Temporal profiling of the breast tumour microenvironment reveals collagen XII as a driver of metastasis

Histoplasty Modification of the Tumor Microenvironment in a Murine Preclinical Model of Breast Cancer

PURPOSE

To develop a noninvasive therapeutic approach able to alter the biophysical organization and physiology of the extracellular matrix (ECM) in breast cancer.

MATERIALS AND METHODS

In a 4T1 murine model of breast cancer, histoplasty treatment with a proprietary 700-kHz multielement therapy transducer using a coaxially aligned ultrasound (US) imaging probe was used to target the center of an ex vivo tumor and deliver subablative acoustic energy. Tumor collagen morphology was qualitatively evaluated before and after histoplasty with second harmonic generation. Separately, mice bearing bilateral 4T1 tumors (n = 4; total tumors = 8) were intravenously injected with liposomal doxorubicin. The right flank tumor was histoplasty-treated, and tumors were fluorescently imaged to detect doxorubicin uptake after histoplasty treatment. Next, 4T1 tumor-bearing mice were randomized into 2 treatment groups (sham vs histoplasty, n = 3 per group). Forty-eight hours after sham/histoplasty treatment, tumors were harvested and analyzed using flow cytometry.

RESULTS

Histoplasty significantly increased (P = .002) liposomal doxorubicin diffusion into 4T1 tumors compared with untreated tumors (2.12- vs 1.66-fold increase over control). Flow cytometry on histoplasty-treated tumors (n = 3) demonstrated a significant increase in tumor macrophage frequency (42% of CD45 vs 33%; P = .022) and a significant decrease in myeloid-derived suppressive cell frequency (7.1% of CD45 vs 10.3%; P = .044). Histoplasty-treated tumors demonstrated increased CD8+ (5.1% of CD45 vs 3.1%; P = .117) and CD4+ (14.1% of CD45 vs 11.8%; P = .075) T-cell frequency.

CONCLUSIONS

Histoplasty is a nonablative focused US approach to noninvasively modify the tumor ECM, increase chemotherapeutic uptake, and alter the tumor immune microenvironment.

LncRNA MAGI2-AS3-Encoded Polypeptide Restrains the Proliferation and Migration of Breast Cancer Cells

Accumulating articles have reported the coding potential of long non-coding RNAs (lncRNAs). However, only a few lncRNAs-encoded peptides have been studied. Breast cancer (BRCA) progression-related gene modules were determined by weighted gene co-expression network analysis (WGCNA). Cell viability, proliferation, and migration capacities were assessed by Cell counting kit-8 (CCK8), 5-ethynyl-2'-deoxyuridine (EdU), and transwell assays. Immunofluorescence (IF) assay was implemented to observe protein expression. Co-immunoprecipitation (Co-IP) and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) were employed to analyze MAGI2 antisense RNA 3 (MAGI2-AS3)-ORF5-interacted proteins. WGCNA identified that MEpurple and MEblack modules were significantly negatively correlated with T stage in BRCA patients. MAGI2-AS3 was screened as one of the differentially expressed (DE) lncRNAs with translational potential in MEblack and MEpurple modules in BRCA. The data in The Cancer Genome Atlas (TCGA) uncovered that MAGI2-AS3 abundance was significantly decreased in invasive BRCA patients, and it had high diagnostic and prognostic values. MAGI2-AS3-ORF5 notably restrained BRCA cell viability, proliferation, and migration. Mechanically, MAGI2-AS3-ORF5 might affect the progression of BRCA cells by binding to extracellular matrix (ECM)-related proteins. MAGI2-AS3-ORF5 played an anti-tumor role by inhibiting BRCA cell viability, proliferation, and migration. MAGI2-AS3-ORF5 might modulate BRCA cell migration through ECM-associated proteins.

Targets in the Tumour Matrisome to Promote Cancer Therapy Response

The extracellular matrix (ECM) is composed of complex fibrillar proteins, proteoglycans, and macromolecules, generated by stromal, immune, and cancer cells. The components and organisation of the matrix evolves as tumours progress to invasive disease and metastasis. In many solid tumours, dense fibrotic ECM has been hypothesised to impede therapy response by limiting drug and immune cell access. Interventions to target individual components of the ECM, collectively termed the matrisome, have, however, revealed complex tumour-suppressor, tumour-promoter, and immune-modulatory functions, which have complicated clinical translation. The degree to which distinct components of the matrisome can dictate tumour phenotypes and response to therapy is the subject of intense study. A primary aim is to identify therapeutic opportunities within the matrisome, which might support a better response to existing therapies. Many matrix signatures have been developed which can predict prognosis, immune cell content, and immunotherapy responses. In this review, we will examine key components of the matrisome which have been associated with advanced tumours and therapy resistance. We have primarily focussed here on targeting matrisome components, rather than specific cell types, although several examples are described where cells of origin can dramatically affect tumour roles for matrix components. As we unravel the complex biochemical, biophysical, and intracellular transduction mechanisms associated with the ECM, numerous therapeutic opportunities will be identified to modify tumour progression and therapy response.

Biomimetic "nano-spears" for CAFs-targeting: splintered three "shields" with enhanced cisplatin anti-TNBC efficiency

The treatment dilemma of triple-negative breast cancer (TNBC) revolves around drug resistance and metastasis. Cancer-associated fibroblasts (CAFs) contribute to cisplatin (Cis) resistance and further metastasis in TNBC, making TNBC a difficult-to-treat disease. The dense stromal barrier which restricts drug delivery, invasive phenotype of tumor cells, and immunosuppressive tumor microenvironment (TME) induced by CAFs serve as three "shields" for TNBC against Cis therapy. Here, we designed a silybin-loaded biomimetic nanoparticle coated with anisamide-modified red blood cell membrane (ARm@SNP) as a "nanospear" for CAFs-targeting, which could shatter the "shields" and significantly exhibit inhibitory effect on 4T1 cells in combination with Cis both in vitro and in vivo. The ARm@SNP/Cis elicited 4T1 tumor growth arrest and destroyed three "shields" as follows: disintegrating the stromal barrier by inhibiting blood vessels growth and the expression of fibronectin; decreasing 4T1 cell invasion and metastasis by affecting the TGF-β/Twist/EMT pathway which impeded EMT activation; reversing the immunosuppressive microenvironment by increasing the activity and infiltration of immunocompetent cells. Based on CAFs-targeting, ARm@SNP reversed the resistance of Cis, remodeled the TME and inhibited invasion and metastasis while significantly improving the therapeutic effect of Cis on 4T1 tumor-bearing mice, providing a promising approach for treating intractable TNBC.

Peptide set test: a peptide-centric strategy to infer differentially expressed proteins

MOTIVATION

The clinical translation of mass spectrometry-based proteomics has been challenging due to limited statistical power caused by large technical variability and inter-patient heterogeneity. Bottom-up proteomics provides an indirect measurement of proteins through digested peptides. This raises the question whether peptide measurements can be used directly to better distinguish differentially expressed proteins.

