The role of tumor stroma in cancer progression and prognosis: emphasis on carcinoma-associated fibroblasts and non-small cell lung cancer

Stromal Expression of CD10 in Breast Carcinoma and Its Association with Known Prognostic Factors-A Tissue Microarray-Based Study

Background  Breast cancer is an epithelial malignancy; however, stroma plays a key role with its stimulatory and inhibitory factors in modulating tumor invasion and metastasis. CD10, a matrix metalloproteinase, is known to regulate cell adhesion, migration and helps in determining the progression of tumor. This knowledge helps to identify specific signals that promote growth, dedifferentiation, invasion, metastasis and serve as target for better therapeutic management. Objectives  The aim of this study was to estimate frequency of expression of stromal CD10 and assess its prognostic significance in breast carcinomas by correlating with known prognostic factors. Materials and Methods  Morphological parameters of 62 cases of carcinoma breast were studied on H&E (hematoxylin and eosin) stained sections and expressions of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2/neu), and CD10 on manually constructed tissue microarray sections by immunohistochemistry (IHC). Staining pattern, percentage of stained cells, and intensity of stains were evaluated and IHC scoring of all markers was done. CD10 scores were correlated with the known prognostic factors (ER, PR, and HER2/neu). A p -value less than 0.05 was considered as significant. Results  Stromal expression of CD10 was found in 82.3% of cases and it was significantly associated with increasing tumor size ( p  = 0.012), increasing tumor grade ( p  = 0.001), lymph node metastasis ( p  = 0.018), necrosis ( p  = 0.008), lymphovascular invasion ( p  = 0.008), ER negativity ( p  = 0.001), PR negativity( p  = 0.007), HER 2 positivity ( p  = 0.012), triple-negative molecular subtypes ( p  = 0.001), and poor prognostic groups ( p  = 0.01). Conclusion  CD10 can be used as an independent prognostic stromal marker and this will help to envisage new therapeutic strategies.

Mechanisms of HIF-driven immunosuppression in tumour microenvironment

Hypoxia arises due to insufficient oxygen delivery to rapidly proliferating tumour cells that outpace the available blood supply. It is a characteristic feature of most solid tumour microenvironments and plays a critical role in regulating anti-tumour immunity, enhancing tumoral heterogeneity, and promoting therapeutic resistance and poor clinical outcomes. Hypoxia-inducible factors (HIFs) are the major hypoxia-responsive transcription factors that are activated under low oxygenation conditions and have been identified to drive multifunctional roles in tumour immune evasion. The HIF signalling network serves as an attractive target for targeted therapeutic approaches. This review aims to provide a comprehensive overview of the most crucial mechanisms by which HIF controls the expression of immunosuppressive molecules and immune checkpoints, disrupts cancer immunogenicity, and induces immunotherapeutic resistance.

A study on fractional tumor-immune interaction model related to lung cancer via generalized Laguerre polynomials

BACKGROUND

Cancer, a complex and deadly health concern today, is characterized by forming potentially malignant tumors or cancer cells. The dynamic interaction between these cells and their environment is crucial to the disease. Mathematical models can enhance our understanding of these interactions, helping us predict disease progression and treatment strategies.

METHODS

In this study, we develop a fractional tumor-immune interaction model specifically for lung cancer (FTIIM-LC). We present some definitions and significant results related to the Caputo operator. We employ the generalized Laguerre polynomials (GLPs) method to find the optimal solution for the FTIIM-LC model. We then conduct a numerical simulation and compare the results of our method with other techniques and real-world data.

RESULTS

We propose a FTIIM-LC model in this paper. The approximate solution for the proposed model is derived using a series of expansions in a new set of polynomials, the GLPs. To streamline the process, we integrate Lagrange multipliers, GLPs, and operational matrices of fractional and ordinary derivatives. We conduct a numerical simulation to study the effects of varying fractional orders and achieve the expected theoretical results.

CONCLUSION

The findings of this study demonstrate that the optimization methods used can effectively predict and analyze complex phenomena. This innovative approach can also be applied to other nonlinear differential equations, such as the fractional Klein-Gordon equation, fractional diffusion-wave equation, breast cancer model, and fractional optimal control problems.

Nanomedicine Strategies for Targeting Tumor Stroma

The tumor stroma, or the microenvironment surrounding solid tumors, can significantly impact the effectiveness of cancer therapies. The tumor microenvironment is characterized by high interstitial pressure, a consequence of leaky vasculature, and dense stroma created by excessive deposition of various macromolecules such as collagen, fibronectin, and hyaluronic acid (HA). In addition, non-cancerous cells such as cancer-associated fibroblasts (CAFs) and the extracellular matrix (ECM) itself can promote tumor growth. In recent years, there has been increased interest in combining standard cancer treatments with stromal-targeting strategies or stromal modulators to improve therapeutic outcomes. Furthermore, the use of nanomedicine, which can improve the delivery and retention of drugs in the tumor, has been proposed to target the stroma. This review focuses on how different stromal components contribute to tumor progression and impede chemotherapeutic delivery. Additionally, this review highlights recent advancements in nanomedicine-based stromal modulation and discusses potential future directions for developing more effective stroma-targeted cancer therapies.

Cell State and Cell Type: Deconvoluting Circulating Tumor Cell Populations in Liquid Biopsies by Multi-Omics

Bi-directional crosstalk between the tumor and the tumor microenvironment (TME) has been shown to increase the rate of tumor evolution and to play a key role in neoplastic progression, therapeutic resistance, and a patient's overall survival. Here, we set out to use a comprehensive liquid-biopsy analysis to study cancer and specific TME cells in circulation and their association with disease status. Cytokeratin+, CD45- circulating rare cells (CRCs) from nine breast and four prostate cancer patients were characterized through morphometrics, single-cell copy number analysis, and targeted multiplexed proteomics to delineate cancer cell lineage from other rare cells originating in the TME. We show that we can detect epithelial circulating tumor cells (EPI.CTC), CTCs undergoing epithelial-to-mesenchymal transition (EMT.CTC) and circulating endothelial cells (CECs) using a universal rare event detection platform (HDSCA). Longitudinal analysis of an index patient finds that CTCs are present at the time of disease progression, while CECs are predominately present at the time of stable disease. In a small cohort of prostate and breast cancer patients, we find high inter-patient and temporal intra-patient variability in the expression of tissue specific markers such as ER, HER2, AR, PSA and PSMA and EpCAM. Our study stresses the importance of the multi-omic characterization of circulating rare cells in patients with breast and prostate carcinomas, specifically highlighting overlapping and cell type defining proteo-genomic characteristics of CTCs and CECs.

Shedding light on macrophage immunotherapy in lung cancer

The search for therapeutic options for lung cancer continues to advance, with rapid advances in the search for therapies to improve patient prognosis. At present, systemic chemotherapy, immune checkpoint inhibitor therapy, antiangiogenic therapy, and targeted therapy for driver gene positivity are available in the clinic. Common clinical treatments fail to achieve desired outcomes due to immunosuppression of the tumor microenvironment (TME). Tumor immune evasion is mediated by cytokines, chemokines, immune cells, and other cells such as vascular endothelial cells within the tumor immune microenvironment. Tumor-associated macrophages (TAMs) are important immune cells in the TME, inducing tumor angiogenesis, encouraging tumor cell proliferation and migration, and suppressing antitumor immune responses. Thus, TAM targeting becomes the key to lung cancer immunotherapy. This review focuses on macrophage phenotype, polarization mechanism, role in lung cancer, and advances in macrophage centric immunotherapies.

Prognostic evaluation of cancer associated fibrosis and tumor budding in colorectal cancer

Colorectal carcinoma (CRC) is the second most common cancer and third leading cause of cancer-related deaths worldwide. Although the staging system provides a standardized guidance in treatment regimens, the clinical outcome in patients with colon cancer at the same TNM stage may vary dramatically. Thus, for better predictive accuracy, further prognostic and/or predictive markers are required. Patients who underwent curative surgery for colorectal cancer in past 3 years at a tertiary care hospital were retrospectively included in this cohort study to evaluate the prognostic indicators, tumor-stroma ratio (TSR) and tumor budding (TB) on histopathological sections and correlated them with pTNM staging, histopathological grading, tumor size, and lymphovascular and perineural invasion in patients with colo-rectal cancer. TB was strongly associated with advanced stage of the disease along with lympho-vascular and peri-neural invasion and it can be used as an independent adverse prognostic factor. TSR showed a better sensitivity, specificity, PPV and NPV as compared to TB in patients having poorly differentiated adenocarcinoma than those with moderately or well differentiated.

