Spatial Proximity to Fibroblasts Impacts Molecular Features and Therapeutic Sensitivity of Breast Cancer Cells Influencing Clinical Outcomes

3D tumor cultures for drug resistance and screening development in clinical applications

Tumor drug resistance presents a growing challenge in medical practice, particularly during anti-cancer therapies, where the emergence of drug-resistant cancer cells significantly complicates clinical treatment. In recent years, three-dimensional (3D) tumor culture technology, which more effectively simulates the in vivo physiological environment, has gained increasing attention in tumor drug resistance research and clinical applications. By mimicking the in vivo cellular microenvironment, 3D tumor culture technology not only recapitulates cell-cell interactions but also more faithfully reproduces the biological effects of therapeutic agents. Consequently, 3D tumor culture technology is emerging as a crucial tool in biomedical and clinical research. We summarize the benefits of 3D culture models and organoid technology, explore their application in the realm of drug resistance, drug screening, and personalized therapy, and discuss their potential application prospects and challenges in clinical transformation, with the aim of providing insights for optimizing cancer treatment strategies and advancing precision therapy.

Unveiling the link between chronic inflammation and cancer

The highly nuanced transition from an inflammatory process to tumorigenesis is of great scientific interest. While it is well known that environmental stimuli can cause inflammation, less is known about the oncogenic modifications that chronic inflammation in the tissue microenvironment can bring about, as well as how these modifications can set off pro-tumorigenic processes. It is clear that no matter where the environmental factors come from, maintaining an inflammatory microenvironment encourages carcinogenesis. In addition to encouraging angiogenesis and metastatic processes, sustaining the survival and proliferation of malignant transformed cells, and possibly altering the efficacy of therapeutic agents, inflammation can negatively regulate the antitumoral adaptive and innate immune responses. Because chronic inflammation has multiple pathways involved in tumorigenesis and metastasis, it has gained recognition as a marker of cancer and a desirable target for cancer therapy. Recent advances in our knowledge of the molecular mechanisms that drive cancer's progression demonstrate that inflammation promotes tumorigenesis and metastasis while suppressing anti-tumor immunity. In many solid tumor types, including breast, lung, and liver cancer, inflammation stimulates the activation of oncogenes and impairs the body's defenses against the tumor. Additionally, it alters the microenvironment of the tumor. As a tactical approach to cancer treatment, these findings have underscored the importance of targeting inflammatory pathways. This review highlights the role of inflammation in cancer development and metastasis, focusing on its impact on tumor progression, immune suppression, and therapy resistance. It examines current anti-inflammatory strategies, including NSAIDs, cytokine modulators, and STAT3 inhibitors, while addressing their potential and limitations. The review emphasizes the need for further research to unravel the complex mechanisms linking inflammation to cancer progression and identify molecular targets for specific cancer subtypes.

An Optimized Protocol for Simultaneous Propagation of Patient-derived Organoids and Matching CAFs

Recurrent hormone receptor-positive (HR+) breast cancer is a leading cause of cancer mortality in women. Recurrence and resistance to targeted therapies have been difficult to study due to the long clinical course of the disease, the complex nature of resistance, and the lack of clinically relevant model systems. Existing models are limited to a few HR+ cell lines, organoid models, and patient-derived xenograft models, all lacking components of the human tumor microenvironment. Furthermore, the low take rate and loss of estrogen receptor (ER) expression in patient-derived organoids (PDOs) has been challenging. Our protocol allows simultaneous isolation of PDOs and matching cancer-associated fibroblasts (CAFs) from primary and metastatic HR+ breast cancers. Importantly, our protocol has a higher take rate and enables long-term culturing of PDOs that retain ER expression. Our matching PDOs and CAFs will provide researchers with a new resource to study the influence of the tumor microenvironment on various aspects of cancer biology such as cell growth and drug resistance in HR+ breast cancer. Key features • Propagation of patient-derived organoids and matching cancer-associated fibroblasts from primary and metastatic hormone receptor (HR+) positive breast cancer. • Optimized media for long-term culturing of HR+ organoids from primary tumors and bone metastasis. • Co-culture model to assess the influence of the tumor stroma on breast cancer progression.

A spheroid whole mount drug testing pipeline with machine-learning based image analysis identifies cell-type specific differences in drug efficacy on a single-cell level

BACKGROUND

The growth and drug response of tumors are influenced by their stromal composition, both in vivo and 3D-cell culture models. Cell-type inherent features as well as mutual relationships between the different cell types in a tumor might affect drug susceptibility of the tumor as a whole and/or of its cell populations. However, a lack of single-cell procedures with sufficient detail has hampered the automated observation of cell-type-specific effects in three-dimensional stroma-tumor cell co-cultures.

METHODS

Here, we developed a high-content pipeline ranging from the setup of novel tumor-fibroblast spheroid co-cultures over optical tissue clearing, whole mount staining, and 3D confocal microscopy to optimized 3D-image segmentation and a 3D-deep-learning model to automate the analysis of a range of cell-type-specific processes, such as cell proliferation, apoptosis, necrosis, drug susceptibility, nuclear morphology, and cell density.

RESULTS

This demonstrated that co-cultures of KP-4 tumor cells with CCD-1137Sk fibroblasts exhibited a growth advantage compared to tumor cell mono-cultures, resulting in higher cell counts following cytostatic treatments with paclitaxel and doxorubicin. However, cell-type-specific single-cell analysis revealed that this apparent benefit of co-cultures was due to a higher resilience of fibroblasts against the drugs and did not indicate a higher drug resistance of the KP-4 cancer cells during co-culture. Conversely, cancer cells were partially even more susceptible in the presence of fibroblasts than in mono-cultures.

CONCLUSION

In summary, this underlines that a novel cell-type-specific single-cell analysis method can reveal critical insights regarding the mechanism of action of drug substances in three-dimensional cell culture models.

Assessing Novel Antibody-Based Therapies in Reconstructive 3D Cell Models of the Tumor Microenvironment

Targeted, combinatorial, and immunomodulatory therapies, such as antibody-drug conjugates (ADCs) and immunomodulatory antibodies (Abs), are powerful weapons against tumor cells and immune cells within the tumor microenvironment (TME). Therefore, the evaluation of such therapies should be conducted in pre-clinical models able to recapitulate the complex cellular and molecular crosstalk of the TME. To build-in critical hallmarks of the TME, a breast cancer heterotypic 3D cell model (3D-3) is devised using a microencapsulation strategy with an inert biomaterial (alginate) and agitation-based cultures. Both stromal and immune components are added to multicellular tumor spheroids, therefore fostering cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs) immunomodulatory interactions. The potential of the methodology to assess Ab-based therapies is then addressed by employing a series of anti-HER2-based ADCs. ADCs induced tumor-cell specific cytotoxicity toward HER2+ breast cancer spheroids while sparing HER2-negative CAFs. In addition, an immunomodulatory blocking Ab against colony-stimulating factor 1 receptor (CSF1R) decreases the expression of immunosuppressive and anti-inflammatory markers in TAMs, like what is previously observed upon in vivo α-CSF1R administration. Collectively, the human TME-based 3D-3 cell model is a suitable tool to evaluate the anti-tumor and immunomodulatory potential of novel antibody-based therapies directed against TME targets, such as cancer cells and macrophages.

STAT3: Key targets of growth-promoting receptor positive breast cancer

Breast cancer has become the malignant tumor with the first incidence and the second mortality among female cancers. Most female breast cancers belong to luminal-type breast cancer and HER2-positive breast cancer. These breast cancer cells all have different driving genes, which constantly promote the proliferation and metastasis of breast cancer cells. Signal transducer and activator of transcription 3 (STAT3) is an important breast cancer-related gene, which can promote the progress of breast cancer. It has been proved in clinical and basic research that over-expressed and constitutively activated STAT3 is involved in the progress, proliferation, metastasis and chemotherapy resistance of breast cancer. STAT3 is an important key target in luminal-type breast cancer and HER2-positive cancer, which has an important impact on the curative effect of related treatments. In breast cancer, the activation of STAT3 will change the spatial position of STAT3 protein and cause different phenotypic changes of breast cancer cells. In the current basic research and clinical research, small molecule inhibitors activated by targeting STAT3 can effectively treat breast cancer, and enhance the efficacy level of related treatment methods for luminal-type and HER2-positive breast cancers.