RESULTS

We present a novel method called the peptide set test, which detects coordinated changes in the expression of peptides originating from the same protein and compares them to the rest of the peptidome. Applying our method to data from a published spike-in experiment and simulations demonstrates improved sensitivity without compromising precision, compared to aggregation-based approaches. Additionally, applying the peptide set test to compare the tumor proteomes of tamoxifen-sensitive and tamoxifen-resistant breast cancer patients reveals significant alterations in peptide levels of collagen XII, suggesting an association between collagen XII-mediated matrix reassembly and tamoxifen resistance. Our study establishes the peptide set test as a powerful peptide-centric strategy to infer differential expression in proteomics studies.

AVAILABILITY AND IMPLEMENTATION

Peptide set test (PepSetTest) is publicly available at https://github.com/JmWangBio/PepSetTest.

Understanding the matrix: collagen modifications in tumors and their implications for immunotherapy

Tumors are highly complex and heterogenous ecosystems where malignant cells interact with healthy cells and the surrounding extracellular matrix (ECM). Solid tumors contain large ECM deposits that can constitute up to 60% of the tumor mass. This supports the survival and growth of cancerous cells and plays a critical role in the response to immune therapy. There is untapped potential in targeting the ECM and cell-ECM interactions to improve existing immune therapy and explore novel therapeutic strategies. The most abundant proteins in the ECM are the collagen family. There are 28 different collagen subtypes that can undergo several post-translational modifications (PTMs), which alter both their structure and functionality. Here, we review current knowledge on tumor collagen composition and the consequences of collagen PTMs affecting receptor binding, cell migration and tumor stiffness. Furthermore, we discuss how these alterations impact tumor immune responses and how collagen could be targeted to treat cancer.

Tumor Biomechanics Alters Metastatic Dissemination of Triple Negative Breast Cancer via Rewiring Fatty Acid Metabolism

In recent decades, the role of tumor biomechanics on cancer cell behavior at the primary site has been increasingly appreciated. However, the effect of primary tumor biomechanics on the latter stages of the metastatic cascade, such as metastatic seeding of secondary sites and outgrowth remains underappreciated. This work sought to address this in the context of triple negative breast cancer (TNBC), a cancer type known to aggressively disseminate at all stages of disease progression. Using mechanically tuneable model systems, mimicking the range of stiffness's typically found within breast tumors, it is found that, contrary to expectations, cancer cells exposed to softer microenvironments are more able to colonize secondary tissues. It is shown that heightened cell survival is driven by enhanced metabolism of fatty acids within TNBC cells exposed to softer microenvironments. It is demonstrated that uncoupling cellular mechanosensing through integrin β1 blocking antibody effectively causes stiff primed TNBC cells to behave like their soft counterparts, both in vitro and in vivo. This work is the first to show that softer tumor microenvironments may be contributing to changes in disease outcome by imprinting on TNBC cells a greater metabolic flexibility and conferring discrete cell survival advantages.

CAF-associated genes putatively representing distinct prognosis by in silico landscape of stromal components of colon cancer

Comprehensive understanding prognostic relevance of distinct tumor microenvironment (TME) remained elusive in colon cancer. In this study, we performed in silico analysis of the stromal components of primary colon cancer, with a focus on the markers of cancer-associated fibroblasts (CAF) and tumor-associated endothelia (TAE), as well as immunological infiltrates like tumor-associated myeloid cells (TAMC) and cytotoxic T lymphocytes (CTL). The relevant CAF-associated genes (CAFG)(representing R index = 0.9 or beyond with SPARC) were selected based on stroma specificity (cancer stroma/epithelia, cS/E = 10 or beyond) and expression amounts, which were largely exhibited negative prognostic impacts. CAFG were partially shared with TAE-associated genes (TAEG)(PLAT, ANXA1, and PTRF) and TAMC-associated genes (TAMCG)(NNMT), but not with CTL-associated genes (CTLG). Intriguingly, CAFG were prognostically subclassified in order of fibrosis (representing COL5A2, COL5A1, and COL12A1) followed by exclusive TAEG and TAMCG. Prognosis was independently stratified by CD8A, a CTL marker, in the context of low expression of the strongest negative prognostic CAFG, COL8A1. CTLG were comprehensively identified as IFNG, B2M, and TLR4, in the group of low S/E, representing good prognosis. Our current in silico analysis of the micro-dissected stromal gene signatures with prognostic relevance clarified comprehensive understanding of clinical features of the TME and provides deep insights of the landscape.

Nitric oxide nano-reactor DNMF/PLGA enables tumor vascular microenvironment and chemo-hyperthermia synergetic therapy

BACKGROUND

Breast cancer ranks first among malignant tumors, of which triple-negative breast cancer (TNBC) is characterized by its highly invasive behavior and the worst prognosis. Timely diagnosis and precise treatment of TNBC are substantially challenging. Abnormal tumor vessels play a crucial role in TNBC progression and treatment. Nitric oxide (NO) regulates angiogenesis and maintains vascular homeostasis, while effective NO delivery can normalize the tumor vasculature. Accordingly, we have proposed here a tumor vascular microenvironment remodeling strategy based on NO-induced vessel normalization and extracellular matrix collagen degradation with multimodality imaging-guided nanoparticles against TNBC called DNMF/PLGA.

RESULTS

Nanoparticles were synthesized using a chemotherapeutic agent doxorubicin (DOX), a NO donor L-arginine (L-Arg), ultrasmall spinel ferrites (MnFe2O4), and a poly (lactic-co-glycolic acid) (PLGA) shell. Nanoparticle distribution in the tumor was accurately monitored in real-time through highly enhanced magnetic resonance imaging and photoacoustic imaging. Near-infrared irradiation of tumor cells revealed that MnFe2O4 catalyzes the production of a large amount of reactive oxygen species (ROS) from H2O2, resulting in a cascade catalysis of L-Arg to trigger NO production in the presence of ROS. In addition, DOX activates niacinamide adenine dinucleotide phosphate oxidase to generate and supply H2O2. The generated NO improves the vascular endothelial cell integrity and pericellular contractility to promote vessel normalization and induces the activation of endogenous matrix metalloproteinases (mainly MMP-1 and MMP-2) so as to promote extravascular collagen degradation, thereby providing an auxiliary mechanism for efficient nanoparticle delivery and DOX penetration. Moreover, the chemotherapeutic effect of DOX and the photothermal effect of MnFe2O4 served as a chemo-hyperthermia synergistic therapy against TNBC.

CONCLUSION

The two therapeutic mechanisms, along with an auxiliary mechanism, were perfectly combined to enhance the therapeutic effects. Briefly, multimodality image-guided nanoparticles provide a reliable strategy for the potential application in the fight against TNBC.