Overcoming cancer-associated fibroblast-induced immunosuppression by anti-interleukin-6 receptor antibody

Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironment and play a central role in tumor progression. Previously, we reported that CAFs might induce tumor immunosuppression via interleukin-6 (IL-6) and promote tumor progression by blocking local IL-6 in the tumor microenvironment with neutralizing antibody. Here, we explore whether an anti-IL-6 receptor antibody could be used as systemic therapy to treat cancer, and further investigate the mechanisms by which IL-6 induces tumor immunosuppression. In clinical samples, IL-6 expression was significantly correlated with α-smooth muscle actin expression, and high IL-6 cases showed tumor immunosuppression. Multivariate analysis showed that IL-6 expression was an independent prognostic factor. In vitro, IL-6 contributed to cell proliferation and differentiation into CAFs. Moreover, IL-6 increased hypoxia-inducible factor 1α (HIF1α) expression and induced tumor immunosuppression by enhancing glucose uptake by cancer cells and competing for glucose with immune cells. MR16-1, a rodent analog of anti-IL-6 receptor antibody, overcame CAF-induced immunosuppression and suppressed tumor progression in immunocompetent murine cancer models by regulating HIF1α activation in vivo. The anti-IL-6 receptor antibody could be systemically employed to overcome tumor immunosuppression and improve patient survival with various cancers. Furthermore, the tumor immunosuppression was suggested to be induced by IL-6 via HIF1α activation.

Cytological features of stromal spindle cells and their prognostic significance in lung adenocarcinoma

INTRODUCTION

Cancer-associated fibroblasts (CAFs) in the tumour microenvironment play a key role in tumour development, proliferation, invasion, and metastasis. The cytological features of spindle cells including CAFs-defined as stromal spindle cells (SSCs) adjacent to cancer cells-are frequently encountered in pulmonary adenocarcinomas. This study aimed to investigate the association between the presence of SSCs in cytological specimens and the clinicopathological features.

METHODS

We evaluated 211 patients with pulmonary adenocarcinoma who underwent surgical resection. All participants had cytological specimens corresponding to the histological specimens available for review.

RESULTS

Of the 211 cases examined, 89 were SSC-positive (SSC+ ) and 122 were SSC-negative (SSC- ). SSC+ cases were more frequently associated with higher pathological stage (P < 0.001), lymph node metastasis (P = 0.002), anaplastic lymphoma kinase (ALK) gene rearrangement (P = 0.04), high tumour grade (P < 0.001), solid and micropapillary predominant pattern (P = 0.02), and lymphatic vessel (P = 0.003), blood vessel (P < 0.001), and pleural invasion (P = 0.03) as compared to SSC- cases. Patients with SSC+ adenocarcinoma had a significantly shorter recurrence-free survival than those with SSC- adenocarcinoma (P = 0.009). Cytologically, necrotic background (P = 0.002), mucinous cancer cells (P = 0.02), pleomorphic cells (P < 0.001), and mutual cell inclusions (P = 0.01) were observed more frequently in SSC+ adenocarcinomas.

CONCLUSIONS

The presence of SSCs could be an important cytological feature for predicting poor prognosis in lung adenocarcinomas.

Integrative analyses of bulk and single-cell RNA-seq identified cancer-associated fibroblasts-related signature as a prognostic factor for immunotherapy in NSCLC

An emerging view regarding cancer-associated fibroblast (CAF) is that it plays a critical role in tumorigenesis and immunosuppression in the tumor microenvironment (TME), but the clinical significance and biological functions of CAFs in non-small cell lung cancer (NSCLC) are still poorly explored. Here, we aimed to identify the CAF-related signature for NSCLC through integrative analyses of bulk and single-cell genomics, transcriptomics, and proteomics profiling. Using CAF marker genes identified in weighted gene co-expression network analysis (WGCNA), we constructed and validated a CAF-based risk model that stratifies patients into two prognostic groups from four independent NSCLC cohorts. The high-score group exhibits a higher abundance of CAFs, decreased immune cell infiltration, increased epithelial-mesenchymal transition (EMT), activated transforming growth factor beta (TGFβ) signaling, and a limited survival rate compared with the low-score group. Considering the immunosuppressive feature in the high-score group, we speculated an inferior clinical response for immunotherapy in these patients, and this association was successfully verified in two NSCLC cohorts treated with immune checkpoint blockades (ICBs). Furthermore, single-cell RNA sequence datasets were used to clarify the molecular mechanisms underlying the aggressive and immunosuppressive phenotype in the high-score group. We found that one of the genes in the risk model, filamin binding LIM protein 1 (FBLIM1), is mainly expressed in fibroblasts and upregulated in CAFs compared to fibroblasts from normal tissue. FBLIM1-positive CAF subtype was correlated with increased TGFβ expression, higher mesenchymal marker level, and immunosuppressive tumor microenvironment. Finally, we demonstrated that FBLIM1 might serve as a poor prognostic marker for immunotherapy in clinical samples. In conclusion, we identified a novel CAF-based classifier with prognostic value in NSCLC patients and those treated with ICBs. Single-cell transcriptome profiling uncovered FBLIM1-positive CAFs as an aggressive subtype with a high abundance of TGFβ, EMT, and an immunosuppressive phenotype in NSCLC.

ROLE OF STROMAL MICROENVIRONMENT IN THE FORMATION OF INVASIVE, ANGIOGENIC, AND METASTATIC POTENTIAL OF ENDOMETRIOID CARCINOMA OF ENDOMETRIUM

The aim of the study was to determine the association of indicators of the progression of endometrioid carcinoma of the endometrium (ECE) with the type of stromal microenvironment, the counts of CXCL12+ fibroblasts and CD163+ macrophages, and the expression of the chemokine CXCL12 and its receptor CXCR4 in tumor cells.

MATERIALS AND METHODS

Histological preparations of ECE samples (n = 51) were analyzed. Expression of CXCL2 and CXCR4 antigens in tumor cells, the content of CXCL12+ fibroblasts and CD163+ macrophages, and the density of microvessels were determined by the immunohistochemical method.

RESULTS

Groups of ECE with desmoplastic and inflammatory stromal reactions were delineated. The majority (80.0%) of tumors with desmoplasia were of low differentiation grade, deeply invading the myometrium; 65.0% of patients with these tumors were at stage III of the disease. In ECE cases of stages I-II, 77.4% of ECE showed an inflammatory type of stroma. The high angiogenic and invasive potential of EC of stages I-II was associated with an inflammatory stromal type, high counts of CD163+ macrophages and CXCL12+ fibroblasts in the tumor microenvironment, high expression of the chemokine receptor CXCR4, and reduced expression of its ligand CXCL12 in tumor cells. In the majority of EC of stage III, the increase in angiogenic, invasive, and metastatic potential was accompanied by the presence of desmoplastic stroma, increased expression of CXCR4 in tumor cells, and a high count of CXCL12+ fibroblasts.

CONCLUSIONS

The obtained results showed that the morphological architecture of the stromal ECE component is related to the molecular features of its constituents and tumor cells. Their interaction modulates the phenotypic characteristics of ECE associated with the degree of malignancy.

The Prognostic and therapeutic value and clinical implications of fibroblast activation protein-α as a novel biomarker in colorectal cancer

The identification of contributing factors leading to the development of Colorectal Cancer (CRC), as the third fatal malignancy, is crucial. Today, the tumor microenvironment has been shown to play a key role in CRC progression. Fibroblast-Activation Protein-α (FAP) is a type II transmembrane cell surface proteinase expressed on the surface of cancer-associated fibroblasts in tumor stroma. As an enzyme, FAP has di- and endoprolylpeptidase, endoprotease, and gelatinase/collagenase activities in the Tumor Microenvironment (TME). According to recent reports, FAP overexpression in CRC contributes to adverse clinical outcomes such as increased lymph node metastasis, tumor recurrence, and angiogenesis, as well as decreased overall survival. In this review, studies about the expression level of FAP and its associations with CRC patients' prognosis are reviewed. High expression levels of FAP and its association with clinicopathological factors have made as a potential target. In many studies, FAP has been evaluated as a therapeutic target and diagnostic factor into which the current review tries to provide a comprehensive insight. Video Abstract.

Tumor Microenvironment as a Therapeutic Target in Melanoma Treatment

The role of the tumor microenvironment in tumor growth and therapy has recently attracted more attention in research and drug development. The ability of the microenvironment to trigger tumor maintenance, progression, and resistance is the main cause for treatment failure and tumor relapse. Accumulated evidence indicates that the maintenance and progression of tumor cells is determined by components of the microenvironment, which include stromal cells (endothelial cells, fibroblasts, mesenchymal stem cells, and immune cells), extracellular matrix (ECM), and soluble molecules (chemokines, cytokines, growth factors, and extracellular vesicles). As a solid tumor, melanoma is not only a tumor mass of monolithic tumor cells, but it also contains supporting stroma, ECM, and soluble molecules. Melanoma cells are continuously in interaction with the components of the microenvironment. In the present review, we focus on the role of the tumor microenvironment components in the modulation of tumor progression and treatment resistance as well as the impact of the tumor microenvironment as a therapeutic target in melanoma.

