Cell morphology best predicts tumorigenicity and metastasis in vivo across multiple TNBC cell lines of different metastatic potential

BACKGROUND

Metastasis is the leading cause of death in breast cancer patients. For metastasis to occur, tumor cells must invade locally, intravasate, and colonize distant tissues and organs, all steps that require tumor cell migration. The majority of studies on invasion and metastasis rely on human breast cancer cell lines. While it is known that these cells have different properties and abilities for growth and metastasis, the in vitro morphological, proliferative, migratory, and invasive behavior of these cell lines and their correlation to in vivo behavior is poorly understood. Thus, we sought to classify each cell line as poorly or highly metastatic by characterizing tumor growth and metastasis in a murine model of six commonly used human triple-negative breast cancer xenografts, as well as determine which in vitro assays commonly used to study cell motility best predict in vivo metastasis.

METHODS

We evaluated the liver and lung metastasis of human TNBC cell lines MDA-MB-231, MDA-MB-468, BT549, Hs578T, BT20, and SUM159 in immunocompromised mice. We characterized each cell line's cell morphology, proliferation, and motility in 2D and 3D to determine the variation in these parameters between cell lines.

RESULTS

We identified MDA-MB-231, MDA-MB-468, and BT549 cells as highly tumorigenic and metastatic, Hs578T as poorly tumorigenic and metastatic, BT20 as intermediate tumorigenic with poor metastasis to the lungs but highly metastatic to the livers, and SUM159 as intermediate tumorigenic but poorly metastatic to the lungs and livers. We showed that metrics that characterize cell morphology are the most predictive of tumor growth and metastatic potential to the lungs and liver. Further, we found that no single in vitro motility assay in 2D or 3D significantly correlated with metastasis in vivo.

CONCLUSIONS

Our results provide an important resource for the TNBC research community, identifying the metastatic potential of 6 commonly used cell lines. Our findings also support the use of cell morphological analysis to investigate the metastatic potential and emphasize the need for multiple in vitro motility metrics using multiple cell lines to represent the heterogeneity of metastasis in vivo.

Carcinogen exposure enhances cancer immunogenicity by blocking the development of an immunosuppressive tumor microenvironment

Carcinogen exposure is strongly associated with enhanced cancer immunogenicity. Increased tumor mutational burden and resulting neoantigen generation have been proposed to link carcinogen exposure and cancer immunogenicity. However, the neoantigen-independent immunological impact of carcinogen exposure on cancer is unknown. Here, we demonstrate that chemical carcinogen-exposed cancer cells fail to establish an immunosuppressive tumor microenvironment (TME), resulting in their T cell-mediated rejection in vivo. A chemical carcinogen-treated breast cancer cell clone that lacked any additional coding region mutations (i.e., neoantigen) was rejected in mice in a T cell-dependent manner. Strikingly, the coinjection of carcinogen- and control-treated cancer cells prevented this rejection, suggesting that the loss of immunosuppressive TME was the dominant cause of rejection. Reduced M-CSF expression by carcinogen-treated cancer cells significantly suppressed tumor-associated macrophages (TAMs) and resulted in the loss of an immunosuppressive TME. Single-cell analysis of human lung cancers revealed a significant reduction in the immunosuppressive TAMs in former smokers compared with individuals who had never smoked. These findings demonstrate that carcinogen exposure impairs the development of an immunosuppressive TME and indicate a novel link between carcinogens and cancer immunogenicity.