Comprehensive Matrisome Profiling of Human Adipose Tissue for Soft Tissue Reconstruction

For effective translation of research from tissue engineering and regenerative medicine domains, the cell-instructive extracellular matrix (ECM) of specific tissues must be accurately realized. As adipose tissue is gaining traction as a biomaterial for soft tissue reconstruction, with highly variable clinical outcomes obtained, a quantitative investigation of the adipose tissue matrisome is overdue. In this study, the human adipose tissue matrisome is profiled using quantitative sequential windowed acquisition of all theoretical fragment ion spectra - mass spectrometry (SWATH-MS) proteomics across a cohort of 13 fat-grafting patients, to provide characterization of ECM proteins within the tissue, and to understand human population variation. There are considerable differences in the expression of matrisome proteins across the patient cohort, with age and lipoaspirate collection technique contributing to the greatest variation across the core matrisome. A high abundance of basement membrane proteins (collagen IV and heparan sulfate proteoglycan) is detected, as well as fibrillar collagens I and II, reflecting the hierarchical structure of the tissue. This study provides a comprehensive proteomic evaluation of the adipose tissue matrisome and contributes to an enhanced understanding of the influence of the matrisome in adipose-related pathologies by providing a healthy reference cohort and details an experimental pipeline that can be further exploited for future biomaterial development.

Extracellular matrix dynamics: A key regulator of cell migration across length-scales and systems

The interactions between cells and their surrounding extracellular matrix (ECM) are dynamic and play critical roles in cell migration during development, health, and diseases. Recent advances have highlighted the complexity and diversity of ECM compositions, or "matrisomes", of tissues resulting in ECMs of different physical, mechanical, and biochemical properties. Investigating the effects of these properties on cell-ECM interactions in the context of cell migration have led to a better understanding of the principles underlying tissue morphogenesis, wound healing, immune response, or cancer metastasis. These new insights into the interplay between ECM dynamics and cell migration can lead to the identification of unique opportunities for therapeutic interventions.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Longitudinal plasma proteome profiling reveals the diversity of biomarkers for diagnosis and cetuximab therapy response of colorectal cancer

Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.

Cell-cell communication characteristics in breast cancer metastasis

Breast cancer, a highly fatal disease due to its tendency to metastasize, is the most prevalent form of malignant tumors among women worldwide. Numerous studies indicate that breast cancer exhibits a unique predilection for metastasis to specific organs including the bone, liver, lung, and brain. However, different types of, The understanding of the heterogeneity of metastatic breast cancer has notably improved with the recent advances in high-throughput sequencing techniques. Focusing on the modification in the microenvironment of the metastatic organs and the crosstalk between tumor cells and in situ cells, noteworthy research points include the identification of two distinct modes of tumor growth in bone metastases, the influence of type II pneumocyte on lung metastases, the paradoxical role of Kupffer cells in liver metastases, and the breakthrough of the blood-brain barrier (BBB) breach in brain metastases. Overall, this review provides a comprehensive overview of the characteristics of breast cancer metastases, shedding light on the pivotal roles of immune and resident cells in the development of distinct metastatic foci.

Nano- and Microstructures of Collagen-Nanocellulose Hydrogels as Engineered Extracellular Matrices

The extracellular matrix (ECM) is the fundamental acellular element of human tissues, providing their mechanical structure while delivering biomechanical and biochemical signals to cells. Three-dimensional (3D) tissue models commonly use hydrogels to recreate the ECM in vitro and support the growth of cells as organoids and spheroids. Collagen-nanocellulose (COL-NC) hydrogels rely on the blending of both polymers to design matrices with tailorable physical properties. Despite the promising application of these biomaterials in 3D tissue models, the architecture and network organization of COL-NC remain unclear. Here, we investigate the structural effects of incorporating NC fibers into COL hydrogels by small-angle neutron scattering (SANS) and ultra-SANS (USANS). The critical hierarchical structure parameters of fiber dimensions, interfiber distance, and coassembled open structures of NC and COL in the absence and presence of cells were determined. We found that NC expanded and increased the homogeneity in the COL network without affecting the inherent fiber properties of both polymers. Cells cultured as spheroids in COL-NC remodeled the hydrogel network without a significant impact on its architecture. Our study reveals the polymer organization of COL-NC hydrogels and demonstrates SANS and USANS as exceptional techniques to reveal nano- and micron-scale details on polymer organization, which leads to a better understanding of the structural properties of hydrogels to engineer novel ECMs.

EMID2 is a novel biotherapeutic for aggressive cancers identified by in vivo screening

BACKGROUND

New drugs to tackle the next pathway or mutation fueling cancer are constantly proposed, but 97% of them are doomed to fail in clinical trials, largely because they are identified by cellular or in silico screens that cannot predict their in vivo effect.

METHODS

We screened an Adeno-Associated Vector secretome library (> 1000 clones) directly in vivo in a mouse model of cancer and validated the therapeutic effect of the first hit, EMID2, in both orthotopic and genetic models of lung and pancreatic cancer.

RESULTS

EMID2 overexpression inhibited both tumor growth and metastatic dissemination, consistent with prolonged survival of patients with high levels of EMID2 expression in the most aggressive human cancers. Mechanistically, EMID2 inhibited TGFβ maturation and activation of cancer-associated fibroblasts, resulting in more elastic ECM and reduced levels of YAP in the nuclei of cancer cells.

CONCLUSION

This is the first in vivo screening, precisely designed to identify proteins able to interfere with cancer cell invasiveness. EMID2 was selected as the most potent protein, in line with the emerging relevance of the tumor extracellular matrix in controlling cancer cell invasiveness and dissemination, which kills most of cancer patients.

Integrating single-cell and bulk transcriptomic analyses to develop a cancer-associated fibroblast-derived biomarker for predicting prognosis and therapeutic response in breast cancer

Background

Cancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA.

Methods

CAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA.

Results

Integrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA.

Conclusions

A novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA.

Distinguished biomimetic dECM system facilitates early detection of metastatic breast cancer cells

Breast cancer is the most prevalent malignant tumor affecting women's health. Bone is the most common distant metastatic organ, worsening the quality of life and increasing the mortality of patients. Early detection of breast cancer bone metastasis is urgent for halting disease progression and improving tumor prognosis. Recently, extracellular matrix (ECM) with biomimetic tissue niches opened a new avenue for tumor models in vitro. Here, we developed a biomimetic decellularized ECM (dECM) system to recapitulate bone niches at different situations, bone mimetic dECM from osteoblasts (BM-ECM) and bone tumor mimetic dECM from osteosarcoma cells (OS-ECM). The two kinds of dECMs exhibited distinct morphology, protein composition, and distribution. Interestingly, highly metastatic breast cancer cells tended to adhere and migrate on BM-ECM, while lowly metastatic breast cancer cells preferred the OS-ECM niche. Epithelial-to-mesenchymal transition was a potential mechanism to initiate the breast cancer cell migration on different biomimetic dECMs. Importantly, in the nude mice model, the dECM system captured metastatic breast cancer cells as early as 10 days after orthotopic transplantation in mammary gland pads, with higher signal on BM-ECM than that on OS-ECM. Collectively, the biomimetic dECM system might be a promising tumor model to distinguish the metastatic ability of breast cancer cells in vitro and to facilitate early detection of metastatic breast cancer cells in vivo, contributing to the diagnosis of breast cancer bone metastasis.