Development of cancer-associated fibroblast-related gene signature for predicting the survival and immunotherapy response in lung adenocarcinoma

The present study aims to construct a predictive model for prognosis and immunotherapy response in lung adenocarcinoma (LUAD). Transcriptome data were extracted from the Cancer Genome Atlas (TCGA), GSE41271, and IMvigor210. The weighted gene correlation network analysis was utilized to identify the hub modules related to immune/stromal cells. Then, univariate, LASSO, and multivariate Cox regression analyses were employed to develop a predictive signature based on genes of the hub module. Moreover, the association between the predictive signature and immunotherapy response was also investigated. As a result, seven genes (FGF10, SERINE2, LSAMP, STXBP5, PDE5A, GLI2, FRMD6) were screened to develop the cancer associated fibroblasts (CAFs)-related risk signature (CAFRS). LUAD patients with high-risk score underwent shortened Overall survival (OS). A strong correlation was found between CAFRS and immune infiltrations/functions. The gene set variation analysis showed that G2/M checkpoint, epithelial-mesenchymal transition, hypoxia, glycolysis, and PI3K-Akt-mTOR pathways were greatly enriched in the high-risk subgroup. Moreover, patients with higher risk score were less likely to respond to immunotherapy. A nomogram based on CAFRS and Stage presented a stronger predictive performance for OS than the single indicator. In conclusion, the CAFRS exhibited a potent predictive value for OS and immunotherapy response in LUAD.

Nanomedicines: intervention in inflammatory pathways of cancer

Inflammation is a complex defense process that maintains tissue homeostasis. However, this complex cascade, if lasts long, may contribute to pathogenesis of several diseases. Chronic inflammation has been exhaustively studied in the last few decades, for its contribution in development and progression of cancer. The intrinsic limitations of conventional anti-inflammatory and anti-cancer therapies triggered the development of nanomedicines for more effective and safer therapies. Targeting inflammation and tumor cells by nanoparticles, encapsulated with active therapeutic agents, offers a promising outcome with patient survival. Considerable technological success has been achieved in this field through exploitation of tumor microenvironment, and recognition of molecules overexpressed on endothelial cells or macrophages, through enhanced vascular permeability, or by rendering biomimetic approach to nanoparticles. This review focusses on the inflammatory pathways in progression of a tumor, and advancement in nanotechnologies targeting these pathways. We also aim to identify the gaps that hinder the successful clinical translation of nanotherapeutics with further clinical studies that will allow oncologist to precisely identify the patients who may be benefited from nanotherapy at time when promotion or progression of tumor initiates. It is postulated that the nanomedicines, in near future, will shift the paradigm of cancer treatment and improve patient survival.

High Expression of Triggering Receptor Expressed on Myeloid Cells 1 Predicts Poor Prognosis in Glioblastoma

Background

Glioblastoma (GBM) is a highly malignant tumor with poor prognosis, and new treatment strategies are urgently needed. Currently, the role of triggering receptor expressed on myeloid cells 1 (TREM-1) in tumors has been studied, but the role of TREM-1 in GBM remains unclear.

Methods

Immunohistochemical staining for TREM-1 was performed in 91 patients diagnosed with GBM. Clinicopathological characteristics and survival times were recorded. TREM-1 expression and its effect on prognosis were analyzed using online Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA) databases. The expression profile of TCGA-GBM cohort was used to perform functional enrichment analysis. The CIBERSORT method and Tumor Immune Estimation Resource (TIMER) database were used to estimate the tumor-infiltrating immune cells (TIICs). The ESTIMATE algorithm was used to estimate the immune-stromal scores. Finally, the relationships of TREM-1 with TIICs, immune-stromal score, and immune checkpoint genes (ICGs) were analyzed.

Results

The expression of TREM-1 was upregulated in GBM, and high TREM-1 expression predicted a poor prognosis. TREM-1, surgical resection, postoperative radiotherapy, and temozolomide (TMZ) chemotherapy were associated with the survival time of patients with GBM, but only surgical resection and TREM-1 expression were independent prognostic factors. GBM with high TREM-1 expression exhibited increased neutrophil and macrophage infiltration. TREM-1 was positively associated with the immune-stromal score and multiple ICGs, and most of which were involved in immunosuppressive responses.

Conclusion

The present study revealed that high expression of TREM-1 in GBM is an independent poor prognosis factor and that TREM-1 is associated with the immunosuppressive microenvironment. Thus, blocking TREM-1 may be a strategy for enhancing the GBM immune response.

A prognostic and immunotherapeutic predictive model based on the cell-originated characterization of tumor microenvironment in lung adenocarcinoma

Tumor microenvironment (TME) plays a crucial role in predicting prognosis and response to therapy in lung cancer. Our study established a prognostic and immunotherapeutic predictive model, the tumor immune cell score (TICS), by differentiating cell origins in lung adenocarcinoma (LUAD) based on the transcriptomic data of 2,510 patients in 14 independent cohorts, including 12 public datasets and two in-house cohorts. The high TICS was associated with prolonged overall survival (OS), especially in the early-stage LUAD. For the advanced-stage LUAD, high TICS predicted a superior OS in patients who were treated with immunotherapy instead of chemotherapy or TKI. The result suggested that TICS could serve as an indicator for the prognostic stratification management of patients in the early-stage LUAD, and as a potential guide for therapeutic decision-marking in the advanced-stage LUAD. Our findings provided an insight into prognosis stratification and potential guidance for treatment strategy selection.

MHAttnSurv: Multi-head attention for survival prediction using whole-slide pathology images

Whole slide images (WSI) based survival prediction has attracted increasing interest in pathology. Despite this, extracting prognostic information from WSIs remains a challenging task due to their enormous size and the scarcity of pathologist annotations. Previous studies have utilized multiple instance learning approach to combine information from several randomly sampled patches, but this approach may not be adequate as different visual patterns may contribute unequally to prognosis prediction. In this study, we introduce a multi-head attention mechanism that allows each attention head to independently explore the utility of various visual patterns on a tumor slide, thereby enabling more comprehensive information extraction from WSIs. We evaluated our approach on four cancer types from The Cancer Genome Atlas database. Our model achieved an average c-index of 0.640, outperforming three existing state-of-the-art approaches for WSI-based survival prediction on these datasets. Visualization of attention maps reveals that the attention heads synergistically focus on different morphological patterns, providing additional evidence for the effectiveness of multi-head attention in survival prediction.

TGF-β as Predictive Marker and Pharmacological Target in Lung Cancer Approach

Lung cancer (LC) represents the leading cause of cancer incidence and mortality worldwide. LC onset is strongly related to genetic mutations and environmental interactions, such as tobacco smoking, or pathological conditions, such as chronic inflammation. Despite advancement in knowledge of the molecular mechanisms involved in LC, this tumor is still characterized by an unfavorable prognosis, and the current therapeutic options are unsatisfactory. TGF-β is a cytokine that regulates different biological processes, particularly at the pulmonary level, and its alteration has been demonstrated to be associated with LC progression. Moreover, TGF-β is involved in promoting invasiveness and metastasis, via epithelial to mesenchymal transition (EMT) induction, where TGF-β is the major driver. Thus, a TGF-β-EMT signature may be considered a potential predictive marker in LC prognosis, and TGF-β-EMT inhibition has been demonstrated to prevent metastasis in various animal models. Concerning a LC therapeutic approach, some TGF-β and TGF-β-EMT inhibitors could be used in combination with chemo- and immunotherapy without major side effects, thereby improving cancer therapy. Overall, targeting TGF-β may be a valid possibility to fight LC, both in improving LC prognosis and cancer therapy, via a novel approach that could open up new effective strategies against this aggressive cancer.

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.

Prognostic histological markers in oral tongue squamous cell carcinoma patients treated with (chemo)radiotherapy

Treatment of oral tongue squamous cell carcinoma (OTSCC) frequently includes surgery with postoperative radiotherapy (RT) or chemoradiotherapy (CRT). Resistance to RT or CRT remains a major clinical challenge and highlights the need to identify predictive markers for it. We included 71 OTSCC patients treated with surgery combined with RT or CRT. We evaluated the association between tumor budding, tumor-stroma ratio (TSR), depth of invasion (DOI), tumor-infiltrating lymphocytes (TILs), hypoxia-inducible factor-1alpha (HIF-1alpha) expression, octamer-binding transcription factor 4 (OCT4) expression, high-endothelial venules (HEVs), and disease-free survival (DFS) using uni- and multivariate analyses. No significant association was observed between the different histological and molecular markers (TSR, DOI, TILs, HEV, HIF-1alph, OCT4) and DFS. However, an associative trend between DOI, budding, and DFS was noted. Further studies with larger cohorts are needed to explore the prognostic value of DOI and budding for OTSCC patients treated with postoperative RT or CRT.

