor abrogated Col I-induced resistance to EGFR-TKI. Patients with Col I-rich stroma had a significantly shorter progression-free survival time after EGFR-TKI therapy (238 days vs 404 days; P < .05). Collagen type I induces mTOR activation through an Akt-independent pathway, which results in EGFR-TKI resistance. Combination therapy using EGFR-TKI and mTOR inhibitor could be a possible strategy to combat this resistance.