The collagen landscape in cancer: profiling collagens in tumors and in circulation reveals novel markers of cancer-associated fibroblast subtypes

Cancer-associated fibroblasts (CAFs) deposit and remodel collagens in the tumor stroma, impacting cancer progression and efficacy of interventions. CAFs are the focus of new therapeutics with the aim of normalizing the tumor microenvironment. To do this, a better understanding of CAF heterogeneity and collagen composition in cancer is needed. In this study, we sought to profile the expression of collagens at multiple levels with the goal of identifying cancer biomarkers. We investigated the collagen expression pattern in various cell types and CAF subtypes in a publicly available single-cell RNA sequencing (RNA-seq) dataset of pancreatic ductal adenocarcinoma. Next, we investigated the collagen expression profile in tumor samples across cancer types from The Cancer Genome Atlas (TCGA) database and evaluated if specific patterns of collagen expression were associated with prognosis. Finally, we profiled circulating collagen peptides using a panel of immunoassays to measure collagen fragments in the serum of cancer patients. We found that pancreatic stellate cells and fibroblasts were the primary producers of collagens in the pancreas. COL1A1, COL3A1, COL5A1, COL6A1 were expressed in all CAF subtypes, whereas COL8A1, COL10A1, COL11A1, COL12A1 were specific to myofibroblast CAFs (myCAF) and COL14A1 specific to inflammatory CAFs (iCAF). In TCGA database, myCAF collagens COL10A1 and COL11A1 were elevated across solid tumor types, and multiple associations between high expression and worse survival were found. Finally, circulating collagen biomarkers were elevated in the serum of patients with cancer relative to healthy controls with COL11A1 (myCAF) having the best diagnostic accuracy of the markers measured. In conclusion, CAFs express a noncanonical collagen profile with specific collagen subtypes associated with iCAFs and myCAFs in PDAC. These collagens are deregulated at the cellular, tumor, and systemic levels across different solid tumors and associate with survival. These findings could lead to new discoveries such as novel biomarkers and therapeutic targets. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Engineered Adoptive T-Cell Therapies for Breast Cancer: Current Progress, Challenges, and Potential

Breast cancer remains a significant health challenge, and novel treatment approaches are critically needed. This review presents an in-depth analysis of engineered adoptive T-cell therapies (E-ACTs), an innovative frontier in cancer immunotherapy, focusing on their application in breast cancer. We explore the evolving landscape of chimeric antigen receptor (CAR) and T-cell receptor (TCR) T-cell therapies, highlighting their potential and challenges in targeting breast cancer. The review addresses key obstacles such as target antigen selection, the complex breast cancer tumor microenvironment, and the persistence of engineered T-cells. We discuss the advances in overcoming these barriers, including strategies to enhance T-cell efficacy. Finally, our comprehensive analysis of the current clinical trials in this area provides insights into the future possibilities and directions of E-ACTs in breast cancer treatment.

Personalized tumor combination therapy optimization using the single-cell transcriptome

BACKGROUND

The precise characterization of individual tumors and immune microenvironments using transcriptome sequencing has provided a great opportunity for successful personalized cancer treatment. However, the cancer treatment response is often characterized by in vitro assays or bulk transcriptomes that neglect the heterogeneity of malignant tumors in vivo and the immune microenvironment, motivating the need to use single-cell transcriptomes for personalized cancer treatment.

METHODS

Here, we present comboSC, a computational proof-of-concept study to explore the feasibility of personalized cancer combination therapy optimization using single-cell transcriptomes. ComboSC provides a workable solution to stratify individual patient samples based on quantitative evaluation of their personalized immune microenvironment with single-cell RNA sequencing and maximize the translational potential of in vitro cellular response to unify the identification of synergistic drug/small molecule combinations or small molecules that can be paired with immune checkpoint inhibitors to boost immunotherapy from a large collection of small molecules and drugs, and finally prioritize them for personalized clinical use based on bipartition graph optimization.

RESULTS

We apply comboSC to publicly available 119 single-cell transcriptome data from a comprehensive set of 119 tumor samples from 15 cancer types and validate the predicted drug combination with literature evidence, mining clinical trial data, perturbation of patient-derived cell line data, and finally in-vivo samples.

CONCLUSIONS

Overall, comboSC provides a feasible and one-stop computational prototype and a proof-of-concept study to predict potential drug combinations for further experimental validation and clinical usage using the single-cell transcriptome, which will facilitate and accelerate personalized tumor treatment by reducing screening time from a large drug combination space and saving valuable treatment time for individual patients. A user-friendly web server of comboSC for both clinical and research users is available at www.combosc.top . The source code is also available on GitHub at https://github.com/bm2-lab/comboSC .

Decellularized diseased tissues: current state-of-the-art and future directions

Decellularized matrices derived from diseased tissues/organs have evolved in the most recent years, providing novel research perspectives for understanding disease occurrence and progression and providing accurate pseudo models for developing new disease treatments. Although decellularized matrix maintaining the native composition, ultrastructure, and biomechanical characteristics of extracellular matrix (ECM), alongside intact and perfusable vascular compartments, facilitates the construction of bioengineered organ explants in vitro and promotes angiogenesis and tissue/organ regeneration in vivo, the availability of healthy tissues and organs for the preparation of decellularized ECM materials is limited. In this paper, we review the research advancements in decellularized diseased matrices. Considering that current research focuses on the matrices derived from cancers and fibrotic organs (mainly fibrotic kidney, lungs, and liver), the pathological characterizations and the applications of these diseased matrices are mainly discussed. Additionally, a contrastive analysis between the decellularized diseased matrices and decellularized healthy matrices, along with the development in vitro 3D models, is discussed in this paper. And last, we have provided the challenges and future directions in this review. Deep and comprehensive research on decellularized diseased tissues and organs will promote in-depth exploration of source materials in tissue engineering field, thus providing new ideas for clinical transformation.

Crosstalk and plasticity driving between cancer-associated fibroblasts and tumor microenvironment: significance of breast cancer metastasis

Cancer-associated fibroblasts (CAFs) are the most abundant stromal cell population in breast tumors. A functionally diverse population of CAFs increases the dynamic complexity of the tumor microenvironment (TME). The intertwined network of the TME facilitates the interaction between activated CAFs and breast cancer cells, which can lead to the proliferation and invasion of breast cells. Considering the special transmission function of CAFs, the aim of this review is to summarize and highlight the crosstalk between CAFs and breast cancer cells in the TME as well as the relationship between CAFs and extracellular matrix (ECM), soluble cytokines, and other stromal cells in the metastatic state. The crosstalk between cancer-associated fibroblasts and tumor microenvironment also provides a plastic therapeutic target for breast cancer metastasis. In the course of the study, the inhibitory effects of different natural compounds on targeting CAFs and the advantages of different drug combinations were summarized. CAFs are also widely used in the diagnosis and treatment of breast cancer. The cumulative research on this phenomenon supports the establishment of a targeted immune microenvironment as a possible breakthrough in the prevention of invasive metastasis of breast cancer.