Rational Design of HER2-Targeted Combination Therapies to Reverse Drug Resistance in Fibroblast-Protected HER2+ Breast Cancer Cells

Introduction

Fibroblasts, an abundant cell type in the breast tumor microenvironment, interact with cancer cells and orchestrate tumor progression and drug resistance. However, the mechanisms by which fibroblast-derived factors impact drug sensitivity remain poorly understood. Here, we develop rational combination therapies that are informed by proteomic profiling to overcome fibroblast-mediated therapeutic resistance in HER2+ breast cancer cells.

Methods

Drug sensitivity to the HER2 kinase inhibitor lapatinib was characterized under conditions of monoculture and exposure to breast fibroblast-conditioned medium. Protein expression was measured using reverse phase protein arrays. Candidate targets for combination therapy were identified using differential expression and multivariate regression modeling. Follow-up experiments were performed to evaluate the effects of HER2 kinase combination therapies in fibroblast-protected cancer cell lines and fibroblasts.

Results

Compared to monoculture, fibroblast-conditioned medium increased the expression of plasminogen activator inhibitor-1 (PAI1) and cell cycle regulator polo like kinase 1 (PLK1) in lapatinib-treated breast cancer cells. Combination therapy of lapatinib with inhibitors targeting either PAI1 or PLK1, eliminated fibroblast-protected cancer cells, under both conditions of direct coculture with fibroblasts and protection by fibroblast-conditioned medium. Analysis of publicly available, clinical transcriptomic datasets revealed that HER2-targeted therapy fails to suppress PLK1 expression in stroma-rich HER2+ breast tumors and that high PAI1 gene expression associates with high stroma density. Furthermore, we showed that an epigenetics-directed approach using a bromodomain and extraterminal inhibitor to globally target fibroblast-induced proteomic adaptions in cancer cells, also restored lapatinib sensitivity.

Conclusions

Our data-driven framework of proteomic profiling in breast cancer cells identified the proteolytic degradation regulator PAI1 and the cell cycle regulator PLK1 as predictors of fibroblast-mediated treatment resistance. Combination therapies targeting HER2 kinase and these fibroblast-induced signaling adaptations eliminates fibroblast-protected HER2+ breast cancer cells.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-024-00823-0.

Tumor Cell Communications as Promising Supramolecular Targets for Cancer Chemotherapy: A Possible Strategy

Fifty-two years have passed since President Nixon launched the "War on Cancer". Despite unparalleled efforts and funds allocated worldwide, the outlined goals were not achieved because cancer treatment approaches such as chemotherapy, radiation therapy, hormonal and targeted therapies have not fully met the expectations. Based on the recent literature, a new direction in cancer therapy can be proposed which targets connections between cancer cells and their microenvironment by chemical means. Cancer-stromal synapses such as immunological synapses between cancer and immune cells provide an attractive target for this approach. Such synapses form ligand-receptor clusters on the interface of the interacting cells. They share a common property of involving intercellular clusters of spatially proximate and cooperatively acting proteins. Synapses provide the space for the focused intercellular signaling molecules exchange. Thus, the disassembly of cancer-stromal synapses may potentially cause the collapse of various tumors. Additionally, the clustered arrangement of synapse components offers opportunities to enhance treatment safety and precision by using targeted crosslinking chemical agents which may inactivate cancer synapses even in reduced concentrations. Furthermore, attaching a cleavable cell-permeable toxic agent(s) to a crosslinker may further enhance the anti-cancer effect of such therapeutics. The highlighted approach promises to be universal, relatively simple and cost-efficient. We also hope that, unlike chemotherapeutic and immune drugs that interact with a single target, by using supramolecular large clusters that include many different components as a target, the emergence of a resistance characteristic of chemo- and immunotherapy is extremely unlikely.

Dissecting the Spatially Restricted Effects of Microenvironment-Mediated Resistance on Targeted Therapy Responses

The response of tumors to anti-cancer therapies is defined not only by cell-intrinsic therapy sensitivities but also by local interactions with the tumor microenvironment. Fibroblasts that make tumor stroma have been shown to produce paracrine factors that can strongly reduce the sensitivity of tumor cells to many types of targeted therapies. Moreover, a high stroma/tumor ratio is generally associated with poor survival and reduced therapy responses. However, in contrast to advanced knowledge of the molecular mechanisms responsible for stroma-mediated resistance, its effect on the ability of tumors to escape therapeutic eradication remains poorly understood. To a large extent, this gap of knowledge reflects the challenge of accounting for the spatial aspects of microenvironmental resistance, especially over longer time frames. To address this problem, we integrated spatial inferences of proliferation-death dynamics from an experimental animal model of targeted therapy responses with spatial mathematical modeling. With this approach, we dissected the impact of tumor/stroma distribution, magnitude and distance of stromal effects. While all of the tested parameters affected the ability of tumor cells to resist elimination, spatial patterns of stroma distribution within tumor tissue had a particularly strong impact.

Rational design of HER2-targeted combination therapies to reverse drug resistance in fibroblast-protected HER2+ breast cancer cells

Introduction

Fibroblasts, an abundant cell type in the breast tumor microenvironment, interact with cancer cells and orchestrate tumor progression and drug resistance. However, the mechanisms by which fibroblast-derived factors impact drug sensitivity remain poorly understood. Here, we develop rational combination therapies that are informed by proteomic profiling to overcome fibroblast-mediated therapeutic resistance in HER2+ breast cancer cells.

Methods

Drug sensitivity to the HER2 kinase inhibitor lapatinib was characterized under conditions of monoculture and exposure to breast fibroblast-conditioned medium. Protein expression was measured using reverse phase protein arrays. Candidate targets for combination therapy were identified using differential expression and multivariate regression modeling. Follow-up experiments were performed to evaluate the effects of HER2 kinase combination therapies in fibroblast-protected cancer cell lines and fibroblasts.

Results

Compared to monoculture, fibroblast-conditioned medium increased the expression of plasminogen activator inhibitor-1 (PAI1) and cell cycle regulator polo like kinase 1 (PLK1) in lapatinib-treated breast cancer cells. Combination therapy of lapatinib with inhibitors targeting either PAI1 or PLK1, eliminated fibroblast-protected cancer cells, under both conditions of direct coculture with fibroblasts and protection by fibroblast-conditioned medium. Analysis of publicly available, clinical transcriptomic datasets revealed that HER2-targeted therapy fails to suppress PLK1 expression in stroma-rich HER2+ breast tumors and that high PAI1 gene expression associates with high stroma density. Furthermore, we showed that an epigenetics-directed approach using a bromodomain and extraterminal inhibitor to globally target fibroblast-induced proteomic adaptions in cancer cells, also restored lapatinib sensitivity.

Conclusions

Our data-driven framework of proteomic profiling in breast cancer cells identified the proteolytic degradation regulator PAI1 and the cell cycle regulator PLK1 as predictors of fibroblast-mediated treatment resistance. Combination therapies targeting HER2 kinase and these fibroblast-induced signaling adaptations eliminates fibroblast-protected HER2+ breast cancer cells.