PET and Optical Imaging of Caveolin-1 in Gastric Tumors

Previous studies have suggested tumoral caveolin-1 (CAV1) as a predictive biomarker for the response to anti-HER2 antibody drug therapies in gastric tumors. In this study, radiolabeled and fluorescently labeled anti-CAV1 antibodies were developed and tested as an immunoPET or optical imaging agent to detect CAV1 in HER2-positive/CAV1-high NCIN87 gastric tumors. The expression of CAV1 receptors in NCIN87 gastric tumors and nontumor murine organs was determined by Western blot. Binding assays were performed to validate the anti-CAV1 antibody specificity for CAV1-expressing NCIN87 cancer cells. Subcutaneous and orthotopic NCIN87 xenografts were used for PET imaging and ex vivo biodistribution of the radioimmunoconjugate. Additional HER2-PET and CAV1-optical imaging was also performed to determine CAV1 in the HER2-positive tumors. 89Zr-labeled anti-CAV1 antibody was able to bind to CAV1-expressing NCIN87 cells with a Bmax value of 2.7 × 103 CAV1 receptors/cell in vitro. ImmunoPET images demonstrated the localization of the antibody in subcutaneous NCIN87 xenografts. In the orthotopic model, CAV1 expression was also observed by optical imaging in the HER2-positive tumors previously imaged with HER2-PET. Ex vivo biodistribution analysis further confirmed these imaging results. The preclinical data from this study demonstrate the potential of using CAV1-PET and optical imaging for detecting gastric tumors.

Irradiated Mammary Spheroids Elucidate Mechanisms of Macrophage-Mediated Breast Cancer Recurrence

Introduction

While most patients with triple negative breast cancer receive radiation therapy to improve outcomes, a significant subset of patients continue to experience recurrence. Macrophage infiltration into radiation-damaged sites has been shown to promote breast cancer recurrence in pre-clinical models. However, the mechanisms that drive recurrence are unknown. Here, we developed a novel spheroid model to evaluate macrophage-mediated tumor cell recruitment.

Methods

We characterized infiltrating macrophage phenotypes into irradiated mouse mammary tissue via flow cytometry. We then engineered a spheroid model of radiation damage with primary fibroblasts, macrophages, and 4T1 mouse mammary carcinoma cells using in vivo macrophage infiltration results to inform our model. We analyzed 4T1 infiltration into spheroids when co-cultured with biologically relevant ratios of pro-healing M2:pro-inflammatory M1 macrophages. Finally, we quantified interleukin 6 (IL-6) secretion associated with conditions favorable to tumor cell infiltration, and we directly evaluated the impact of IL-6 on tumor cell invasiveness in vitro and in vivo.

Results

In our in vivo model, we observed a significant increase in M2 macrophages in mouse mammary glands 10 days post-irradiation. We determined that tumor cell motility toward irradiated spheroids was enhanced in the presence of a 2:1 ratio of M2:M1 macrophages. We also measured a significant increase in IL-6 secretion after irradiation both in vivo and in our model. This secretion increased tumor cell invasiveness, and tumor cell invasion and recruitment were mitigated by neutralizing IL-6.

Conclusions

Our work suggests that interactions between infiltrating macrophages and damaged stromal cells facilitate breast cancer recurrence through IL-6 signaling.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-023-00775-x.

Replisome dysfunction upon inducible TIMELESS degradation synergizes with ATR inhibition to trigger replication catastrophe

The structure of DNA replication forks is preserved by TIMELESS (TIM) in the fork protection complex (FPC) to support seamless fork progression. While the scaffolding role of the FPC to couple the replisome activity is much appreciated, the detailed mechanism whereby inherent replication fork damage is sensed and counteracted during DNA replication remains largely elusive. Here, we implemented an auxin-based degron system that rapidly triggers inducible proteolysis of TIM as a source of endogenous DNA replication stress and replisome dysfunction to dissect the signaling events that unfold at stalled forks. We demonstrate that acute TIM degradation activates the ATR-CHK1 checkpoint, whose inhibition culminates in replication catastrophe by single-stranded DNA accumulation and RPA exhaustion. Mechanistically, unrestrained replisome uncoupling, excessive origin firing, and aberrant reversed fork processing account for the synergistic fork instability. Simultaneous TIM loss and ATR inactivation triggers DNA-PK-dependent CHK1 activation, which is unexpectedly necessary for promoting fork breakage by MRE11 and catastrophic cell death. We propose that acute replisome dysfunction results in a hyper-dependency on ATR to activate local and global fork stabilization mechanisms to counteract irreversible fork collapse. Our study identifies TIM as a point of replication vulnerability in cancer that can be exploited with ATR inhibitors.