Quantifying in vivo collagen reorganization during immunotherapy in murine melanoma with second harmonic generation imaging

Significance

Increased collagen linearization and deposition during tumorigenesis can impede immune cell infiltration and lead to tumor metastasis. Although melanoma is well studied in immunotherapy research, studies that quantify collagen changes during melanoma progression and treatment are lacking.

Aim

Image in vivo collagen in preclinical melanoma models during immunotherapy and quantify the collagen phenotype in treated and control mice.

Approach

Second harmonic generation imaging of collagen was performed in mouse melanoma tumors in vivo over a treatment time-course. Animals were treated with a curative radiation and immunotherapy combination. Collagen morphology was quantified over time at an image and single fiber level using CurveAlign and CT-FIRE software.

Results

In immunotherapy-treated mice, collagen reorganized toward a healthy phenotype, including shorter, wider, curlier collagen fibers, with modestly higher collagen density. Temporally, collagen fiber straightness and length changed late in treatment (Day 9 and 12) while width and density changed early (Day 6) compared to control mice. Single fiber level collagen analysis was most sensitive to the changes between treatment groups compared to image level analysis.

Conclusions

Quantitative second harmonic generation imaging can provide insight into collagen dynamics in vivo during immunotherapy, with key implications in improving immunotherapy response in melanoma and other cancers.

Defined extracellular matrix compositions support stiffness-insensitive cell spreading and adhesion signaling

Integrin-dependent adhesion to the extracellular matrix (ECM) mediates mechanosensing and signaling in response to altered microenvironmental conditions. In order to provide tissue- and organ-specific cues, the ECM is composed of many different proteins that temper the mechanical properties and provide the necessary structural diversity. Despite most human tissues being soft, the prevailing view from predominantly in vitro studies is that increased stiffness triggers effective cell spreading and activation of mechanosensitive signaling pathways. To address the functional coupling of ECM composition and matrix rigidity on compliant substrates, we developed a matrix spot array system to screen cell phenotypes against different ECM mixtures on defined substrate stiffnesses at high resolution. We applied this system to both cancer and normal cells and surprisingly identified ECM mixtures that support stiffness-insensitive cell spreading on soft substrates. Employing the motor-clutch model to simulate cell adhesion on biochemically distinct soft substrates, with varying numbers of available ECM-integrin-cytoskeleton (clutch) connections, we identified conditions in which spreading would be supported on soft matrices. Combining simulations and experiments, we show that cell spreading on soft is supported by increased clutch engagement on specific ECM mixtures and even augmented by the partial inhibition of actomyosin contractility. Thus, "stiff-like" spreading on soft is determined by a balance of a cell's contractile and adhesive machinery. This provides a fundamental perspective for in vitro mechanobiology studies, identifying a mechanism through which cells spread, function, and signal effectively on soft substrates.

Embedded Bioprinting of Breast Tumor Cells and Organoids Using Low-Concentration Collagen-Based Bioinks

Bioinks for 3D bioprinting of tumor models should not only meet printability requirements but also accurately maintain and support phenotypes of tumor surrounding cells to recapitulate key tumor hallmarks. Collagen is a major extracellular matrix protein for solid tumors, but low viscosity of collagen solution has made 3D bioprinted cancer models challenging. This work produces embedded, bioprinted breast cancer cells and tumor organoid models using low-concentration collagen I based bioinks. The biocompatible and physically crosslinked silk fibroin hydrogel is used to generate the support bath for the embedded 3D printing. The composition of the collagen I based bioink is optimized with a thermoresponsive hyaluronic acid-based polymer to maintain the phenotypes of both the noninvasive epithelial and invasive breast cancer cells, as well as cancer-associated fibroblasts. Mouse breast tumor organoids are bioprinted using optimized collagen bioink to mimic in vivo tumor morphology. A vascularized tumor model is also created using a similar strategy, with significantly enhanced vasculature formation under hypoxia. This study shows the great potential of embedded bioprinted breast tumor models utilizing a low-concentration collagen-based bioink for advancing the understanding of tumor cell biology and facilitating drug discovery research.

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

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

Identification of a basement membrane-related genes signature to predict prognosis, immune landscape and guide therapy in gastric cancer

The basement membrane is an essential defense against cancer progression and is intimately linked to the tumor immune microenvironment. However, there is limited research comprehensively discussing the potential application of basement membrane-related genes (BMRGs) in the prognosis evaluation and immunotherapy of gastric cancer (GC). The RNA-seq data and clinical information of GC patients were collected from the TCGA and GEO database. Prognosis-associated BMRGs were filtered via univariate Cox regression analysis. The 4-BMRGs signatures were constructed by lasso regression. Prognostic predictive accuracy of the 4-BMRGs signature was appraised with survival analysis, receiver operating characteristic curves, and nomogram. Gene set enrichment analysis (GSEA), gene ontology, and gene set variation analysis were performed to dig out potential mechanisms and functions. The Estimate algorithm and ssGSEA were used for assessing the tumor microenvironment and immunological characteristics. Identification of molecular subtypes by consensus clustering. Drug sensitivity analysis using the "pRRophetic" R package. Immunotherapy validation with immunotherapy cohort. A 4-BMRGs signature was constructed, which could excellently predict the GC patient prognosis (5-year AUC value of 0.873). Kaplan-Meier and Cox regression analyses showed that the 4-BMRGs signature was an OS-independent prognostic factor, and that higher risk scores were associated with shorter OS. The high-risk subgroup exhibits a higher abundance of immune cell infiltration, such as macrophages. Additionally, we observed a strong correlation between 2 BMRGs (LUM, SPARC) and immune cells such as CD8 + T cells and macrophages. The high-risk subgroup appears to be more sensitive to Axitinib, DMOG, Gemcitabine and Docetaxel by pRRophetic analysis. Furthermore, the validation of the cohort that received immune therapy revealed that patients in the high-risk group who underwent immune checkpoint inhibitor treatment exhibited better response rates. Pan-cancer analysis also shows that risk scores are strongly associated with immune and carcinogenic pathways. The 4-BMRGs signature has demonstrated accuracy and reliability in predicting the GC patient's prognosis and could assist in the formulation of clinical strategies.

Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

Bladder cancer was one of the most common carcinomas around the world. However, the mechanism of the disease still remained to be investigated. We expected to establish a prognostic survival model with 9 prognostic genes to predict overall survival (OS) in patients of bladder cancer. The gene expression data of bladder cancer were obtained from TCGA and GEO datasets. TCGA and GEO datasets were used for screening prognostic genes along with developing and validating a 9-gene prognostic survival model by method of weighted gene co-expression network analysis (WGCNA) and LASSO with Cox regression. The relative analysis of evaluate tumor burden mutation (TBM), GO, KEGG, chemotherapy drug and functional pathway were also performed based on CAF-related mRNAs. 151 Overlapping CAF-related genes were distinguished after intersecting differentially expressed genes from 945 genes in TCGA and 491 genes in GEO dataset. 9 Prognostic genes (MSRB2, AGMAT, KLF6, DDAH2, GADD45B, SERPINE2, STMN3, TEAD2, and COMP) were used for construction of prognostic model after LASSO with Cox regression. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. Functional analysis indicated chemokine, cytokine, ECM interaction, oxidative stress and apoptosis were highly appeared. Potential drugs targeted different CAF-related genes like vemurafenib, irofulven, ghiotepa, and idarubicin were found as well. We constructed a novel 9 CAF-related mRNAs prognostic model and explored the gene expression and potential functional information of related genes, which might be worthy of clinical application. In addition, potential chemotherapy drugs could provide useful insights into the potential clinical treatment of bladder cancer.

Cracking the pattern of tumor evolution based on single-cell copy number alterations

Copy number alterations (CNAs) are a key characteristic of tumor development and progression. The accumulation of various CNAs during tumor development plays a critical role in driving tumor evolution. Heterogeneous clones driven by distinct CNAs have different selective advantages, leading to differential patterns of tumor evolution that are essential for developing effective cancer therapies. Recent advances in single-cell sequencing technology have enabled genome-wide copy number profiling of tumor cell populations at single-cell resolution. This has made it possible to explore the evolutionary patterns of CNAs and accurately discover the mechanisms of intra-tumor heterogeneity. Here, we propose a two-step statistical approach that distinguishes neutral, linear, branching and punctuated evolutionary patterns for a tumor cell population based on single-cell copy number profiles. We assessed our approach using a variety of simulated and real single-cell genomic and transcriptomic datasets, demonstrating its high accuracy and robustness in predicting tumor evolutionary patterns. We applied our approach to single-cell DNA sequencing data from 20 breast cancer patients and observed that punctuated evolution is the dominant evolutionary pattern in breast cancer. Similar conclusions were drawn when applying the approach to single-cell RNA sequencing data obtained from 132 various cancer patients. Moreover, we found that differential immune cell infiltration is associated with specific evolutionary patterns. The source code of our study is available at https://github.com/FangWang-SYSU/PTEM.

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.

Regulation of tumor immunity and immunotherapy by the tumor collagen extracellular matrix

It has been known for decades that the tumor extracellular matrix (ECM) is dysfunctional leading to loss of tissue architecture and promotion of tumor growth. The altered ECM and tumor fibrogenesis leads to tissue stiffness that act as a physical barrier to immune cell infiltration into the tumor microenvironment (TME). It is becoming increasingly clear that the ECM plays important roles in tumor immune responses. A growing body of data now indicates that ECM components also play a more active role in immune regulation when dysregulated ECM components act as ligands to interact with receptors on immune cells to inhibit immune cell subpopulations in the TME. In addition, immunotherapies such as checkpoint inhibitors that are approved to treat cancer are often hindered by ECM changes. In this review we highlight the ways by which ECM alterations affect and regulate immunity in cancer. More specifically, how collagens and major ECM components, suppress immunity in the complex TME. Finally, we will review how our increased understanding of immune and immunotherapy regulation by the ECM is leading towards novel disruptive strategies to overcome immune suppression.

Effective methods for bulk RNA-seq deconvolution using scnRNA-seq transcriptomes

BACKGROUND

RNA profiling technologies at single-cell resolutions, including single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq, scnRNA-seq for short), can help characterize the composition of tissues and reveal cells that influence key functions in both healthy and disease tissues. However, the use of these technologies is operationally challenging because of high costs and stringent sample-collection requirements. Computational deconvolution methods that infer the composition of bulk-profiled samples using scnRNA-seq-characterized cell types can broaden scnRNA-seq applications, but their effectiveness remains controversial.

RESULTS

We produced the first systematic evaluation of deconvolution methods on datasets with either known or scnRNA-seq-estimated compositions. Our analyses revealed biases that are common to scnRNA-seq 10X Genomics assays and illustrated the importance of accurate and properly controlled data preprocessing and method selection and optimization. Moreover, our results suggested that concurrent RNA-seq and scnRNA-seq profiles can help improve the accuracy of both scnRNA-seq preprocessing and the deconvolution methods that employ them. Indeed, our proposed method, Single-cell RNA Quantity Informed Deconvolution (SQUID), which combines RNA-seq transformation and dampened weighted least-squares deconvolution approaches, consistently outperformed other methods in predicting the composition of cell mixtures and tissue samples.

CONCLUSIONS

We showed that analysis of concurrent RNA-seq and scnRNA-seq profiles with SQUID can produce accurate cell-type abundance estimates and that this accuracy improvement was necessary for identifying outcomes-predictive cancer cell subclones in pediatric acute myeloid leukemia and neuroblastoma datasets. These results suggest that deconvolution accuracy improvements are vital to enabling its applications in the life sciences.

Fibroblast-derived matrix models desmoplastic properties and forms a prognostic signature in cancer progression

The desmoplastic reaction observed in many cancers is a hallmark of disease progression and prognosis, particularly in breast and pancreatic cancer. Stromal-derived extracellular matrix (ECM) is significantly altered in desmoplasia, and as such plays a critical role in driving cancer progression. Using fibroblast-derived matrices (FDMs), we show that cancer cells have increased growth on cancer associated FDMs, when compared to FDMs derived from non-malignant tissue (normal) fibroblasts. We assess the changes in ECM characteristics from normal to cancer-associated stroma at the primary tumor site. Compositional, structural, and mechanical analyses reveal significant differences, with an increase in abundance of core ECM proteins, coupled with an increase in stiffness and density in cancer-associated FDMs. From compositional changes of FDM, we derived a 36-ECM protein signature, which we show matches in large part with the changes in pancreatic ductal adenocarcinoma (PDAC) tumor and metastases progression. Additionally, this signature also matches at the transcriptomic level in multiple cancer types in patients, prognostic of their survival. Together, our results show relevance of FDMs for cancer modelling and identification of desmoplastic ECM components for further mechanistic studies.

IGFBP2 secretion by mammary adipocytes limits breast cancer invasion

The progression of noninvasive ductal carcinoma in situ to invasive ductal carcinoma for patients with breast cancer results in a significantly poorer prognosis and is the precursor to metastatic disease. In this work, we have identified insulin-like growth factor-binding protein 2 (IGFBP2) as a potent adipocrine factor secreted by healthy breast adipocytes that acts as a barrier against invasive progression. In line with this role, adipocytes differentiated from patient-derived stromal cells were found to secrete IGFBP2, which significantly inhibited breast cancer invasion. This occurred through binding and sequestration of cancer-derived IGF-II. Moreover, depletion of IGF-II in invading cancer cells using small interfering RNAs or an IGF-II-neutralizing antibody ablated breast cancer invasion, highlighting the importance of IGF-II autocrine signaling for breast cancer invasive progression. Given the abundance of adipocytes in the healthy breast, this work exposes the important role they play in suppressing cancer progression and may help expound upon the link between increased mammary density and poorer prognosis.