Cancer-stromal cell interactions in breast cancer brain metastases induce glycocalyx-mediated resistance to HER2-targeting therapies

Brain metastatic breast cancer is particularly lethal largely due to therapeutic resistance. Almost half of the patients with metastatic HER2-positive breast cancer develop brain metastases, representing a major clinical challenge. We previously described that cancer-associated fibroblasts are an important source of resistance in primary tumors. Here, we report that breast cancer brain metastasis stromal cell interactions in 3D cocultures induce therapeutic resistance to HER2-targeting agents, particularly to the small molecule inhibitor of HER2/EGFR neratinib. We investigated the underlying mechanisms using a synthetic Notch reporter system enabling the sorting of cancer cells that directly interact with stromal cells. We identified mucins and bulky glycoprotein synthesis as top-up-regulated genes and pathways by comparing the gene expression and chromatin profiles of stroma-contact and no-contact cancer cells before and after neratinib treatment. Glycoprotein gene signatures were also enriched in human brain metastases compared to primary tumors. We confirmed increased glycocalyx surrounding cocultures by immunofluorescence and showed that mucinase treatment increased sensitivity to neratinib by enabling a more efficient inhibition of EGFR/HER2 signaling in cancer cells. Overexpression of truncated MUC1 lacking the intracellular domain as a model of increased glycocalyx-induced resistance to neratinib both in cell culture and in experimental brain metastases in immunodeficient mice. Our results highlight the importance of glycoproteins as a resistance mechanism to HER2-targeting therapies in breast cancer brain metastases.

Peristromal niches protect lung cancers from targeted therapies through a combined effect of multiple molecular mediators

Targeted therapies directed against oncogenic signaling addictions, such as inhibitors of ALK in ALK+ NSCLC often induce strong and durable clinical responses. However, they are not curative in metastatic cancers, as some tumor cells persist through therapy, eventually developing resistance. Therapy sensitivity can reflect not only cell-intrinsic mechanisms but also inputs from stromal microenvironment. Yet, the contribution of tumor stroma to therapeutic responses in vivo remains poorly defined. To address this gap of knowledge, we assessed the contribution of stroma-mediated resistance to therapeutic responses to the frontline ALK inhibitor alectinib in xenograft models of ALK+ NSCLC. We found that stroma-proximal tumor cells are partially protected against cytostatic effects of alectinib. This effect is observed not only in remission, but also during relapse, indicating the strong contribution of stroma-mediated resistance to both persistence and resistance. This therapy-protective effect of the stromal niche reflects a combined action of multiple mechanisms, including growth factors and extracellular matrix components. Consequently, despite improving alectinib responses, suppression of any individual resistance mechanism was insufficient to fully overcome the protective effect of stroma. Focusing on shared collateral sensitivity of persisters offered a superior therapeutic benefit, especially when using an antibody-drug conjugate with bystander effect to limit therapeutic escape. These findings indicate that stroma-mediated resistance might be the major contributor to both residual and progressing disease and highlight the limitation of focusing on suppressing a single resistance mechanism at a time.

The cellular composition of the tumor microenvironment is an important marker for predicting therapeutic efficacy in breast cancer

At present, the incidence rate of breast cancer ranks first among new-onset malignant tumors in women. The tumor microenvironment is a hot topic in tumor research. There are abundant cells in the tumor microenvironment that play a protumor or antitumor role in breast cancer. During the treatment of breast cancer, different cells have different influences on the therapeutic response. And after treatment, the cellular composition in the tumor microenvironment will change too. In this review, we summarize the interactions between different cell compositions (such as immune cells, fibroblasts, endothelial cells, and adipocytes) in the tumor microenvironment and the treatment mechanism of breast cancer. We believe that detecting the cellular composition of the tumor microenvironment is able to predict the therapeutic efficacy of treatments for breast cancer and benefit to combination administration of breast cancer.

Brain metastasis-associated fibroblasts secrete fucosylated PVR/CD155 that induces breast cancer invasion

Brain metastasis cancer-associated fibroblasts (bmCAFs) are emerging as crucial players in the development of breast cancer brain metastasis (BCBM), but our understanding of the underlying molecular mechanisms is limited. In this study, we aim to elucidate the pathological contributions of fucosylation (the post-translational modification of proteins by the dietary sugar L-fucose) to tumor-stromal interactions that drive the development of BCBM. Here, we report that patient-derived bmCAFs secrete high levels of polio virus receptor (PVR), which enhance the invasive capacity of BC cells. Mechanistically, we find that HIF1α transcriptionally upregulates fucosyltransferase 11, which fucosylates PVR, triggering its secretion from bmCAFs. Global phosphoproteomic analysis of BC cells followed by functional verification identifies cell-cell junction and actin cytoskeletal signaling as modulated by bmCAF-secreted, -fucosylated PVR. Our findings delineate a hypoxia- and fucosylation-regulated mechanism by which bmCAFs contribute to the invasiveness of BCBM in the brain.

Spatial simulation of autologous cell defection for cancer treatment

Cancer cells are highly cooperative in a nepotistic way and evolutionarily dynamic. Present cancer treatments often overlook these aspects, inducing the selection of resistant cancer cells and the corresponding relapse. As an alternative method of cancer elimination, autologous cell defection (ACD) was suggested by which modified cancer cells parasitically reliant on other cancer cells are implemented to the cancer cluster. Specifically, modified cancer cells should not produce costly growth factors that promote the growth of other cancer cells while receiving the benefit of exposure to such growth factors. Analytical models and rudimentary experiments up to date provide the medical feasibility of this method. In this study, I built comprehensive spatial simulation models by embracing the effects of the multiple growth factors, the Warburg effect, mutations and immunity. The simulation results based on planar spatial structures indicate that implementation of the defective modified tumours may replace the existing cancer cluster and defective cells would later collapse by themselves. Furthermore, I built a mathematical model that compares the fitness of the cells adjacent to the hypertumour-cancer interface. I also calculated whether anticancer drugs that reduce the effects of the growth factors promote or demote the utility of ACD under diverse fitness functions. The computational examination implies that anticancer drugs may impede the therapeutic effect of ACD when there is a strong concavity in the fitness function. The analysis results could work as a general guidance for effective ACD that may expand the paradigm of cancer treatment.

Stroma-Mediated Breast Cancer Cell Proliferation Indirectly Drives Chemoresistance by Accelerating Tumor Recovery between Chemotherapy Cycles

The ability of tumors to survive therapy reflects both cell-intrinsic and microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity induced by stroma-produced paracrine factors. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies. In vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. At the same time, consistent with prior studies, fibroblast-produced secreted factors stimulated treatment-independent enhancement of tumor cell proliferation. Spatial analyses indicated that proximity to stroma is often associated with enhanced tumor cell proliferation in vivo. These observations suggested an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To evaluate this hypothesis, a spatial agent-based model of stroma impact on proliferation/death dynamics was developed that was quantitatively parameterized using inferences from histologic analyses and experimental studies. The model demonstrated that the observed enhancement of tumor cell proliferation within stroma-proximal niches could enable tumors to avoid elimination over multiple chemotherapy cycles. Therefore, this study supports the existence of an indirect mechanism of environment-mediated chemoresistance that might contribute to the negative correlation between stromal content and poor therapy outcomes.

SIGNIFICANCE

Integration of experimental research with mathematical modeling reveals an indirect microenvironmental chemoresistance mechanism by which stromal cells stimulate breast cancer cell proliferation and highlights the importance of consideration of proliferation/death dynamics. See related commentary by Wall and Echeverria, p. 3667.

Avoiding Extinction: Cancer-Associated Fibroblasts Help Triple-Negative Breast Cancer Outrun Chemotherapy

Neoadjuvant chemotherapy is a staple of triple-negative breast cancer (TNBC) treatment. Predicated on the principle of fractional cell killing, chemotherapy regimens are typically cycles of short drug exposure followed by a period of recovery from the toxic side effects. However, many patients experience chemotherapy resistance for a variety of reasons, resulting in tumors that are not sufficiently reduced with treatment. Response to chemotherapy prior to surgical resection is a strong predictor of patient prognosis; therefore, finding ways to improve efficacy is a critical need. Tremendous effort has gone into understanding the relationship between the tumor microenvironment and treatment sensitivity in many tumor types. In this issue of Cancer Research, Miroshnychenko and colleagues investigate how the well-characterized phenomenon of cancer-associated fibroblast (CAF)-induced proliferation of tumor cells allows TNBC to evade extinction after multiple cycles of cytotoxic chemotherapies. Their findings imply CAF-promoted tumor cell proliferation allows tumor cells to push through stressful conditions caused by treatment and to avoid tumor elimination. This mechanism of 'indirect' chemoresistance contrasts with the dogma that tumor cell proliferation enhances chemosensitivity. This study opens the door for the discovery of mechanisms and therapeutic targets to limit the ability of CAFs to rescue tumor cells from the brink of extinction. See related article by Miroshnychenko et al., p. 3681.