Exploiting E3 ubiquitin ligases to reeducate the tumor microenvironment for cancer therapy

Tumor development relies on a complex and aberrant tissue environment in which cancer cells receive the necessary nutrients for growth, survive through immune escape, and acquire mesenchymal properties that mediate invasion and metastasis. Stromal cells and soluble mediators in the tumor microenvironment (TME) exhibit characteristic anti-inflammatory and protumorigenic activities. Ubiquitination, which is an essential and reversible posttranscriptional modification, plays a vital role in modulating the stability, activity and localization of modified proteins through an enzymatic cascade. This review was motivated by accumulating evidence that a series of E3 ligases and deubiquitinases (DUBs) finely target multiple signaling pathways, transcription factors and key enzymes to govern the functions of almost all components of the TME. In this review, we systematically summarize the key substrate proteins involved in the formation of the TME and the E3 ligases and DUBs that recognize these proteins. In addition, several promising techniques for targeted protein degradation by hijacking the intracellular E3 ubiquitin-ligase machinery are introduced.

Tumor Microenvironmental Cytokines Drive NSCLC Cell Aggressiveness and Drug-Resistance via YAP-Mediated Autophagy

Dynamic reciprocity between cellular components of the tumor microenvironment and tumor cells occurs primarily through the interaction of soluble signals, i.e., cytokines produced by stromal cells to support cancer initiation and progression by regulating cell survival, differentiation and immune cell functionality, as well as cell migration and death. In the present study, we focused on the analysis of the functional response of non-small cell lung cancer cell lines elicited by the treatment with some crucial stromal factors which, at least in part, mimic the stimulus exerted in vivo on tumor cells by microenvironmental components. Our molecular and functional results highlight the role played by the autophagic machinery in the cellular response in terms of the invasive capacity, stemness and drug resistance of two non-small lung cancer cell lines treated with stromal cytokines, also highlighting the emerging role of the YAP pathway in the mutual and dynamic crosstalk between tumor cells and tumor microenvironment elements. The results of this study provide new insights into the YAP-mediated autophagic mechanism elicited by microenvironmental cytokines on non-small cell lung cancer cell lines and may suggest new potential strategies for future cancer therapeutic interventions.

Heterotypic signaling of cancer-associated fibroblasts in shaping the cancer cell drug resistance

The context-dependent reciprocal interaction between the cancer cells and surrounding fibroblasts is imperative for regulating malignant potential, metabolic reprogramming, immunosuppression, and ECM deposition. However, recent evidence also suggests that cancer-associated fibroblasts induce chemoresistance in cancer cells to various anticancer regimens. Because of the protumorigenic function of cancer-associated fibroblasts, these stromal cell types have emerged as fascinating therapeutic targets for cancer. However, this notion was recently challenged by studies that targeted cancer-associated fibroblasts and highlighted the underlying heterogeneity by identifying a subset of these cells with tumor-restricting functions. Hence, it is imperative to understand the heterogeneity and heterotypic signaling of cancer-associated fibroblasts to target tumor-promoting signaling processes by sparing tumor-restricting ones. In this review, we discuss the heterogeneity and heterotypic signaling of cancer-associated fibroblasts in shaping drug resistance and also list the cancer-associated fibroblast-targeting therapeutics.

Analysis of EMT induction in a non-invasive breast cancer cell line by mesenchymal stem cell supernatant: Study of 2D and 3D microfluidic based aggregate formation and migration ability, and cytoskeleton remodeling

AIMS

The process of Epithelial-to-mesenchymal transition (EMT) as a phenotypic invasive shift and the factors affecting it, are under extensive research. Application of supernatants of human adipose-derived mesenchymal stem cells (hADMSCs) on non-invasive cancer cells is a well known method of in vitro induction of EMT like process. While previous researches have focused on the effects of hADMSCs supernatant on the biochemical signaling pathways of the cells through expression of different proteins and genes, we investigated pro-carcinogic alterations of physico-mechanical cues in terms of changes in cell motility and aggregated formation in 3D microenvironments, and cytoskeletal actin-myosin content and fiber arrangement.

MAIN METHODS

MCF-7 cancer cells were treated by the supernatant from 48 hour-starved hADMSCs, and their vimentin/E-cadherin expressions were evaluated. The invasive potential of treated and non-treated cells was measured and compared through aggregate formation and migration capability. Furthermore, alterations in cell and nucleus morphologies were studied, and F-actin and myosin-II alterations in terms of content and arrangement were investigated.

KEY FINDINGS

Results indicated that application of hADMSCs supernatant enhanced vimentin expression as the biomarker of EMT, and induced pro-carcinogenic effects on non-invasive cancer cells through increased invasive potential by higher cell motility and reduced aggregate formation, rearrangement of actin structure and generation of more stress fibers, together with increased myosin II that lead to enhanced cell motility and traction force.

SIGNIFICANCE

Our results indicated that in vitro induction of EMT through mesenchymal supernatant influenced biophysical features of cancer cells through cytoskeletal remodeling that emphasizes the interconnection of chemical and physical signaling pathways during cancer progress and invasion. Results give a better insight to EMT as a biological process and the synergy between biochemical and biophysical parameters that contribute to this process, and eventually assist in improving cancer treatment strategies.

A novel basement membrane-related gene signature for prognosis of lung adenocarcinomas

BACKGROUND

Lung adenocarcinoma (LUAD) remains a global health concern with its poor prognosis and high mortality. Whether tumor cells invade through the basement membrane (BM) is the key factor to determine the prognosis of LUAD. This study aimed to identify the BM-related gene signatures to improve the overall prognosis of LUAD.

MATERIALS & METHODS

A series of bioinformatics analyses were conducted based on TCGA and GEO datasets. Unsupervised consistent cluster analysis was performed, and 500 LUAD patients were assigned to two different groups according to expressions of 222 BM-related genes. The differentially expressed genes (DEGs) between the two clusters were identified, and Lasso regression, ROC curve, univariate and multivariate Cox regression analyses and enrichment analysis were conducted. Besides, ssGSEA, CIBERSORT and ESTIMATE algorithmwere were employed to understand the relationship between the tumor microenvironment (TME) and risk scores. Moreover, single cell clustering and trajectory analyses were performed to further understand the significance of BM-related genes. Finally, qRT-PCR was used to verify the prognosis model.

RESULTS

A total of 31 prognostic BM-related genes were determined for LUAD, and a novel 17-mRNA prognostic model named BMsocre was successfully established to predict the overall survival of LUAD patients. The high BMscore group indicated worse prognosis. Seventeen DEGs were enriched mainly in metabolism, ECM-receptor interaction and immune response. In addition, the high-risk group showed higher TMB and lower immune score. The low-risk group had a better immunotherapeutic response where immune escape was less likely. The BMscore model was verified in our patient cohort. Furthermore, NELL2 was mainly expressed in clusters of T cells, and was identified to play a critical role in T-cell differentiation.

CONCLUSIONS

A novel BMscore model was successfully established and might be effective for providing guidance to LUAD therapy.

The Journey of Cancer Cells to the Brain: Challenges and Opportunities

Cancer metastases into the brain constitute one of the most severe, but not uncommon, manifestations of cancer progression. Several factors control how cancer cells interact with the brain to establish metastasis. These factors include mediators of signaling pathways participating in migration, infiltration of the blood-brain barrier, interaction with host cells (e.g., neurons, astrocytes), and the immune system. Development of novel therapies offers a glimpse of hope for increasing the diminutive life expectancy currently forecasted for patients suffering from brain metastasis. However, applying these treatment strategies has not been sufficiently effective. Therefore, there is a need for a better understanding of the metastasis process to uncover novel therapeutic targets. In this review, we follow the journey of various cancer cells from their primary location through the diverse processes that they undergo to colonize the brain. These processes include EMT, intravasation, extravasation, and infiltration of the blood-brain barrier, ending up with colonization and angiogenesis. In each phase, we focus on the pathways engaging molecules that potentially could be drug target candidates.

Constructing 3D In Vitro Models of Heterocellular Solid Tumors and Stromal Tissues Using Extrusion-Based Bioprinting

Malignant tumor tissues exhibit inter- and intratumoral heterogeneities, aberrant development, dynamic stromal composition, diverse tissue phenotypes, and cell populations growing within localized mechanical stresses in hypoxic conditions. Experimental tumor models employing engineered systems that isolate and study these complex variables using in vitro techniques are under development as complementary methods to preclinical in vivo models. Here, advances in extrusion bioprinting as an enabling technology to recreate the three-dimensional tumor milieu and its complex heterogeneous characteristics are reviewed. Extrusion bioprinting allows for the deposition of multiple materials, or selected cell types and concentrations, into models based upon physiological features of the tumor. This affords the creation of complex samples with representative extracellular or stromal compositions that replicate the biology of patient tissue. Biomaterial engineering of printable materials that replicate specific features of the tumor microenvironment offer experimental reproducibility, throughput, and physiological relevance compared to animal models. In this review, we describe the potential of extrusion-based bioprinting to recreate the tumor microenvironment within in vitro models.