Quantification of subtype purity in Luminal A breast cancer predicts clinical characteristics and survival

PURPOSE

PAM50 profiling assigns each breast cancer to a single intrinsic subtype based on a bulk tissue sample. However, individual cancers may show evidence of admixture with an alternate subtype that could affect prognosis and treatment response. We developed a method to model subtype admixture using whole transcriptome data and associated it with tumor, molecular, and survival characteristics for Luminal A (LumA) samples.

METHODS

We combined TCGA and METABRIC cohorts and obtained transcriptome, molecular, and clinical data, which yielded 11,379 gene transcripts in common and 1,178 cases assigned to LumA. We used semi-supervised non-negative matrix factorization (ssNMF) to compute the subtype admixture proportions of the four major subtypes-pLumA, pLumB, pHER2, and pBasal-for each case and measured associations with tumor characteristics, molecular features, and survival.

RESULTS

Luminal A cases in the lowest versus highest quartile for pLumA transcriptomic proportion had a 27% higher prevalence of stage > 1, nearly a threefold higher prevalence of TP53 mutation, and a hazard ratio of 2.08 for overall mortality. We found positive associations between pHER2 and HER2 positivity by IHC or FISH; between pLumB and PR negativity; and between pBasal and younger age, node positivity, TP53 mutation, and EGFR expression. Predominant basal admixture, in contrast to predominant LumB or HER2 admixture, was not associated with shorter survival.

CONCLUSION

Bulk sampling for genomic analyses provides an opportunity to expose intratumor heterogeneity, as reflected by subtype admixture. Our results elucidate the striking extent of diversity among LumA cancers and suggest that determining the extent and type of admixture holds promise for refining individualized therapy. LumA cancers with a high degree of basal admixture appear to have distinct biological characteristics that warrant further study.

RFWD3 promotes ZRANB3 recruitment to regulate the remodeling of stalled replication forks

Replication fork reversal is an important mechanism to protect the stability of stalled forks and thereby preserve genomic integrity. While multiple enzymes have been identified that can remodel forks, their regulation remains poorly understood. Here, we demonstrate that the ubiquitin ligase RFWD3, whose mutation causes Fanconi Anemia, promotes recruitment of the DNA translocase ZRANB3 to stalled replication forks and ubiquitinated sites of DNA damage. Using electron microscopy, we show that RFWD3 stimulates fork remodeling in a ZRANB3-epistatic manner. Fork reversal is known to promote nascent DNA degradation in BRCA2-deficient cells. Consistent with a role for RFWD3 in fork reversal, inactivation of RFWD3 in these cells rescues fork degradation and collapse, analogous to ZRANB3 inactivation. RFWD3 loss impairs ZRANB3 localization to spontaneous nuclear foci induced by inhibition of the PCNA deubiquitinase USP1. We demonstrate that RFWD3 promotes PCNA ubiquitination and interaction with ZRANB3, providing a mechanism for RFWD3-dependent recruitment of ZRANB3. Together, these results uncover a new role for RFWD3 in regulating ZRANB3-dependent fork remodeling.

Understanding and modeling nerve-cancer interactions

The peripheral nervous system plays an important role in cancer progression. Studies in multiple cancer types have shown that higher intratumoral nerve density is associated with poor outcomes. Peripheral nerves have been shown to directly regulate tumor cell properties, such as growth and metastasis, as well as affect the local environment by modulating angiogenesis and the immune system. In this Review, we discuss the identity of nerves in organs in the periphery where solid tumors grow, the known mechanisms by which nerve density increases in tumors, and the effects these nerves have on cancer progression. We also discuss the strengths and weaknesses of current in vitro and in vivo models used to study nerve-cancer interactions. Increased understanding of the mechanisms by which nerves impact tumor progression and the development of new approaches to study nerve-cancer interactions will facilitate the discovery of novel treatment strategies to treat cancer by targeting nerves.