Friend or foe? The elusive role of hepatic stellate cells in liver cancer

Liver fibrosis is a substantial risk factor for the development and progression of liver cancer, which includes hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Studies utilizing cell fate mapping and single-cell transcriptomics techniques have identified quiescent perisinusoidal hepatic stellate cells (HSCs) as the primary source of activated collagen-producing HSCs and liver cancer-associated fibroblasts (CAFs) in HCC and liver metastasis, complemented in iCCA by contributions from portal fibroblasts. At the same time, integrative computational analysis of single-cell, single-nucleus and spatial RNA sequencing data have revealed marked heterogeneity among HSCs and CAFs, with distinct subpopulations displaying unique gene expression signatures and functions. Some of these subpopulations have divergent roles in promoting or inhibiting liver fibrogenesis and carcinogenesis. In this Review, we discuss the dual roles of HSC subpopulations in liver fibrogenesis and their contribution to liver cancer promotion, progression and metastasis. We review the transcriptomic and functional similarities between HSC and CAF subpopulations, highlighting the pathways that either promote or prevent fibrosis and cancer, and the immunological landscape from which these pathways emerge. Insights from ongoing studies will yield novel strategies for developing biomarkers, assessing prognosis and generating new therapies for both HCC and iCCA prevention and treatment.

Interaction of phenotypic sublines isolated from triple-negative breast cancer cell line MDA-MB-231 modulates their sensitivity to paclitaxel and doxorubicin in 2D and 3D assays

Breast cancer is a rapidly evolving, multifactorial disease that accumulates numerous genetic and epigenetic alterations. These result in molecular and phenotypic heterogeneity within the tumor, the complexity of which is further amplified through specific interactions between cancer cells. We aimed to analyze cell phenotypic sublines and the influence of their interaction on drug resistance, spheroid formation, and migration. Seven sublines were derived from the MDA-MB-231 breast cancer cell line using a multiple-cell suspension dilution. The growth rate, CD133 receptor expression, migration ability, and chemosensitivity of these sublines to anticancer drugs doxorubicin (DOX) and paclitaxel (PTX) were determined. Three sublines (F5, D8, H2) have been chosen to study their interaction in 2D and 3D assays. In the 2D model, the resistance of all sublines composition to DOX decreased, but in the 3D model, the resistance of all sublines except H2, increased to both PTX and DOX. In the 3D model, the combined sublines F5 and D8 had higher resistance to DOX and statistically significantly lower resistance for PTX compared to the control. The interaction between cancer stem-like cells (F5) and increased migration cells (D8) increased resistance to PTX in cell monolayer and increased resistance against both DOX and PTX in the spheroids. The interaction of DOX-resistant (H2) cells with other cell subpopulations (D8, F5, HF) decreased the resistance to DOX in cell monolayer and both DOX and PTX in spheroids.

Simultaneous isolation of hormone receptor-positive breast cancer organoids and fibroblasts reveals stroma-mediated resistance mechanisms

Recurrent hormone receptor-positive (HR+) breast cancer kills more than 600,000 women annually. Although HR+ breast cancers typically respond well to therapies, approximately 30% of patients relapse. At this stage, the tumors are usually metastatic and incurable. Resistance to therapy, particularly endocrine therapy is typically thought to be tumor intrinsic (e.g., estrogen receptor mutations). However, tumor-extrinsic factors also contribute to resistance. For example, stromal cells, such as cancer-associated fibroblasts (CAFs), residing in the tumor microenvironment, are known to stimulate resistance and disease recurrence. Recurrence in HR+ disease has been difficult to study due to the prolonged clinical course, complex nature of resistance, and lack of appropriate model systems. Existing HR+ models are limited to HR+ cell lines, a few HR+ organoid models, and xenograft models that all lack components of the human stroma. Therefore, there is an urgent need for more clinically relevant models to study the complex nature of recurrent HR+ breast cancer, and the factors contributing to treatment relapse. Here, we present an optimized protocol that allows a high take-rate, and simultaneous propagation of patient-derived organoids (PDOs) and matching CAFs, from primary and metastatic HR+ breast cancers. Our protocol allows for long-term culturing of HR+ PDOs that retain estrogen receptor expression and show responsiveness to hormone therapy. We further show the functional utility of this system by identifying CAF-secreted cytokines, such as growth-regulated oncogene α , as stroma-derived resistance drivers to endocrine therapy in HR+ PDOs.

Periostin+ Stromal Cells Guide Lymphovascular Invasion by Cancer Cells

Cancer cell dissemination to sentinel lymph nodes is associated with poor patient outcomes, particularly in breast cancer. The process by which cancer cells egress from the primary tumor upon interfacing with the lymphatic vasculature is complex and driven by dynamic interactions between cancer cells and stromal cells, including cancer-associated fibroblasts (CAF). The matricellular protein periostin can distinguish CAF subtypes in breast cancer and is associated with increased desmoplasia and disease recurrence in patients. However, as periostin is secreted, periostin-expressing CAFs are difficult to characterize in situ, limiting our understanding of their specific contribution to cancer progression. Here, we used in vivo genetic labeling and ablation to lineage trace periostin+ cells and characterize their functions during tumor growth and metastasis. Periostin-expressing CAFs were spatially found at periductal and perivascular margins, were enriched at lymphatic vessel peripheries, and were differentially activated by highly metastatic cancer cells versus poorly metastatic counterparts. Surprisingly, genetically depleting periostin+ CAFs slightly accelerated primary tumor growth but impaired intratumoral collagen organization and inhibited lymphatic, but not lung, metastases. Periostin ablation in CAFs impaired their ability to deposit aligned collagen matrices and inhibited cancer cell invasion through collagen and across lymphatic endothelial cell monolayers. Thus, highly metastatic cancer cells mobilize periostin-expressing CAFs in the primary tumor site that promote collagen remodeling and collective cell invasion within lymphatic vessels and ultimately to sentinel lymph nodes.

SIGNIFICANCE

Highly metastatic breast cancer cells activate a population of periostin-expressing CAFs that remodel the extracellular matrix to promote escape of cancer cells into lymphatic vessels and drive colonization of proximal lymph nodes.

Convergent Approaches to Delineate the Metabolic Regulation of Tumor Invasion by Hyaluronic Acid Biosynthesis

Metastasis is the leading cause of breast cancer-related deaths and is often driven by invasion and cancer-stem like cells (CSCs). Both the CSC phenotype and invasion are associated with increased hyaluronic acid (HA) production. How these independent observations are connected, and which role metabolism plays in this process, remains unclear due to the lack of convergent approaches integrating engineered model systems, computational tools, and cancer biology. Using microfluidic invasion models, metabolomics, computational flux balance analysis, and bioinformatic analysis of patient data, the functional links between the stem-like, invasive, and metabolic phenotype of breast cancer cells as a function of HA biosynthesis are investigated. These results suggest that CSCs are more invasive than non-CSCs and that broad metabolic changes caused by overproduction of HA play a role in this process. Accordingly, overexpression of hyaluronic acid synthases (HAS) 2 or 3 induces a metabolic phenotype that promotes cancer cell stemness and invasion in vitro and upregulates a transcriptomic signature predictive of increased invasion and worse patient survival. This study suggests that HA overproduction leads to metabolic adaptations to satisfy the energy demands for 3D invasion of breast CSCs highlighting the importance of engineered model systems and multidisciplinary approaches in cancer research.