Reprogramming the tumor microenvironment with biotechnology

The tumor microenvironment (TME) is a unique environment that is developed by the tumor and controlled by tumor-induced interactions with host cells during tumor progression. The TME includes immune cells, which can be classified into two types: tumor- antagonizing and tumor-promoting immune cells. Increasing the tumor treatment responses is associated with the tumor immune microenvironment. Targeting the TME has become a popular topic in research, which includes polarizing macrophage phenotype 2 into macrophage phenotype 1 using Toll-like receptor agonists with cytokines, anti-CD47, and anti-SIPRα. Moreover, inhibiting regulatory T cells through blockades and depletion restricts immunosuppressive cells in the TME. Reprogramming T cell infiltration and T cell exhaustion improves tumor infiltrating lymphocytes, such as CD8⁺ or CD4⁺ T cells. Targeting metabolic pathways, including glucose, lipid, and amino acid metabolisms, can suppress tumor growth by restricting the absorption of nutrients and adenosine triphosphate energy into tumor cells. In conclusion, these TME reprogramming strategies exhibit more effective responses using combination treatments, biomaterials, and nanoparticles. This review highlights how biomaterials and immunotherapy can reprogram TME and improve the immune activity.

The efficacy of a machine learning algorithm for assessing tumour components as a prognostic marker of surgically resected stage IA lung adenocarcinoma

BACKGROUND

The importance of the stromal components in tumour progression has been discussed widely, but their prognostic role in small size tumours with lepidic components is not fully understood. Applying digital tissue image analysis to whole-slide imaging may enhance the accuracy and reproducibility of pathological assessment. This study aimed to evaluate the prognostic value of tumour components of lung adenocarcinoma by measuring the dimensions of the tumour consisting elements separately, using a machine learning algorithm.

METHODS

Between September 2002 and December 2016, 317 patients with surgically resected, pathological stage IA adenocarcinoma with lepidic components were analysed. We assessed the whole tumour area, including the lepidic components, and measured the epithelium, collagen, elastin areas and alveolar air space. We analysed the prognostic impact of each tumour component.

RESULTS

The dimensions of the epithelium and collagen areas were independent significant risk factors for recurrence-free survival (hazard ratio, 8.38; 95% confidence interval, 1.14-61.88; P = 0.037, and hazard ratio, 2.58; 95% confidence interval, 1.14-5.83; P = 0.022, respectively). According to the subgroup analysis when combining the epithelium and collagen areas as risk factors, patients with tumours consisting of both large epithelium and collagen areas showed significantly poor prognoses (P = 0.002).

CONCLUSIONS

We assessed tumour components using a machine learning algorithm to stratify the post-operative prognosis of surgically resected stage IA adenocarcinomas. This method might guide the selection of patients with a high risk of recurrence.

Emphasis on Adipocyte Transformation: Anti-Inflammatory Agents to Prevent the Development of Cancer-Associated Adipocytes

Of the various cell types in the tumor microenvironment (TME), adipocytes undergo a dynamic transformation when activated by neighboring cancer cells. Although these adipocytes, known as cancer-associated adipocytes (CAAs), have been reported to play a crucial role in tumor progression, the factors that mediate their transformation remain elusive. In this review, we discuss the hypothesis that inflammatory signals involving NF-ĸB activation can induce lipolysis and adipocyte dedifferentiation. This provides a mechanistic understanding of CAA formation and introduces the concept of preventing adipocyte transformation via anti-inflammatory agents. Indeed, epidemiological studies indicate a higher efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) in obese patients with cancer, suggesting that NSAIDs can modulate the TME. Inhibition of cyclooxygenase-2 (COX-2) and prostaglandin production leads to the suppression of inflammatory signals such as NF-ĸB. Thus, we suggest the use of NSAIDs in cancer patients with metabolic disorders to prevent the transformation of TME components. Moreover, throughout this review, we attempt to expand our knowledge of CAA transformation to improve the clinical feasibility of targeting CAAs.

Pericentromeric satellite lncRNAs are induced in cancer-associated fibroblasts and regulate their functions in lung tumorigenesis

The abnormal tumor microenvironment (TME) often dictates the therapeutic response of cancer to chemo- and immuno-therapy. Aberrant expression of pericentromeric satellite repeats has been reported for epithelial cancers, including lung cancer. However, the transcription of tandemly repetitive elements in stromal cells of the TME has been unappreciated, limiting the optimal use of satellite transcripts as biomarkers or anti-cancer targets. We found that transcription of pericentromeric satellite DNA (satDNA) in mouse and human lung adenocarcinoma was observed in cancer-associated fibroblasts (CAFs). In vivo, lung fibroblasts expressed pericentromeric satellite repeats HS2/HS3 specifically in tumors. In vitro, transcription of satDNA was induced in lung fibroblasts in response to TGFβ, IL1α, matrix stiffness, direct contact with tumor cells and treatment with chemotherapeutic drugs. Single-cell transcriptome analysis of human lung adenocarcinoma confirmed that CAFs were the cell type with the highest number of satellite transcripts. Human HS2/HS3 pericentromeric transcripts were detected in the nucleus, cytoplasm, extracellularly and co-localized with extracellular vesicles in situ in human biopsies and activated fibroblasts in vitro. The transcripts were transmitted into recipient cells and entered their nuclei. Knock-down of satellite transcripts in human lung fibroblasts attenuated cellular senescence and blocked the formation of an inflammatory CAFs phenotype which resulted in the inhibition of their pro-tumorigenic functions. In sum, our data suggest that satellite long non-coding (lnc) RNAs are induced in CAFs, regulate expression of inflammatory genes and can be secreted from the cells, which potentially might present a new element of cell-cell communication in the TME.

Predictive role of neostromal CD10 expression in breast cancer patients treated with neoadjuvant chemotherapy

Background: The therapeutic strategy of invasive breast cancer is based on routine histopathological markers (estrogen-, progesterone receptor, HER2, Ki67) routinely evaluated in tumor cells. However, the assessment of cancer stroma could influence therapeutic strategies. Studies have shown that stromal expression of CD10, a zinc-dependent metalloproteinase, is associated with biological aggressiveness of the tumor. In the present retrospective study, we aimed to evaluate stromal CD10 expression and association between CD10 expression and response to neoadjuvant chemotherapy in invasive breast cancer. Methods: CD10 immunohistochemistry was performed on core biopsies taken before the neoadjuvant therapy. Stromal CD10 expression was determined and compared with well-known predictive and prognostic tissue markers as well as with the following groups defined according to the degree of tumor response: no regression, partial regression, and complete regression. Results: A total of 60 locally advanced invasive breast carcinomas of "no special type" were included. The proportion of CD10 positive tumors was significantly higher in the "no regression" group compared to "complete regression" group (p = 0.000). Stromal CD10 expression was found to be significantly associated with decrease in response to neoadjuvant chemotherapy. According to CD10 expression we did not find any difference in hormone receptor status, Ki67, tumor grade or neostromal area. Conclusion: Our data suggest that CD10 expression can serve as a predictive marker of the effect of neoadjuvant chemotherapy in breast cancer patients. Therefore, its inclusion into the routine assessment of biopsies to tailor tumor-specific therapeutic strategies merits consideration.

Cancer-associated fibroblasts contribute to cancer metastasis and apoptosis resistance in human ovarian cancer via paracrine SDF-1α

BACKGROUND

Cancer-associated fibroblasts (CAFs), one of the main members of stromal cells in tumor microenvironment are proposed to play a central role in promoting tumor metastasis. It is unclear whether and how CAFs mediates tumor metastasis or chemoresistance in human ovarian cancer.

METHODS

CAFs were extracted from human ovarian cancer tissues (OCs) of patients with different kinds of histological types.

RESULTS

We found that CAFs showed more aggressive potency than those tumor cells, both of which were isolated from the same ovarian cancer specimen. Moreover, when co-cultured with CAFs, cell migration abilities of ovarian cancer cells (SKOV3, OVCAR3 and HEY) were significantly increased. Next, we preliminarily detected a higher CAFs density in sections of metastatic lesions than those in primary tumor site of primary OCs clinically. However, no significant difference of stromal derived factors-1α (SDF-1α) production from CAFs was found between primary and metastatic lesions. Additionally, in contrast with tumor cells, CAFs exhibited obvious apoptosis resistance when treated with cisplatin. Furthermore, we found that cisplatin-induced cytotoxicity and apoptosis were significantly inhibited by co-cultured with recombinant human SDF-1α in SKOV3 in a time and dose-dependent manner, and this effect was suppressed by the CXCR4 antagonist AMD3100.

CONCLUSIONS

CAFs might be involved in the malignant metastasis in human ovarian cancer through promoting cell migration in tumor cells. And their resistance to cytotoxic agents might be mediated by paracrine SDF-1α/CXCR4 signaling in ovarian cancer.