Cell-extracellular matrix mechanotransduction in 3D

Mechanical properties of extracellular matrices (ECMs) regulate essential cell behaviours, including differentiation, migration and proliferation, through mechanotransduction. Studies of cell-ECM mechanotransduction have largely focused on cells cultured in 2D, on top of elastic substrates with a range of stiffnesses. However, cells often interact with ECMs in vivo in a 3D context, and cell-ECM interactions and mechanisms of mechanotransduction in 3D can differ from those in 2D. The ECM exhibits various structural features as well as complex mechanical properties. In 3D, mechanical confinement by the surrounding ECM restricts changes in cell volume and cell shape but allows cells to generate force on the matrix by extending protrusions and regulating cell volume as well as through actomyosin-based contractility. Furthermore, cell-matrix interactions are dynamic owing to matrix remodelling. Accordingly, ECM stiffness, viscoelasticity and degradability often play a critical role in regulating cell behaviours in 3D. Mechanisms of 3D mechanotransduction include traditional integrin-mediated pathways that sense mechanical properties and more recently described mechanosensitive ion channel-mediated pathways that sense 3D confinement, with both converging on the nucleus for downstream control of transcription and phenotype. Mechanotransduction is involved in tissues from development to cancer and is being increasingly harnessed towards mechanotherapy. Here we discuss recent progress in our understanding of cell-ECM mechanotransduction in 3D.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

The crosstalk between anoikis and epithelial-mesenchymal transition and their synergistic roles in predicting prognosis in colon adenocarcinoma

Anoikis and epithelial-mesenchymal transition (EMT) are significant phenomena occurring in distant metastasis of colon adenocarcinoma (COAD). A comprehensive understanding of their crosstalk and the identification of key genes are vital for treating the distant metastasis of COAD. The objective of this study was to design and validate accurate prognostic predictors for COAD patients based on the anoikis and EMT processes. We obtained gene signatures from various databases and performed univariate and multivariate Cox regression analyses, principal component analysis (PCA). The COAD patients were categorized into the worst prognosis group, the Anoikis Potential Index (API) Low + EMT Potential Index (EPI) High group and the others group. Then we utilized gene set enrichment analysis (GSEA) to identify differentially expressed genes and to establish a prognostic risk model. The model classified patients into high- or low-risk groups, with patients in the high-risk group displaying worse survival status. A nomogram was established to predict overall survival rates, demonstrating high specificity and sensitivity. Additionally, we connected the risk model to the tumor microenvironment (TME) using single-sample GSEA and the MCP counter tool, as well as evaluated the sensitivity to common chemotherapeutic drugs, such as Gefitinib and Gemcitabine. Lastly, cell and tissue experiments suggested a positive correlation among anoikis resistance, EMT, and liver/lung metastasis of COAD. This is the first study to comprehensively analyze the crosstalk between anoikis and EMT and offers new therapeutic targets for COAD metastasis patients.

Membrane trafficking in breast cancer progression: protein kinase D comes into play

Protein kinase D (PKD) is a serine/threonine kinase family that controls important cellular functions, most notably playing a key role in the secretory pathway at the trans-Golgi network. Aberrant expression of PKD isoforms has been found mainly in breast cancer, where it promotes various cellular processes such as growth, invasion, survival and stem cell maintenance. In this review, we discuss the isoform-specific functions of PKD in breast cancer progression, with a particular focus on how the PKD controlled cellular processes might be linked to deregulated membrane trafficking and secretion. We further highlight the challenges of a therapeutic approach targeting PKD to prevent breast cancer progression.

Tumor-Associated Fibrosis Impairs the Response to Immunotherapy

Previously, impaired responses to immunotherapy in cancer had been attributed mainly to inherent tumor characteristics (tumor cell intrinsic factors) such as low immunogenicity, (low) mutational burden, weak host immune system, etc. However, mapping the responses of immunotherapeutic regimes in clinical trials for different types of cancer has pointed towards an obvious commonality - that tumors with a rich fibrotic stroma respond poorly or not at all. This has prompted a harder look on tumor cell extrinsic factors such as the surrounding tumor microenvironment (TME), and specifically, the fibrotic stroma as a potential enabler of immunotherapy failure. Indeed, the role of cancer-associated fibrosis in impeding efficacy of immunotherapy is now well-established. In fact, recent studies reveal a complex interconnection between fibrosis and treatment efficacy. Accordingly, in this review we provide a general overview of what a tumor associated fibrotic reaction is and how it interacts with the members of immune system that are frequently seen to be modulated in a failed immunotherapeutic regime.

Molecular breast cancer subtype identification using photoacoustic spectral analysis and machine learning at the biomacromolecular level

Breast cancer threatens the health of women worldwide, and its molecular subtypes largely determine the therapy and prognosis of patients. However, an uncomplicated and accurate method to identify subtypes is currently lacking. This study utilized photoacoustic spectral analysis (PASA) based on the partial least squares discriminant algorithm (PLS-DA) to identify molecular breast cancer subtypes at the biomacromolecular level in vivo. The area of power spectrum density (APSD) was extracted to semi-quantify the biomacromolecule content. The feature wavelengths were obtained via the variable importance in projection (VIP) score and the selectivity ratio (Sratio), to identify the biomarkers. The PASA achieved an accuracy of 84%. Most of the feature wavelengths fell into the collagen-dominated absorption waveband, which was consistent with the histopathological results. This paper proposes a successful method for identifying molecular breast cancer subtypes and proves that collagen can be treated as a biomarker for molecular breast cancer subtyping.

Everybody needs good neighbours: the progressive DCIS microenvironment

Ductal carcinoma in situ (DCIS) is a pre-invasive form of breast cancer where neoplastic luminal cells are confined to the ductal tree. While as many as 70% of DCIS cases will remain indolent, most women are treated with surgery, often combined with endocrine and radiotherapies. Overtreatment is therefore a major issue, demanding new methods to stratify patients. Somewhat paradoxically, the neoplastic cells in DCIS are genetically comparable to those in invasive disease, suggesting the tumour microenvironment is the driving force for progression. Clinical and mechanistic studies highlight the complex DCIS microenvironment, with multiple cell types competing to regulate progression. Here, we examine recent studies detailing distinct aspects of the DCIS microenvironment and discuss how these may inform more effective care.

10 years of extracellular matrix proteomics: Accomplishments, challenges, and future perspectives

The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics, have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely post-translationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry-based proteomic approaches to define the ECM composition, or "matrisome", of tissues. This review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Last, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. MS-based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics.