Effective dose window for containing tumor burden under tolerable level

A maximum-tolerated dose (MTD) reduces the drug-sensitive cell population, though it may result in the competitive release of drug resistance. Alternative treatment strategies such as adaptive therapy (AT) or dose modulation aim to impose competitive stress on drug-resistant cell populations by maintaining a sufficient number of drug-sensitive cells. However, given the heterogeneous treatment response and tolerable tumor burden level of individual patients, determining an effective dose that can fine-tune competitive stress remains challenging. This study presents a mathematical model-driven approach that determines the plausible existence of an effective dose window (EDW) as a range of doses that conserve sufficient sensitive cells while maintaining the tumor volume below a threshold tolerable tumor volume (TTV). We use a mathematical model that explains intratumor cell competition. Analyzing the model, we derive an EDW determined by TTV and the competitive strength. By applying a fixed endpoint optimal control model, we determine the minimal dose to contain cancer at a TTV. As a proof of concept, we study the existence of EDW for a small cohort of melanoma patients by fitting the model to longitudinal tumor response data. We performed identifiability analysis, and for the patients with uniquely identifiable parameters, we deduced patient-specific EDW and minimal dose. The tumor volume for a patient could be theoretically contained at the TTV either using continuous dose or AT strategy with doses belonging to EDW. Further, we conclude that the lower bound of the EDW approximates the minimum effective dose (MED) for containing tumor volume at the TTV.

The role of tumor microenvironment in drug resistance: emerging technologies to unravel breast cancer heterogeneity

Breast cancer is a highly heterogeneous disease, at both inter- and intra-tumor levels, and this heterogeneity is a crucial determinant of malignant progression and response to treatments. In addition to genetic diversity and plasticity of cancer cells, the tumor microenvironment contributes to tumor heterogeneity shaping the physical and biological surroundings of the tumor. The activity of certain types of immune, endothelial or mesenchymal cells in the microenvironment can change the effectiveness of cancer therapies via a plethora of different mechanisms. Therefore, deciphering the interactions between the distinct cell types, their spatial organization and their specific contribution to tumor growth and drug sensitivity is still a major challenge. Dissecting intra-tumor heterogeneity is currently an urgent need to better define breast cancer biology and to develop therapeutic strategies targeting the microenvironment as helpful tools for combined and personalized treatment. In this review, we analyze the mechanisms by which the tumor microenvironment affects the characteristics of tumor heterogeneity that ultimately result in drug resistance, and we outline state of the art preclinical models and emerging technologies that will be instrumental in unraveling the impact of the tumor microenvironment on resistance to therapies.

Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity

Background: The impact of gene-sets on a spatial phenotype is not necessarily uniform across different locations of cancer tissue. This study introduces a computational platform, GWLCT, for combining gene set analysis with spatial data modeling to provide a new statistical test for location-specific association of phenotypes and molecular pathways in spatial single-cell RNA-seq data collected from an input tumor sample.

Methods: The main advantage of GWLCT consists of an analysis beyond global significance, allowing the association between the gene-set and the phenotype to vary across the tumor space. At each location, the most significant linear combination is found using a geographically weighted shrunken covariance matrix and kernel function. Whether a fixed or adaptive bandwidth is determined based on a cross-validation cross procedure. Our proposed method is compared to the global version of linear combination test (LCT), bulk and random-forest based gene-set enrichment analyses using data created by the Visium Spatial Gene Expression technique on an invasive breast cancer tissue sample, as well as 144 different simulation scenarios.

Results: In an illustrative example, the new geographically weighted linear combination test, GWLCT, identifies the cancer hallmark gene-sets that are significantly associated at each location with the five spatially continuous phenotypic contexts in the tumors defined by different well-known markers of cancer-associated fibroblasts. Scan statistics revealed clustering in the number of significant gene-sets. A spatial heatmap of combined significance over all selected gene-sets is also produced. Extensive simulation studies demonstrate that our proposed approach outperforms other methods in the considered scenarios, especially when the spatial association increases.

Conclusion: Our proposed approach considers the spatial covariance of gene expression to detect the most significant gene-sets affecting a continuous phenotype. It reveals spatially detailed information in tissue space and can thus play a key role in understanding the contextual heterogeneity of cancer cells.

Paracrine enhancement of tumor cell proliferation provides indirect stroma-mediated chemoresistance via acceleration of tumor recovery between chemotherapy cycles

The ability of tumors to survive therapy is mediated not only by cell-intrinsic but also cell-extrinsic, microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity by stroma-produced paracrine factors through activating pro-survival signaling and stemness. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies in TNBC. Our in vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. However, we found that fibroblasts often enhance baseline tumor cell proliferation. Consistent with this in vitro observation, we found evidence of stroma-enhanced TNBC cell proliferation in vivo , in xenograft models and patient samples. Based on these observations, we hypothesized an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To test this hypothesis, we developed a spatial agent-based model of tumor response to repeated dosing of chemotherapy. The model was quantitatively parameterized from histological analyses and experimental studies. We found that even a slight enhancement of tumor cell proliferation within stroma-proximal niches can strongly enhance the ability of tumors to survive multiple cycles of chemotherapy under biologically and clinically feasible parameters. In summary, our study uncovered a novel, indirect mechanism of chemoresistance. Further, our study highlights the limitations of short-term cytotoxicity assays in understanding chemotherapy responses and supports the integration of experimental and in silico modeling.

Inclusion of cancer-associated fibroblasts in drug screening assays to evaluate pancreatic cancer resistance to therapeutic drugs

Pancreatic ductal adenocarcinoma (PDAC) is characterised by a pro-inflammatory stroma and multi-faceted microenvironment that promotes and maintains tumorigenesis. However, the models used to test new and emerging therapies for PDAC have not increased in complexity to keep pace with our understanding of the human disease. Promising therapies that pass pre-clinical testing often fail in pancreatic cancer clinical trials. The objective of this study was to investigate whether changes in the drug-dosing regimen or the addition of cancer-associated fibroblasts (CAFs) to current existing models can impact the efficacy of chemotherapy drugs used in the clinic. Here, we reveal that gemcitabine and paclitaxel markedly reduce the viability of pancreatic cell lines, but not CAFs, when cultured in 2D. Following the use of an in vitro drug pulsing experiment, PDAC cell lines showed sensitivity to gemcitabine and paclitaxel. However, CAFs were less sensitive to pulsing with gemcitabine compared to their response to paclitaxel. We also identify that a 3D co-culture model of MIA PaCa-2 or PANC-1 with CAFs showed an increased chemoresistance to gemcitabine when compared to standard 2D mono-cultures a difference to paclitaxel which showed no measurable difference between the 2D and 3D models, suggesting a complex interaction between the drug in study and the cell type used. Changes to standard 2D mono-culture-based assays and implementation of 3D co-culture assays lend complexity to established models and could provide tools for identifying therapies that will match clinically the success observed with in vitro models, thereby aiding in the discovery of novel therapies.

CD16+ fibroblasts foster a trastuzumab-refractory microenvironment that is reversed by VAV2 inhibition

The leukocyte Fcγ receptor (FcγR)-mediated response is important for the efficacy of therapeutic antibodies; however, little is known about the role of FcγRs in other cell types. Here we identify a subset of fibroblasts in human breast cancer that express CD16 (FcγRIII). An abundance of these cells in HER2⁺ breast cancer patients is associated with poor prognosis and response to trastuzumab. Functionally, upon trastuzumab stimulation, CD16⁺ fibroblasts reduce drug delivery by enhancing extracellular matrix stiffness. Interaction between trastuzumab and CD16 activates the intracellular SYK-VAV2-RhoA-ROCK-MLC2-MRTF-A pathway, leading to elevated contractile force and matrix production. Targeting of a Rho family guanine nucleotide exchange factor, VAV2, which is indispensable for the function of CD16 in fibroblasts rather than leukocytes, reverses desmoplasia provoked by CD16⁺ fibroblasts. Collectively, our study reveals a role for the fibroblast FcγR in drug resistance, and suggests that VAV2 is an attractive target to augment the effects of antibody treatments.