A Model of Basement Membrane-Associated Gene Signature Predicts Liver Hepatocellular Carcinoma Response to Immune Checkpoint Inhibitors

Liver hepatocellular carcinoma (LIHC) is a highly lethal malignant tumor originating from the digestive system, which is a serious threat to human health. In recent years, immunotherapy has shown significant therapeutic effects in the treatment of LIHC, but only for a minority of patients. The basement membrane (BM) plays an important role in the occurrence and development of tumors, including LIHC. Therefore, this study is aimed at establishing a risk score model based on basement membrane-related genes (BMRGs) to predict patient prognosis and response to immunotherapy. First, we defined three patterns of BMRG modification (C1, C2, and C3) by consensus clustering of BMRG sets and LIHC transcriptome data obtained from public databases. Survival analysis showed that patients in the C2 group had a better prognosis, and Gene Set Variation Analysis (GSVA) revealed that the statistically significant pathways were mainly enriched in the C2 group. Moreover, we performed Weighted Correlation Network Analysis (WGCNA) on the above three subgroups and obtained 179 intersecting genes. We further applied function enrichment analyses, and the results demonstrated that they were mainly enriched in metabolism-related pathways. Furthermore, we conducted the LASSO regression analysis and obtained 4 BMRGs (MPV17, GNB1, DHX34, and MAFG) that were significantly related to the prognosis of LIHC patients. We further constructed a prognostic risk score model based on the above genes, which was verified to have good predictive performance for LIHC prognosis. In addition, we analyzed the correlation between the risk score and the tumor immune microenvironment (TIM), and the results showed that the high-risk scoring group tended to be in an immunosuppressed status. Finally, we investigated the relationship between the risk score and LIHC immune function. The results demonstrated that the risk score was closely related to the expression levels of multiple immune checkpoints. Patients in the low-risk group had significantly higher IPS scores, and patients in the high-risk group had lower immune escape and TIDE score. In conclusion, we established a novel risk model based on BMRGs, which may serve as a biomarker for prognosis and immunotherapy in LIHC.

Fighting Carcinogenesis with Plant Metabolites by Weakening Proliferative Signaling and Disabling Replicative Immortality Networks of Rapidly Dividing and Invading Cancerous Cells

BACKGROUND

Cancer, an uncontrolled multistage disease causing swift division of cells, is a leading disease with the highest mortality rate. Cellular heterogeneity, evading growth suppressors, resisting cell death, and replicative immortality drive the tumor progression by resisting the therapeutic action of existing anticancer drugs through a series of intrinsic and extrinsic cellular interactions. The innate cellular mechanisms also regulate the replication process as a fence against proliferative signaling, enabling replicative immortality through telomere dysfunction.

AREA COVERED

The conventional genotoxic drugs have several off-target and collateral side effects associated with them. Thus, the need for the therapies targeting cyclin-dependent kinases or P13K signaling pathway to expose cancer cells to immune destruction, deactivation of invasion and metastasis, and maintaining cellular energetics is imperative. Compounds with anticancer attributes isolated from plants and rich in alkaloids, terpenes, and polyphenols have proven to be less toxic and highly targetspecific, making them biologically significant. This has opened a gateway for the exploration of more novel plant molecules by signifying their role as anticancer agents in synergy and alone, making them more effective than the existing cytotoxic regimens.

EXPERT OPINION

In this context, the current review presented recent data on cancer cases around the globe, along with discussing the fundamentals of proliferative signaling and replicative immortality of cancer cells. Recent findings were also highlighted, including antiproliferative and antireplicative action of plant-derived compounds, besides explaining the need for improving drug delivery systems.

Genetic and phenotypic determinants of morphologies in 3D cultures and xenografts of lung tumor cell lines

We previously proposed the classification of lung adenocarcinoma into two groups: the bronchial epithelial phenotype (BE phenotype) with high-level expressions of bronchial epithelial markers and actionable genetic abnormalities of tyrosine kinase receptors and the non-BE phenotype with low-level expressions of bronchial Bronchial epithelial (BE) epithelial markers and no actionable genetic abnormalities of tyrosine kinase receptors. Here, we performed a comprehensive analysis of tumor morphologies in 3D cultures and xenografts across a panel of lung cancer cell lines. First, we demonstrated that 40 lung cancer cell lines (23 BE and 17 non-BE) can be classified into three groups based on morphologies in 3D cultures on Matrigel: round (n = 31), stellate (n = 5), and grape-like (n = 4). The latter two morphologies were significantly frequent in the non-BE phenotype (1/23 BE, 8/17 non-BE, p = 0.0014), and the stellate morphology was only found in the non-BE phenotype. SMARCA4 mutations were significantly frequent in stellate-shaped cells (4/4 stellate, 4/34 non-stellate, p = 0.0001). Next, from the 40 cell lines, we successfully established 28 xenograft tumors (18 BE and 10 non-BE) in NOD/SCID mice and classified histological patterns of the xenograft tumors into three groups: solid (n = 20), small nests in desmoplasia (n = 4), and acinar/papillary (n = 4). The latter two patterns were characteristically found in the BE phenotype. The non-BE phenotype exhibited a solid pattern with significantly less content of alpha-SMA-positive fibroblasts (p = 0.0004) and collagen (p = 0.0006) than the BE phenotype. Thus, the morphology of the tumors in 3D cultures and xenografts, including stroma genesis, reflects the intrinsic properties of the cancer cell lines. Furthermore, this study serves as an excellent resource for lung adenocarcinoma cell lines, with clinically relevant information on molecular and morphological characteristics and drug sensitivity.

Integrated Analysis Revealed an Inflammatory Cancer-Associated Fibroblast-Based Subtypes with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Bladder Cancer Patients

Inflammatory cancer-associated fibroblasts (iCAFs) are closely related to progression, anticancer therapeutic resistance, and poor prognosis of bladder cancer (BCa). However, the functional role of iCAFs in BCa has been poorly studied. In our study, two BCa scRNA-seq datasets (GSE130001 and GSE146137) were obtained and integrated by the Seurat pipeline. Based on reported markers (COL1A1 and PDGFRA), iCAFs were identified and the related signature of 278 markers was developed. Following unsupervised consensus clustering, two molecular subtypes of TCGA-BLCA were identified and characterized by distinct dysregulated cancer hallmarks, immunological tumor microenvironments, prognoses, responses to chemotherapy/immunotherapy, and stemness. Subsequently, the robustness of the signature-based clustering, in terms of prognosis and therapeutic response prediction, was validated in a GEO-meta cohort with seven independent GEO datasets of 519 BCa patients, and three immune checkpoint inhibitor (ICI)-treated cohorts. Considering the heterogeneity, re-clustering of iCAFs was performed and a subpopulation, named "LOXL2+ iCAFs", was identified. Co-culture CM derived from LOXL2 overexpression/silencing CAFs with T24 cells revealed that overexpression of LOXL2 in CAFs promoted while silencing LOXL2 inhibited the proliferation, migration, and invasion of T24 cells through IL32. Moreover, the positive correlation between LOXL2 and CD206, an M2 macrophage polarization marker, has been observed and validated. Collectively, integrated single-cell and bulk RNA sequencing analyses revealed an iCAF-related signature that can predict prognosis and response to immunotherapy for BCa. Additionally, the hub gene LOXL2 may serve as a promising target for BCa treatment.

Multi-scale pathology image texture signature is a prognostic factor for resectable lung adenocarcinoma: a multi-center, retrospective study

BACKGROUND

Tumor histomorphology analysis plays a crucial role in predicting the prognosis of resectable lung adenocarcinoma (LUAD). Computer-extracted image texture features have been previously shown to be correlated with outcome. However, a comprehensive, quantitative, and interpretable predictor remains to be developed.

METHODS

In this multi-center study, we included patients with resectable LUAD from four independent cohorts. An automated pipeline was designed for extracting texture features from the tumor region in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) at multiple magnifications. A multi-scale pathology image texture signature (MPIS) was constructed with the discriminative texture features in terms of overall survival (OS) selected by the LASSO method. The prognostic value of MPIS for OS was evaluated through univariable and multivariable analysis in the discovery set (n = 111) and the three external validation sets (V₁, n = 115; V₂, n = 116; and V₃, n = 246). We constructed a Cox proportional hazards model incorporating clinicopathological variables and MPIS to assess whether MPIS could improve prognostic stratification. We also performed histo-genomics analysis to explore the associations between texture features and biological pathways.