OUP accepted manuscript

Motivation

Identifying cell types and their abundances and how these evolve during tumor progression is critical to understanding the mechanisms of metastasis and identifying predictors of metastatic potential that can guide the development of new diagnostics or therapeutics. Single-cell RNA sequencing (scRNA-seq) has been especially promising in resolving heterogeneity of expression programs at the single-cell level, but is not always feasible, e.g. for large cohort studies or longitudinal analysis of archived samples. In such cases, clonal subpopulations may still be inferred via genomic deconvolution, but deconvolution methods have limited ability to resolve fine clonal structure and may require reference cell type profiles that are missing or imprecise. Prior methods can eliminate the need for reference profiles but show unstable performance when few bulk samples are available.

Results

In this work, we develop a new method using reference scRNA-seq to interpret sample collections for which only bulk RNA-seq is available for some samples, e.g. clonally resolving archived primary tissues using scRNA-seq from metastases. By integrating such information in a Quadratic Programming framework, our method can recover more accurate cell types and corresponding cell type abundances in bulk samples. Application to a breast tumor bone metastases dataset confirms the power of scRNA-seq data to improve cell type inference and quantification in same-patient bulk samples.

Availability and implementation

Source code is available on Github at https://github.com/CMUSchwartzLab/RADs.

The RNA m6A reader YTHDF2 controls NK cell antitumor and antiviral immunity

N 6-methyladenosine (m6A) is the most prevalent posttranscriptional modification on RNA. NK cells are the predominant innate lymphoid cells that mediate antiviral and antitumor immunity. However, whether and how m6A modifications affect NK cell immunity remain unknown. Here, we discover that YTHDF2, a well-known m6A reader, is upregulated in NK cells upon activation by cytokines, tumors, and cytomegalovirus infection. Ythdf2 deficiency in NK cells impairs NK cell antitumor and antiviral activity in vivo. YTHDF2 maintains NK cell homeostasis and terminal maturation, correlating with modulating NK cell trafficking and regulating Eomes, respectively. YTHDF2 promotes NK cell effector function and is required for IL-15-mediated NK cell survival and proliferation by forming a STAT5-YTHDF2 positive feedback loop. Transcriptome-wide screening identifies Tardbp to be involved in cell proliferation or survival as a YTHDF2-binding target in NK cells. Collectively, we elucidate the biological roles of m6A modifications in NK cells and highlight a new direction to harness NK cell antitumor immunity.

Decellularized extracellular matrix scaffolds identify full-length collagen VI as a driver of breast cancer cell invasion in obesity and metastasis

The extracellular matrix (ECM), a major component of the tumor microenvironment, promotes local invasion to drive metastasis. Here, we describe a method to study whole-tissue ECM effects from disease states associated with metastasis on tumor cell phenotypes and identify the individual ECM proteins and signaling pathways that are driving these effects. We show that decellularized ECM from tumor-bearing and obese mammary glands drives TNBC cell invasion. Proteomics of the ECM from the obese mammary gland led us to identify full-length collagen VI as a novel driver of TNBC cell invasion whose abundance in tumor stroma increases with body mass index in human TNBC patients. Last, we describe the mechanism by which collagen VI contributes to TNBC cell invasion via NG2-EGFR cross-talk and MAPK signaling. Overall, these studies demonstrate the value of decellularized ECM scaffolds obtained from tissues to identify novel functions of the ECM.

Robust and accurate deconvolution of tumor populations uncovers evolutionary mechanisms of breast cancer metastasis

MOTIVATION

Cancer develops and progresses through a clonal evolutionary process. Understanding progression to metastasis is of particular clinical importance, but is not easily analyzed by recent methods because it generally requires studying samples gathered years apart, for which modern single-cell sequencing is rarely an option. Revealing the clonal evolution mechanisms in the metastatic transition thus still depends on unmixing tumor subpopulations from bulk genomic data.