SLC11A1 associated with tumor microenvironment is a potential biomarker of prognosis and immunotherapy efficacy for colorectal cancer

Colorectal cancer (CRC) is one of the most lethal cancers of the digestive system. The tumor microenvironment (TME) plays a central role in the initiation and development of CRC. However, little is known about the modulation mechanism of the TME in CRC. In our study, we attempted to identify a biomarker related to the TME modulation that could serve as a potential prognostic biomarker for CRC. We identified differentially expressed genes between the ImmuneScore high/low and StromalScore high/low groups. Using univariate COX regression analysis and hub gene analysis (cytoHubba), SLC11A1 was identified as the only candidate gene for subsequent analysis. CIBERSORT, EPIC, MCPcounter, and immunogenic cell death were performed to evaluate the effect of SLC11A1 on the TME. We also collected samples and performed Real-time quantitative PCR to verify the expression levels of SLC11A1 in CRC and adjacent normal tissues. The IMvigor210 cohort, TIDE score, and immunophenoscore (IPS) were used to analyze the association between SLC11A1 and immunotherapy efficacy. SLC11A1 was highly expressed in CRC tissues compared with its expression in normal colorectal tissues and was associated with poor prognosis and advanced clinicopathological stages. Gene set enrichment analysis showed that TGF-β pathways, JAK-STAT pathways, and angiogenesis were significantly enriched in the high-SLC11A1 group. Single-cell analysis validated the correlation between SLC11A1 and the TME. Using CIBERSORT, EPIC, and MCPcounter algorithms, we found that there was more macrophage and fibroblast infiltration in the SLC11A1 high-expression group. Meanwhile, high-SLC11A1 patients had lower IPS scores, higher TIDE scores, and fewer immunotherapy benefits than those of low-SLC11A1 patients. In conclusion, SLC11A1 plays a crucial role in the TME and could serve as a potential biomarker for poor prognosis and immunotherapy efficacy in CRC.

The importance of being CAFs (in cancer resistance to targeted therapies)

In the last two decades, clinical oncology has been revolutionized by the advent of targeted drugs. However, the efficacy of these therapies is significantly limited by primary and acquired resistance, that relies not only on cell-autonomous mechanisms but also on tumor microenvironment cues. Cancer-associated fibroblasts (CAFs) are extremely plastic cells of the tumor microenvironment. They not only produce extracellular matrix components that build up the structure of tumor stroma, but they also release growth factors, chemokines, exosomes, and metabolites that affect all tumor properties, including response to drug treatment. The contribution of CAFs to tumor progression has been deeply investigated and reviewed in several works. However, their role in resistance to anticancer therapies, and in particular to molecular therapies, has been largely overlooked. This review specifically dissects the role of CAFs in driving resistance to targeted therapies and discusses novel CAF targeted therapeutic strategies to improve patient survival.

Drug Resistance in Cancers: A Free Pass for Bullying

The cancer burden continues to grow globally, and drug resistance remains a substantial challenge in cancer therapy. It is well established that cancerous cells with clonal dysplasia generate the same carcinogenic lesions. Tumor cells pass on genetic templates to subsequent generations in evolutionary terms and exhibit drug resistance simply by accumulating genetic alterations. However, recent evidence has implied that tumor cells accumulate genetic alterations by progressively adapting. As a result, intratumor heterogeneity (ITH) is generated due to genetically distinct subclonal populations of cells coexisting. The genetic adaptive mechanisms of action of ITH include activating "cellular plasticity", through which tumor cells create a tumor-supportive microenvironment in which they can proliferate and cause increased damage. These highly plastic cells are located in the tumor microenvironment (TME) and undergo extreme changes to resist therapeutic drugs. Accordingly, the underlying mechanisms involved in drug resistance have been re-evaluated. Herein, we will reveal new themes emerging from initial studies of drug resistance and outline the findings regarding drug resistance from the perspective of the TME; the themes include exosomes, metabolic reprogramming, protein glycosylation and autophagy, and the relates studies aim to provide new targets and strategies for reversing drug resistance in cancers.

Agent-Based Models Help Interpret Patterns of Clinical Drug Resistance by Contextualizing Competition Between Distinct Drug Failure Modes

Introduction

Modern targeted cancer therapies are carefully crafted small molecules. These exquisite technologies exhibit an astonishing diversity of observed failure modes (drug resistance mechanisms) in the clinic. This diversity is surprising because back of the envelope calculations and classic modeling results in evolutionary dynamics suggest that the diversity in the modes of clinical drug resistance should be considerably smaller than what is observed. These same calculations suggest that the outgrowth of strong pre-existing genetic resistance mutations within a tumor should be ubiquitous. Yet, clinically relevant drug resistance occurs in the absence of obvious resistance conferring genetic alterations. Quantitatively, understanding the underlying biological mechanisms of failure mode diversity may improve the next generation of targeted anticancer therapies. It also provides insights into how intratumoral heterogeneity might shape interpatient diversity during clinical relapse.

Materials and Methods

We employed spatial agent-based models to explore regimes where spatial constraints enable wild type cells (that encounter beneficial microenvironments) to compete against genetically resistant subclones in the presence of therapy. In order to parameterize a model of microenvironmental resistance, BT20 cells were cultured in the presence and absence of fibroblasts from 16 different tissues. The degree of resistance conferred by cancer associated fibroblasts in the tumor microenvironment was quantified by treating mono- and co-cultures with letrozole and then measuring the death rates.

Results and Discussion

Our simulations indicate that, even when a mutation is more drug resistant, its outgrowth can be delayed by abundant, low magnitude microenvironmental resistance across large regions of a tumor that lack genetic resistance. These observations hold for different modes of microenvironmental resistance, including juxtacrine signaling, soluble secreted factors, and remodeled ECM. This result helps to explain the remarkable diversity of resistance mechanisms observed in solid tumors, which subverts the presumption that the failure mode that causes the quantitatively fastest growth in the presence of drug should occur most often in the clinic.

Conclusion

Our model results demonstrate that spatial effects can interact with low magnitude of resistance microenvironmental effects to successfully compete against genetic resistance that is orders of magnitude larger. Clinical outcomes of solid tumors are intrinsically connected to their spatial structure, and the tractability of spatial agent-based models like the ones presented here enable us to understand this relationship more completely.

Hobotnica: exploring molecular signature quality

A Molecular Features Set (MFS), is a result of a vast diversity of bioinformatics pipelines. The lack of a “gold standard” for most experimental data modalities makes it difficult to provide valid estimation for a particular MFS's quality. Yet, this goal can partially be achieved by analyzing inner-sample Distance Matrices (DM) and their power to distinguish between phenotypes.

The quality of a DM can be assessed by summarizing its power to quantify the differences of inner-phenotype and outer-phenotype distances. This estimation of the DM quality can be construed as a measure of the MFS's quality. 

Here we propose Hobotnica, an approach to estimate MFSs quality by their ability to stratify data, and assign them significance scores, that allow for collating various signatures and comparing their quality for contrasting groups.

Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer

Normal cells explore multiple states to survive stresses encountered during development and self-renewal as well as environmental stresses such as starvation, DNA damage, toxins or infection. Cancer cells co-opt normal stress mitigation pathways to survive stresses that accompany tumour initiation, progression, metastasis and immune evasion. Cancer therapies accentuate cancer cell stresses and invoke rapid non-genomic stress mitigation processes that maintain cell viability and thus represent key targetable resistance mechanisms. In this Review, we describe mechanisms by which tumour ecosystems, including cancer cells, immune cells and stroma, adapt to therapeutic stresses and describe three different approaches to exploit stress mitigation processes: (1) interdict stress mitigation to induce cell death; (2) increase stress to induce cellular catastrophe; and (3) exploit emergent vulnerabilities in cancer cells and cells of the tumour microenvironment. We review challenges associated with tumour heterogeneity, prioritizing actionable adaptive responses for optimal therapeutic outcomes, and development of an integrative framework to identify and target vulnerabilities that arise from adaptive responses and engagement of stress mitigation pathways. Finally, we discuss the need to monitor adaptive responses across multiple scales and translation of combination therapies designed to take advantage of adaptive responses and stress mitigation pathways to the clinic.