RESULTS

A set of eight texture features was selected to construct MPIS. In multivariable analysis, a higher MPIS was associated with significantly worse OS in the discovery set (HR 5.32, 95%CI 1.72-16.44; P = 0.0037) and the three external validation sets (V₁: HR 2.63, 95%CI 1.10-6.29, P = 0.0292; V₂: HR 2.99, 95%CI 1.34-6.66, P = 0.0075; V₃: HR 1.93, 95%CI 1.15-3.23, P = 0.0125). The model that integrated clinicopathological variables and MPIS had better discrimination for OS compared to the clinicopathological variables-based model in the discovery set (C-index, 0.837 vs. 0.798) and the three external validation sets (V₁: 0.704 vs. 0.679; V₂: 0.728 vs. 0.666; V₃: 0.696 vs. 0.669). Furthermore, the identified texture features were associated with biological pathways, such as cytokine activity, structural constituent of cytoskeleton, and extracellular matrix structural constituent.

CONCLUSIONS

MPIS was an independent prognostic biomarker that was robust and interpretable. Integration of MPIS with clinicopathological variables improved prognostic stratification in resectable LUAD and might help enhance the quality of individualized postoperative care.

CD5L-associated gene analyses highlight the dysregulations, prognostic effects, immune associations, and drug-sensitivity predicative potentials of LCAT and CDC20 in hepatocellular carcinoma

BACKGROUND

The dysregulation of CD5L has been reported in hepatocellular carcinoma (HCC). However, its functions in HCC were controversial. In this study, we aimed to identify CD5L-associated pathways and markers and explore their values in HCC diagnosis, prognosis and treatment.

METHODS

HCC datasets with gene expression profiles and clinical data in TCGA and ICGC were downloaded. The immune/stroma cell infiltrations were estimated with xCell. CD5L-associated pathways and CD5L-associated genes (CD5L-AGs) were identified with gene expression comparisons and gene set enrichment analysis (GSEA). Cox regression, Kaplan-Meier survival analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were performed. The correlations of the key genes with immune/stroma infiltrations, immunoregulators, and anti-cancer drug sensitivities in HCC were investigated. At protein level, the key genes dysregulations, their correlations and prognostic values were validated in clinical proteomic tumor analysis consortium (CPTAC) database. Serum CD5L and LCAT activity in 50 HCC and 30 normal samples were evaluated and compared. The correlations of serum LCAT activity with alpha-fetoprotein (AFP), albumin (ALB) and high-density lipoprotein (HDL) in HCC were also investigated.

RESULTS

Through systemic analyses, 14 CD5L-associated biological pathways, 256 CD5L-AGs and 28 CD5L-associated prognostic and diagnostic genes (CD5L-APDGs) were identified. A risk model consisting of LCAT and CDC20 was constructed for HCC overall survival (OS), which could discriminate HCC OS status effectively in both the training and the validation sets. CD5L, LCAT and CDC20 were shown to be significantly correlated with immune/stroma cell infiltrations, immunoregulators and 31 anti-cancer drug sensitivities in HCC. At protein level, the dysregulations of CD5L, LCAT and CDC20 were confirmed. LCAT and CDC20 were shown to be significantly correlated with proliferation marker MKI67. In serum, no significance of CD5L was shown. However, the lower activity of LCAT in HCC serum was obvious, as well as its significant positive correlations ALB and HDL concentrations.

CONCLUSIONS

CD5L, LCAT and CDC20 were dysregulated in HCC both at mRNA and protein levels. The LCAT-CDC20 signature might be new predicator for HCC OS. The associations of the three genes with HCC microenvironment and anti-cancer drug sensitivities would provide new clues for HCC immunotherapy and chemotherapy.

Targeting cancer-associated fibroblasts: Challenges, opportunities and future directions

Cancer-associated fibroblasts (CAFs) are a common cell in the tumour microenvironment with diverse tumour-promoting functions. Their presence in tumours is commonly associated with poor prognosis making them attractive therapeutic targets, particularly in the context of immunotherapy where CAFs have been shown to promote resistance to checkpoint blockade. Previous attempts to inhibit CAFs clinically have not been successful, however, in part due to a lack of understanding of CAF heterogeneity and function, with some fibroblast populations potentially being tumour suppressive. Recent single-cell transcriptomic studies have advanced our understanding of fibroblast phenotypes in normal tissues and cancers, allowing for a more precise characterisation of CAF subsets and providing opportunities to develop new therapies. Here we review recent advances in the field, focusing on the evolving area of therapeutic CAF targeting.

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

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

Extracellular matrix profiles determine risk and prognosis of the squamous cell carcinoma subtype of non-small cell lung carcinoma

BACKGROUND

Squamous cell carcinoma (SqCC) is a subtype of non-small cell lung cancer for which patient prognosis remains poor. The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness remains to be comprehensively characterized.

METHODS

Multi-omics data of SqCC human tumor specimens was combined to characterize ECM features associated with initiation and recurrence. Penalized logistic regression was used to define a matrix risk signature for SqCC tumors and its performance across a panel of tumor types and in SqCC premalignant lesions was evaluated. Consensus clustering was used to define prognostic matreotypes for SqCC tumors. Matreotype-specific tumor biology was defined by integration of bulk RNAseq with scRNAseq data, cell type deconvolution, analysis of ligand-receptor interactions and enriched biological pathways, and through cross comparison of matreotype expression profiles with aging and idiopathic pulmonary fibrosis lung profiles.

RESULTS

This analysis revealed subtype-specific ECM signatures associated with tumor initiation that were predictive of premalignant progression. We identified an ECM-enriched tumor subtype associated with the poorest prognosis. In silico analysis indicates that matrix remodeling programs differentially activate intracellular signaling in tumor and stromal cells to reinforce matrix remodeling associated with resistance and progression. The matrix subtype with the poorest prognosis resembles ECM remodeling in idiopathic pulmonary fibrosis and may represent a field of cancerization associated with elevated cancer risk.

CONCLUSIONS

Collectively, this analysis defines matrix-driven features of poor prognosis to inform precision medicine prevention and treatment strategies towards improving SqCC patient outcome.

Tissue-Specific Human Extracellular Matrix Scaffolds Promote Pancreatic Tumour Progression and Chemotherapy Resistance

Over 80% of patients with pancreatic ductal adenocarcinoma (PDAC) are diagnosed at a late stage and are locally advanced or with concurrent metastases. The aggressive phenotype and relative chemo- and radiotherapeutic resistance of PDAC is thought to be mediated largely by its prominent stroma, which is supported by an extracellular matrix (ECM). Therefore, we investigated the impact of tissue-matched human ECM in driving PDAC and the role of the ECM in promoting chemotherapy resistance. Decellularized human pancreata and livers were recellularized with PANC-1 and MIA PaCa-2 (PDAC cell lines), as well as PK-1 cells (liver-derived metastatic PDAC cell line). PANC-1 cells migrated into the pancreatic scaffolds, MIA PaCa-2 cells were able to migrate into both scaffolds, whereas PK-1 cells were able to migrate into the liver scaffolds only. These differences were supported by significant deregulations in gene and protein expression between the pancreas scaffolds, liver scaffolds, and 2D culture. Moreover, these cell lines were significantly more resistant to gemcitabine and doxorubicin chemotherapy treatments in the 3D models compared to 2D cultures, even after confirmed uptake by confocal microscopy. These results suggest that tissue-specific ECM provides the preserved native cues for primary and metastatic PDAC cells necessary for a more reliable in vitro cell culture.

KIAA1199 Correlates With Tumor Microenvironment and Immune Infiltration in Lung Adenocarcinoma as a Potential Prognostic Biomarker

Background: KIAA1199 has been considered a key regulator of carcinogenesis. However, the relationship between KIAA1199 and immune infiltrates, as well as its prognostic value in lung adenocarcinoma (LUAD) remains unclear. Methods: The expression of KIAA1199 and its influence on tumor prognosis were analyzed using a series of databases, comprising TIMER, GEPIA, UALCAN, LCE, Prognoscan and Kaplan-Meier Plotter. Further, immunohistochemistry (IHC), western blot (WB) and receiver operating characteristic (ROC) curve analyses were performed to verify our findings. The cBioPortal was used to investigate the genomic alterations of KIAA1199. Prediction of candidate microRNA (miRNAs) and transcription factor (TF) targeting KIAA1199, as well as GO and KEGG analyses, were performed based on LinkedOmics. TIMER and TISIDB databases were used to explore the relationship between KIAA1199 and tumor immune infiltration. Results: High expression of KIAA1199 was identified in LUAD and Lung squamous cell carcinoma (LUSC) patients. High expression of KIAA1199 indicated a worse prognosis in LUAD patients. The results of IHC and WB analyses showed that the expression level of KIAA1199 in tumor tissues was higher than that in adjacent tissues. GO and KEGG analyses indicated KIAA1199 was mainly involved in extracellular matrix (ECM)-receptor interaction and extracellular matrix structure constituent. KIAA1199 was positively correlated with infiltrating levels of CD4+ T cells, macrophages, neutrophil cells, dendritic cells, and showed positive relationship with immune marker subsets expression of a variety of immunosuppressive cells. Conclusion: High expression of KIAA1199 predicts a poor prognosis of LUAD patients. KIAA1199 might exert its carcinogenic role in the tumor microenvironment via participating in the extracellular matrix formation and regulating the infiltration of immune cells in LUAD. The results indicate that KIAA1199 might be a novel biomarker for evaluating prognosis and immune cell infiltration in LUAD.