COL12A1 Acts as a Novel Prognosis Biomarker and Activates Cancer-Associated Fibroblasts in Pancreatic Cancer through Bioinformatics and Experimental Validation

Pancreatic cancer remains one of the most challenging malignancies to date and is associated with poor survival. Cancer-associated fibroblasts (CAFs) are key stromal cells in the tumor microenvironment (TME) that play a crucial role in tumor progression in pancreatic cancer. Thus, uncovering the key genes involved in CAF progression and determining their prognostic value is critically important. Herein, we report our discoveries in this research area. Analysis of The Cancer Genome Atlas (TCGA) dataset and investigation of our clinical tissue samples indicated that COL12A1 expression was aberrantly highly expressed in pancreatic cancer. Survival and COX regression analyses revealed the significant clinical prognostic value of COL12A1 expression in pancreatic cancer. COL12A1 was mainly expressed in CAFs but not in tumor cells. This was verified with our PCR analysis in cancer cells and CAFs. The knocking down of COL12A1 decreased the proliferation and migration of CAFs and down-regulated the expression of CAF activation markers actin alpha 2 (ACTA2), fibroblast activation protein (FAP), and fibroblast-specific protein 1 (FSP1). Meanwhile, the interleukin 6 (IL6), CXC chemokine Ligand-5 (CXCL5), and CXC chemokine Ligand-10 (CXCL10) expressions were inhibited, and the cancer-promoting effect was reversed by COL12A1 knockdown. Therefore, we demonstrated the potential prognostic and target therapy value of COL12A1 expression in pancreatic cancer and elucidated the molecular mechanism underlying its role in CAFs. The findings of this study might provide new opportunities for TME-targeted therapies in pancreatic cancer.

Unusual Suspects: Bone and Cartilage ECM Proteins as Carcinoma Facilitators

The extracellular matrix (ECM) is the complex three-dimensional network of fibrous proteins and proteoglycans that constitutes an essential part of every tissue to provide support for normal tissue homeostasis. Tissue specificity of the ECM in its topology and structure supports unique biochemical and mechanical properties of each organ. Cancers, like normal tissues, require the ECM to maintain multiple processes governing tumor development, progression and spread. A large body of experimental and clinical evidence has now accumulated to demonstrate essential roles of numerous ECM components in all cancer types. Latest findings also suggest that multiple tumor types express, and use to their advantage, atypical ECM components that are not found in the cancer tissue of origin. However, the understanding of cancer-specific expression patterns of these ECM proteins and their exact roles in selected tumor types is still sketchy. In this review, we summarize the latest data on the aberrant expression of bone and cartilage ECM proteins in epithelial cancers and their specific functions in the pathogenesis of carcinomas and discuss future directions in exploring the utility of this selective group of ECM components as future drug targets.

New target DDR1: A "double-edged sword" in solid tumors

Globally, cancer is a major catastrophic disease that seriously threatens human health. Thus, there is an urgent need to find new strategies to treat cancer. Among them, identifying new targets is one of the best ways to treat cancer at present. Especially in recent years, scientists have discovered many new targets and made breakthroughs in the treatment of cancer, bringing new hope to cancer patients. As one of the novel targets for cancer treatment, DDR1 has attracted much attention due to its unique role in cancer. Hence, here, we focus on a new target, DDR1, which may be a "double-edged sword" of human solid tumors. In this review, we provide a comprehensive overview of how DDR1 acts as a "double-edged sword" in cancer. First, we briefly introduce the structure and normal physiological function of DDR1; Second, we delineate the DDR1 expression pattern in single cells; Next, we sorte out the relationship between DDR1 and cancer, including the abnormal expression of DDR1 in cancer, the mechanism of DDR1 and cancer occurrence, and the value of DDR1 on cancer prognosis. In addition, we introduced the current status of global drug and antibody research and development targeting DDR1 and its future design prospects; Finally, we summarize and look forward to designing more DDR1-targeting drugs in the future to make further progress in the treatment of solid tumors.

Novel genetically engineered H3.3G34R model reveals cooperation with ATRX loss in upregulation of Hoxa cluster genes and promotion of neuronal lineage

Background

Pediatric high-grade gliomas (pHGGs) are aggressive pediatric CNS tumors and an important subset are characterized by mutations in H3F3A, the gene that encodes Histone H3.3 (H3.3). Substitution of Glycine at position 34 of H3.3 with either Arginine or Valine (H3.3G34R/V), was recently described and characterized in a large cohort of pHGG samples as occurring in 5-20% of pHGGs. Attempts to study the mechanism of H3.3G34R have proven difficult due to the lack of knowledge regarding the cell-of-origin and the requirement for co-occurring mutations for model development. We sought to develop a biologically relevant animal model of pHGG to probe the downstream effects of the H3.3G34R mutation in the context of vital co-occurring mutations.

Methods

We developed a genetically engineered mouse model (GEMM) that incorporates PDGF-A activation, TP53 loss and the H3.3G34R mutation both in the presence and loss of Alpha thalassemia/mental retardation syndrome X-linked (ATRX), which is commonly mutated in H3.3G34 mutant pHGGs.

Results

We demonstrated that ATRX loss significantly increases tumor latency in the absence of H3.3G34R and inhibits ependymal differentiation in the presence of H3.3G34R. Transcriptomic analysis revealed that ATRX loss in the context of H3.3G34R upregulates Hoxa cluster genes. We also found that the H3.3G34R overexpression leads to enrichment of neuronal markers but only in the context of ATRX loss.

Conclusions

This study proposes a mechanism in which ATRX loss is the major contributor to many key transcriptomic changes in H3.3G34R pHGGs.

Accession number

GSE197988.

Type XXII Collagen Complements Fibrillar Collagens in the Serological Assessment of Tumor Fibrosis and the Outcome in Pancreatic Cancer

Circulating fragments of type III collagen, measured by PRO-C3, has shown promising results as a tumor fibrosis biomarker. However, the fibrotic tumor microenvironment consists of many other collagens with diverse functions and unexplored biomarker potential. One example hereof is type XXII collagen (COL22). In this study, we investigated the biomarker potential of COL22 by measuring this in serum. An ELISA, named PRO-C22, was developed and measured in two serum cohorts consisting of patients with various solid tumors (n = 220) and healthy subjects (n = 33) (Cohort 1), and patients with pancreatic ductal adenocarcinoma (PDAC) (n = 34), and healthy subjects (n = 20) (Cohort 2). In Cohort 1, PRO-C22 was elevated in the serum from patients with solid tumors, compared to healthy subjects (p < 0.01 to p < 0.0001), and the diagnostic accuracy (AUROC) ranged from 0.87 to 0.98, p < 0.0001. In Cohort 2, the high levels of PRO-C22, in patients with PDAC, were predictive of a worse overall survival (HR = 4.52, 95% CI 1.90−10.7, p = 0.0006) and this remained significant after adjusting for PRO-C3 (HR = 4.27, 95% CI 1.24−10.4, p = 0.0013). In conclusion, PRO-C22 has diagnostic biomarker potential in various solid tumor types and prognostic biomarker potential in PDAC. Furthermore, PRO-C22 complemented PRO-C3 in predicting mortality, suggesting an additive prognostic value when quantifying different collagens.