Materials-driven approaches to understand extrinsic drug resistance in cancer

Metastatic cancer has a poor prognosis, because it is broadly disseminated and associated with both intrinsic and acquired drug resistance. Critical unmet needs in effectively killing drug resistant cancer cells include overcoming the drug desensitization characteristics of some metastatic cancers/lesions, and tailoring therapeutic regimens to both the tumor microenvironment and the genetic profiles of the resident cancer cells. Bioengineers and materials scientists are developing technologies to determine how metastatic sites exclude therapies, and how extracellular factors (including cells, proteins, metabolites, extracellular matrix, and abiotic factors) at metastatic sites significantly affect drug pharmacodynamics. Two looming challenges are determining which feature, or combination of features, from the tumor microenvironment drive drug resistance, and what the relative impact is of extracellular signals vs. intrinsic cell genetics in determining drug response. Sophisticated systems biology tools that can de-convolve a crowded network of signals and responses, as well as controllable microenvironments capable of providing discrete and tunable extracellular cues can help us begin to interrogate the high dimensional interactions governing drug resistance in patients.

Cancer-associated fibroblasts in breast cancer: Challenges and opportunities

The tumor microenvironment is proposed to contribute substantially to the progression of cancers, including breast cancer. Cancer-associated fibroblasts (CAFs) are the most abundant components of the tumor microenvironment. Studies have revealed that CAFs in breast cancer originate from several types of cells and promote breast cancer malignancy by secreting factors, generating exosomes, releasing nutrients, reshaping the extracellular matrix, and suppressing the function of immune cells. CAFs are also becoming therapeutic targets for breast cancer due to their specific distribution in tumors and their unique biomarkers. Agents interrupting the effect of CAFs on surrounding cells have been developed and applied in clinical trials. Here, we reviewed studies examining the heterogeneity of CAFs in breast cancer and expression patterns of CAF markers in different subtypes of breast cancer. We hope that summarizing CAF-related studies from a historical perspective will help to accelerate the development of CAF-targeted therapeutic strategies for breast cancer.

Roadmap on plasticity and epigenetics in cancer

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Hyaluronan as "Agent Smith" in cancer extracellular matrix pathobiology: Regulatory roles in immune response, cancer progression and targeting

Extracellular matrix (ECM) critically regulates cancer cell behavior by governing cell signaling and properties. Hyaluronan (HA) acts as a structural and functional ECM component that mediates critical properties of cancer cells in a molecular size-dependent manner. HA fragments secreted by cancer-associated fibroblasts (CAFs) reveal the correlation of HA to CAF-mediated matrix remodeling, a key step for the initiation of metastasis. The main goal of this article is to highlight the vital functions of HA in cancer cell initiation and progression as well as HA-mediated paracrine interactions among cancer and stromal cells. Furthermore, the HA implication in mediating immune responses to cancer progression is also discussed. Novel data on the role of HA in the formation of pre-metastatic niche may contribute towards the improvement of current theranostic approaches that benefit cancer management.

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

A long-standing practice in the treatment of cancer is that of hitting hard with the maximum tolerated dose to eradicate tumors. This continuous therapy, however, selects for resistant cells, leading to the failure of the treatment. A different type of treatment strategy, adaptive therapy, has recently been shown to have a degree of success in both preclinical xenograft experiments and clinical trials. Adaptive therapy is used to maintain a tumor's volume by exploiting the competition between drug-sensitive and drug-resistant cells with minimum effective drug doses or timed drug holidays. To further understand the role of competition in the outcomes of adaptive therapy, we developed a 2D on-lattice agent-based model. Our simulations show that the superiority of the adaptive strategy over continuous therapy depends on the local competition shaped by the spatial distribution of resistant cells. Intratumor competition can also be affected by fibroblasts, which produce microenvironmental factors that promote cancer cell growth. To this end, we simulated the impact of different fibroblast distributions on treatment outcomes. As a proof of principle, we focused on five types of distribution of fibroblasts characterized by different locations, shapes, and orientations of the fibroblast region with respect to the resistant cells. Our simulation shows that the spatial architecture of fibroblasts modulates tumor progression in both continuous and adaptive therapy. Finally, as a proof of concept, we simulated the outcomes of adaptive therapy of a virtual patient with four metastatic sites composed of different spatial distributions of fibroblasts and drug-resistant cell populations. Our simulation highlights the importance of undetected metastatic lesions on adaptive therapy outcomes.

Multiomics Analysis of Spatially Distinct Stromal Cells Reveals Tumor-Induced O-Glycosylation of the CDK4-pRB Axis in Fibroblasts at the Invasive Tumor Edge

The invasive leading edge represents a potential gateway for tumor metastasis. The role of fibroblasts from the tumor edge in promoting cancer invasion and metastasis has not been comprehensively elucidated. We hypothesize that cross-talk between tumor and stromal cells within the tumor microenvironment results in activation of key biological pathways depending on their position in the tumor (edge vs. core). Here we highlight phenotypic differences between tumor-adjacent-fibroblasts (TAF) from the invasive edge and tumor core fibroblasts from the tumor core, established from human lung adenocarcinomas. A multiomics approach that includes genomics, proteomics, and O-glycoproteomics was used to characterize cross-talk between TAFs and cancer cells. These analyses showed that O-glycosylation, an essential posttranslational modification resulting from sugar metabolism, alters key biological pathways including the cyclin-dependent kinase 4 (CDK4) and phosphorylated retinoblastoma protein axis in the stroma and indirectly modulates proinvasive features of cancer cells. In summary, the O-glycoproteome represents a new consideration for important biological processes involved in tumor-stroma cross-talk and a potential avenue to improve the anticancer efficacy of CDK4 inhibitors.

SIGNIFICANCE

A multiomics analysis of spatially distinct fibroblasts establishes the importance of the stromal O-glycoproteome in tumor-stroma interactions at the leading edge and provides potential strategies to improve cancer treatment. See related commentary by De Wever, p. 537.

Regulation of Bcl-2 Family Proteins in Estrogen Receptor-Positive Breast Cancer and Their Implications in Endocrine Therapy

Estrogen receptor (ER)-positive breast cancer accounts for around two-thirds of breast cancer occurrences, with endocrine therapy serving as first-line therapy in most cases. Targeting estrogen signaling pathways, which play a central role in regulating ER+ breast cell proliferation and survival, has proven to improve patient outcomes. However, despite the undeniable advantages of endocrine therapy, a subset of breast cancer patients develop acquired or intrinsic resistance to ER-targeting agents, limiting their efficacy. The activation of downstream ER signaling pathways upregulates pro-survival mechanisms that have been shown to influence the response of cells to endocrine therapy. The Bcl-2 family proteins play a central role in cell death regulation and have been shown to contribute to endocrine therapy resistance, supporting the survival of breast cancer cells and enhancing cell death evasion. Due to the overexpression of anti-apoptotic Bcl-2 proteins in ER-positive breast cancer, the role of these proteins as potential targets in hormone-responsive breast cancer is growing in interest. In particular, recent advances in the development of BH3 mimetics have enabled their evaluation in preclinical studies with ER+ breast cancer models, and BH3 mimetics have entered early ER+ breast cancer clinical trials. This review summarizes the molecular mechanisms underlying the regulation of Bcl-2 family proteins in ER+ breast cancer. Furthermore, an overview of recent advances in research regarding the efficacy of BH3 mimetics in ER+ breast cancer has been provided.