Mechanics of lung cancer: A finite element model shows strain amplification during early tumorigenesis

Early lung cancer lesions develop within a unique microenvironment that undergoes constant cyclic stretch from respiration. While tumor stiffening is an established driver of tumor progression, the contribution of stress and strain to lung cancer is unknown. We developed tissue scale finite element models of lung tissue to test how early lesions alter respiration-induced strain. We found that an early tumor, represented as alveolar filling, amplified the strain experienced in the adjacent alveolar walls. Tumor stiffening further increased the amplitude of the strain in the adjacent alveolar walls and extended the strain amplification deeper into the normal lung. In contrast, the strain experienced in the tumor proper was less than the applied strain, although regions of amplification appeared at the tumor edge. Measurements of the alveolar wall thickness in clinical and mouse model samples of lung adenocarcinoma (LUAD) showed wall thickening adjacent to the tumors, consistent with cellular response to strain. Modeling alveolar wall thickening by encircling the tumor with thickened walls moved the strain amplification radially outward, to the next adjacent alveolus. Simulating iterative thickening in response to amplified strain produced tracks of thickened walls. We observed such tracks in early-stage clinical samples. The tracks were populated with invading tumor cells, suggesting that strain amplification in very early lung lesions could guide pro-invasive remodeling of the tumor microenvironment. The simulation results and tumor measurements suggest that cells at the edge of a lung tumor and in surrounding alveolar walls experience increased strain during respiration that could promote tumor progression.

Crosstalk of necroptosis and pyroptosis defines tumor microenvironment characterization and predicts prognosis in clear cell renal carcinoma

Pyroptosis and necroptosis are two recently identified forms of immunogenic cell death in the tumor microenvironment (TME), indicating a crucial involvement in tumor metastasis. However, the characteristics of necroptosis and pyroptosis that define tumor microenvironment and prognosis in ccRCC patients remain unknown. We systematically investigated the transcriptional variation and expression patterns of Necroptosis and Pyroptosis related genes (NPRGs). After screening the necroptosis-pyroptosis clusters, the potential functional annotation for clusters was explored by GSVA enrichment analysis. The Necroptosis-Pyroptosis Genes (NPG) scores were used for the prognosis model construction and validation. Then, the correlations of NPG score with clinical features, cancer stem cell (CSC) index, tumor mutation burden (TMB), TME, and Immune Checkpoint Genes (ICGs) were also individually explored to evaluate the prognosis predictive values in ccRCC. Microarray screenings identified 27 upregulated and 1 downregulated NPRGs. Ten overall survival associated NPRGs were filtered to construct the NPG prognostic model indicating a better prognostic signature for ccRCC patients with lower NPG scores (P< 0.001), which was verified using the external cohort. Univariate and multivariate analyses along with Kaplan-Meier survival analysis demonstrated that NPG score prognostic model could be applied as an independent prognostic factor, and AUC values of nomogram from 1- to 5- year overall survival with good agreement in calibration plots suggested that the proposed prognostic signature possessed good predictive capabilities in ccRCC. A high-/sNPG score is proven to be connected with tumor growth and immune-related biological processes, according to enriched GO, KEGG, and GSEA analyses. Comparing patients with a high-NPG score to those with a low-NPG score revealed significant differences in clinical characteristics, growth and recurrence of malignancies (CSC index), TME cell infiltration, and immunotherapeutic response (P< 0.005), potentially making the NPG score multifunctional in the clinical therapeutic setting. Furthermore, AIM2, CASP4, GSDMB, NOD2, and RBCK1 were also found to be highly expressed in ccRCC cell lines and tumor tissues, and GASP4 and GSDMB promote ccRCC cells’ proliferation, migration, and invasion. This study firstly suggests that targeting the NPG score feature for TME characterization may lend novel insights into its clinical applications in the prognostic prediction of ccRCC.

Insights Into the Role of Matrix Metalloproteinases in Cancer and its Various Therapeutic Aspects: A Review

Matrix metalloproteinases (MMPs) are zinc-dependent endopeptidases that regulate the turnover of extracellular matrix (ECM) components. Gross and La Piere discovered MMPs in 1962 during an experiment on tissue samples from a tadpole’s tail. Several subtypes of MMPs have been identified, depending on their substrate specificity and localization. MMPs are involved as essential molecules in multiple and diverse physiological processes, such as reproduction, embryonic development, bone remodeling, tissue repair, and regulation of inflammatory processes. Its activity is controlled at various levels such as at transcription level, pro-peptide activation level and by the activity of a family of tissue inhibitors of metalloproteinase, endogenous inhibitors of MMPs. Cancer metastasis, which is the spread of a tumor to a distant site, is a complex process that is responsible for the majority of cancer-related death It is considered to be an indicator of cancer metastasis. During metastasis, the tumor cells have to invade the blood vessel and degrade the ECM to make a path to new loci in distant places. The degradation of blood vessels and ECM is mediated through the activity of MMPs. Hence, the MMP activity is critical to determining the metastatic potential of a cancer cell. Evasion of apoptosis is one of the hallmarks of cancer that are found to be correlated with the expression of MMPs. As a result, given the importance of MMPs in cancer, we describe the role of these multifunctional enzymes MMPs in various aspects of cancer formation and their rising possibilities as a novel therapeutic target in this review. There is also a brief discussion of various types of therapeutic components and drugs that function against MMPs.

An EMT-based risk score thoroughly predicts the clinical prognosis, tumor immune microenvironment and molecular subtypes of bladder cancer

Background

Epithelial mesenchymal transition (EMT) is closely related to the occurrence, development, metastasis and antitumor immunity of tumors. However, comprehensive studies correlating EMT and prognosis, tumor microenvironment (TME) and molecular subtypes of bladder cancer (BLCA) are lacking.

Methods

TCGA-BLCA was chosen as our training cohort, while Xiangya cohort, GSE13507, GSE48075 were selected as our validation cohorts. Prognostic genes were screened out using univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Then we developed an EMT risk score based on these prognostic genes and systematically correlated the risk score with prognosis, TME and molecular subtypes of BLCA.

Results

Based on EMT related genes, we developed two different EMT patterns, named EMT cluster 1 and cluster 2, and found that cluster 2 showed a worse prognosis and an inflammatory TME phenotype. For personalized prognosis and TME phenotypes predicting, we developed and validated an EMT-based risk score by 7 candidate genes (ANXA10, CNTN1, FAM180A, FN1, IGFL2, KANK4 and TOX3). Patients with high EMT risk scores had lower overall survival (OS) with high predictive accuracy both in the training cohort and validation cohort. In addition, we comprehensively correlated the EMT risk score with TME and molecular subtype, and found that high EMT risk score suggested higher levels of immune cell infiltration and more inclined to present the basal molecular subtype. It was noteworthy that the same results also appeared in the validation of Xiangya cohort.

Conclusions

EMT related genes play an important role in tumor progression and immunity in BLCA. Our EMT risk score could accurately predict prognosis and immunophenotype of a single patient, which could guide more effective precision medical strategies.

Combination of Tumor Mutational Burden and DNA Damage Repair Gene Mutations with Stromal/Immune Scores Improved Prognosis Stratification in Patients with Lung Adenocarcinoma

Background

Both the tumor environment and the genomic landscape of lung cancer may shape patient responses to treatments, including immunotherapy, but their joint impacts on lung adenocarcinoma (LUAD) prognosis are underexplored.

Methods

RNA sequencing data and whole-exome sequencing results were downloaded from the TCGA database, and only LUAD-related data were included in this study. Based on gene expression data, the ESTIMATE algorithm was used to estimate stromal and immune scores, and CIBERSORT analysis was used for quantification of the relative abundances of immune cells. Somatic mutations were used for calculating tumor mutation burden (TMB). Specific mutations in genes involved in DNA damage repair (DDR) pathways were identified. The individual and joint associations of stromal and immune score, TMB, and DDR gene mutations with 5-year survival were analyzed by the Kaplan–Meier method and multivariate Cox model.

Results

LUAD patients with a high (>highest 25%) stromal or immune score had prolonged survival as compared to those with a low (<lowest 25%) score (log-rank P=0.05 and 0.035, respectively). Patients with both high stromal and immune scores had the most favorable survival. Although the survival differences between patients with high (>highest 25%) and low (<lowest 25%) TMB, or between patients with mutant- and wild-type DDR genes were not statistically significant, a survival benefit from high TMB or DDR gene mutations was observed in patients with high stromal or immune scores.

Conclusion

A comprehensive evaluation of transcriptomic signatures and genomic biomarkers may provide a novel avenue for improving prognosis stratification in LUAD.