METHODS

We develop a novel toolkit called robust and accurate deconvolution (RAD) to deconvolve biologically meaningful tumor populations from multiple transcriptomic samples spanning the two progression states. RAD uses gene module compression to mitigate considerable noise in RNA, and a hybrid optimizer to achieve a robust and accurate solution. Finally, we apply a phylogenetic algorithm to infer how associated cell populations adapt across the metastatic transition via changes in expression programs and cell-type composition.

RESULTS

We validated the superior robustness and accuracy of RAD over alternative algorithms on a real dataset, and validated the effectiveness of gene module compression on both simulated and real bulk RNA data. We further applied the methods to a breast cancer metastasis dataset, and discovered common early events that promote tumor progression and migration to different metastatic sites, such as dysregulation of ECM-receptor, focal adhesion and PI3k-Akt pathways.

AVAILABILITY AND IMPLEMENTATION

The source code of the RAD package, models, experiments and technical details such as parameters, is available at https://github.com/CMUSchwartzLab/RAD.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A novel network-based approach for discovering dynamic metabolic biomarkers in cardiovascular disease

Metabolic biomarkers may play an important role in the diagnosis, prognostication and assessment of response to pharmacological therapy in complex diseases. The process of discovering new metabolic biomarkers is a non-trivial task which involves a number of bioanalytical processing steps coupled with a computational approach for the search, prioritization and verification of new biomarker candidates. Kinetic analysis provides an additional dimension of complexity in time-series data, allowing for a more precise interpretation of biomarker dynamics in terms of molecular interaction and pathway modulation. A novel network-based computational strategy for the discovery of putative dynamic biomarker candidates is presented, enabling the identification and verification of unexpected metabolic signatures in complex diseases such as myocardial infarction. The novelty of the proposed method lies in combining metabolic time-series data into a superimposed graph representation, highlighting the strength of the underlying kinetic interaction of preselected analytes. Using this approach, we were able to confirm known metabolic signatures and also identify new candidates such as carnosine and glycocholic acid, and pathways that have been previously associated with cardiovascular or related diseases. This computational strategy may serve as a complementary tool for the discovery of dynamic metabolic or proteomic biomarkers in the field of clinical medicine.

Systematic identification of mutations and copy number alterations associated with cancer patient prognosis

Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed the genomic profiles of 17,879 tumors from patients with known outcomes. We find that mutations in almost all cancer driver genes contain remarkably little information on patient prognosis. However, CNAs in these same driver genes harbor significant prognostic power. Focal CNAs are associated with worse outcomes than broad alterations, and CNAs in many driver genes remain prognostic when controlling for stage, grade, TP53 status, and total aneuploidy. By performing a meta-analysis across independent patient cohorts, we identify robust prognostic biomarkers in specific cancer types, and we demonstrate that a subset of these alterations also confer specific therapeutic vulnerabilities. In total, our analysis establishes a comprehensive resource for cancer biomarker identification and underscores the importance of gene copy number profiling in assessing clinical risk.

KDM5 lysine demethylases are involved in maintenance of 3'UTR length

The complexity by which cells regulate gene and protein expression is multifaceted and intricate. Regulation of 3' untranslated region (UTR) processing of mRNA has been shown to play a critical role in development and disease. However, the process by which cells select alternative mRNA forms is not well understood. We discovered that the Saccharomyces cerevisiae lysine demethylase, Jhd2 (also known as KDM5), recruits 3'UTR processing machinery and promotes alteration of 3'UTR length for some genes in a demethylase-dependent manner. Interaction of Jhd2 with both chromatin and RNA suggests that Jhd2 affects selection of polyadenylation sites through a transcription-coupled mechanism. Furthermore, its mammalian homolog KDM5B (also known as JARID1B or PLU1), but not KDM5A (also known as JARID1A or RBP2), promotes shortening of CCND1 transcript in breast cancer cells. Consistent with these results, KDM5B expression correlates with shortened CCND1 in human breast tumor tissues. In contrast, both KDM5A and KDM5B are involved in the lengthening of DICER1. Our findings suggest both a novel role for this family of demethylases and a novel targetable mechanism for 3'UTR processing.