Engineered Bacteria Enhance Immunotherapy and Targeted Therapy through Stromal Remodeling of Tumors

Desmoplastic solid tumors are characterized by the rapid build-up of extracellular matrix (ECM) macromolecules, such as hyaluronic acid (HA). The resulting physiological barrier prevents the infiltration of immune cells and also impedes the delivery of anticancer agents. The development of a hypervesiculating Escherichia coli Nissle (ΔECHy) based tumor targeting bacterial system capable of distributing a fusion peptide, cytolysin A (ClyA)-hyaluronidase (Hy) via outer membrane vesicles (OMVs) is reported. The capability of targeting hypoxic tumors, manufacturing recombinant proteins in situ and the added advantage of an on-site OMV based distribution system makes the engineered bacterial vector a unique candidate for peptide delivery. The HA degrading potential of Hy for stromal modulation is combined with the cytolytic activity of ClyA followed by testing it within syngeneic cancer models. ΔECHy is combined with immune checkpoint antibodies and tyrosine kinase inhibitors (TKIs) to demonstrate that remodeling the tumor stroma results in the improvement of immunotherapy outcomes and enhancing the efficacy of biological signaling inhibitors. The biocompatibility of ΔECHy is also investigated to show that the engineered bacteria are effectively cleared, elicit minimal inflammatory and immune responses, and therefore could be a reliable candidate as a live biotherapeutic.

A novel anti-tumor/anti-tumor-associated fibroblast/anti-mPEG tri-specific antibody to maximize the efficacy of mPEGylated nanomedicines against fibroblast-rich solid tumor

The therapeutic efficacy of methoxypolyethylene glycol (mPEG)-coated nanomedicines in solid tumor treatment is hindered by tumor-associated fibroblasts (TAFs), which promote tumor progression and form physical barriers. We developed an anti-HER2/anti-FAP/anti-mPEG tri-specific antibody (TsAb) for one-step conversion of mPEG-coated liposomal doxorubicin (Lipo-Dox) to immunoliposomes, which simultaneously target HER2⁺ breast cancer cells and FAP⁺ TAFs. The non-covalent modification did not adversely alter the physical characteristics and stability of Lipo-Dox. The TsAb-Lipo-Dox exhibited specific targeting and enhanced cytotoxicity against mono- and co-cultured HER2⁺ breast cancer cells and FAP⁺ TAFs, compared to bi-specific antibody (BsAb) modified or unmodified Lipo-Dox. An in vivo model of human breast tumor containing TAFs also revealed the improved tumor accumulation and therapeutic efficacy of TsAb-modified mPEGylated liposomes without signs of toxicity. Our data indicate that arming clinical mPEGylated nanomedicines with the TsAb is a feasible and applicable approach for overcoming the difficulties caused by TAFs in solid tumor treatment.

Hobotnica: exploring molecular signature quality

A Molecular Features Set (MFS), is a result of a vast diversity of bioinformatics pipelines. The lack of a "gold standard" for most experimental data modalities makes it difficult to provide valid estimation for a particular MFS's quality. Yet, this goal can partially be achieved by analyzing inner-sample Distance Matrices (DM) and their power to distinguish between phenotypes. The quality of a DM can be assessed by summarizing its power to quantify the differences of inner-phenotype and outer-phenotype distances. This estimation of the DM quality can be construed as a measure of the MFS's quality.  Here we propose Hobotnica, an approach to estimate MFSs quality by their ability to stratify data, and assign them significance scores, that allow for collating various signatures and comparing their quality for contrasting groups.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

Microenvironmental modulation of the developing tumour: an immune-stromal dialogue

Successful establishment of a tumour relies on a cascade of interactions between cancer cells and stromal cells within an evolving microenvironment. Both immune and nonimmune cellular components are key factors in this process, and the individual players may change their role from tumour elimination to tumour promotion as the microenvironment develops. While the tumour-stroma crosstalk present in an established tumour is well-studied, aspects in the early tumour or premalignant microenvironment have received less attention. This is in part due to the challenges in studying this process in the clinic or in mouse models. Here, we review the key anti- and pro-tumour factors in the early microenvironment and discuss how understanding this process may be exploited in the clinic.

A SNAI2-PEAK1-INHBA stromal axis drives progression and lapatinib resistance in HER2-positive breast cancer by supporting subpopulations of tumor cells positive for antiapoptotic and stress signaling markers

Intercellular mechanisms by which the stromal microenvironment contributes to solid tumor progression and targeted therapy resistance remain poorly understood, presenting significant clinical hurdles. PEAK1 (Pseudopodium-Enriched Atypical Kinase One) is an actin cytoskeleton- and focal adhesion-associated pseudokinase that promotes cell state plasticity and cancer metastasis by mediating growth factor-integrin signaling crosstalk. Here, we determined that stromal PEAK1 expression predicts poor outcomes in HER2-positive breast cancers high in SNAI2 expression and enriched for MSC content. Specifically, we identified that the fibroblastic stroma in HER2-positive breast cancer patient tissue stains positive for both nuclear SNAI2 and cytoplasmic PEAK1. Furthermore, mesenchymal stem cells (MSCs) and cancer-associated fibroblasts (CAFs) express high PEAK1 protein levels and potentiate tumorigenesis, lapatinib resistance and metastasis of HER2-positive breast cancer cells in a PEAK1-dependent manner. Analysis of PEAK1-dependent secreted factors from MSCs revealed INHBA/activin-A as a necessary factor in the conditioned media of PEAK1-expressing MSCs that promotes lapatinib resistance. Single-cell CycIF analysis of MSC-breast cancer cell co-cultures identified enrichment of p-Akthigh/p-gH2AXlow, MCL1high/p-gH2AXlow and GRP78high/VIMhigh breast cancer cell subpopulations by the presence of PEAK1-expressing MSCs and lapatinib treatment. Bioinformatic analyses on a PEAK1-centric stroma-tumor cell gene set and follow-up immunostaining of co-cultures predict targeting antiapoptotic and stress pathways as a means to improve targeted therapy responses and patient outcomes in HER2-positive breast cancer and other stroma-rich malignancies. These data provide the first evidence that PEAK1 promotes tumorigenic phenotypes through a previously unrecognized SNAI2-PEAK1-INHBA stromal cell axis.

Engineering stromal heterogeneity in cancer

Based on our exponentially increasing knowledge of stromal heterogeneity from advances in single-cell technologies, the notion that stromal cell types exist as a spectrum of unique subpopulations that have specific functions and spatial distributions in the tumor microenvironment has significant impact on tumor modeling for drug development and personalized drug testing. In this Review, we discuss the importance of incorporating stromal heterogeneity and tumor architecture, and propose an overall approach to guide the reconstruction of stromal heterogeneity in vitro for tumor modeling. These next-generation tumor models may support the development of more precise drugs targeting specific stromal cell subpopulations, as well as enable improved recapitulation of patient tumors in vitro for personalized drug testing.

Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response

Tumors are not only aggregates of malignant cells but also well-organized complex ecosystems. The immunological components within tumors, termed the tumor immune microenvironment (TIME), have long been shown to be strongly related to tumor development, recurrence and metastasis. However, conventional studies that underestimate the potential value of the spatial architecture of the TIME are unable to completely elucidate its complexity. As innovative high-flux and high-dimensional technologies emerge, researchers can more feasibly and accurately detect and depict the spatial architecture of the TIME. These findings have improved our understanding of the complexity and role of the TIME in tumor biology. In this review, we first epitomized some representative emerging technologies in the study of the spatial architecture of the TIME and categorized the description methods used to characterize these structures. Then, we determined the functions of the spatial architecture of the TIME in tumor biology and the effects of the gradient of extracellular nonspecific chemicals (ENSCs) on the TIME. We also discussed the potential clinical value of our understanding of the spatial architectures of the TIME, as well as current limitations and future prospects in this novel field. This review will bring spatial architectures of the TIME, an emerging dimension of tumor ecosystem research, to the attention of more researchers and promote its application in tumor research and clinical practice.