Integrated RNA and DNA sequencing reveals early drivers of metastatic breast cancer

Pyroptosis-Inducing Platinum(IV) Prodrugs via GSDME Pathway for Chemoimmunotherapy and Metastasis Inhibition in Triple-Negative Breast Cancer

Pyroptosis has attracted significant attention for its role in cancer chemotherapy and immunotherapy. However, few drugs have been reported to induce pyroptosis via the Caspase-3/gasdermin E (GSDME) pathway. Herein, three novel PtIV prodrugs, MRP, DRP, and HRP are rationally designed by conjugating DNA methyltransferase (DNMT) inhibitor (RG108) and/or histone deacetylase (HDAC) inhibitor (PhB) to the PtIV center. These prodrugs can be easily reduced to cisplatin (CDDP) due to the high glutathione (GSH) levels in tumors, liberating the coordinated ligands. Released RG108 reactivates the GSDME gene and reduces pyroptosis in low GSDME-expressing tumor cells. Meanwhile, PhB-induced chromatin loosening enhances CDDP-DNA binding, which not only increases Caspase-3 expression, but also upregulates GSDME. HRP demonstrates superior ability to suppress tumor growth and metastasis while reducing systemic toxicity compared with CDDP. By reactivating GSDME and loosening chromatin, HRP effectively boosts tumor cell pyroptosis and exhibits the most pronounced anticancer performance. These findings highlight HRP's potential as a therapeutic agent for triple-negative breast cancer (TNBC) and offer innovative strategies for combining chemotherapy with immunotherapy. To the best of current knowledge, this is the first report of platinum complexes inducing pyroptosis via the Caspase-3/GSDME pathway in low GSDME-expressing tumor cells.

Single-Cell Analysis Reveals that Vitamin C Inhibits Bone Metastasis of Renal Cancer via Cell Cycle Arrest and Microenvironment Remodeling

Bone metastasis is the second most common site of distant metastatic spread in renal cell carcinoma (RCC) patients, significantly contributing to cancer-related mortality. The metastatic process is driven by both intrinsic tumor cell properties, such as cancer stem cell-like characteristics, and the bone microenvironment. Understanding the complex interactions between cancer cells and their niche is crucial for identifying therapeutic targets to eliminate metastasis-initiating cells and prevent overt metastasis. In this study, a murine bone metastasis model is developed using renal cancer cells derived from fibrin gel-induced 3D tumor spheres, which exhibit stem-like phenotypes. It is found that a stable form of vitamin C, L-ascorbic acid 2-phosphate sesquimagnesium (APM), significantly inhibits the growth of renal cancer stem-like cells in vitro and the progression of RCC bone metastasis in vivo. Single-cell RNA sequencing revealed that APM induces cell cycle arrest and reduces the metastatic potential of cancer cells. Furthermore, APM remodels the tumor microenvironment by suppressing osteoclast differentiation and neutrophil recruitment. Combining APM with a CXCR2 antagonist, SB225002, further inhibits bone metastasis progression. This study provides a high-resolution profile of vitamin C's antitumor effects in the bone metastatic microenvironment and supports the rationale for clinical trials of vitamin C in bone metastatic RCC.

Genomic and immune profiling of breast cancer brain metastases

BACKGROUND

Brain metastases (BrM) arising from breast cancer (BC) are an increasing consequence of advanced disease, with up to half of patients with metastatic HER2 + or triple negative BC experiencing central nervous system (CNS) recurrence. The genomic alterations driving CNS recurrence, along with contributions of the immune microenvironment, particularly by intrinsic subtype, remain unclear.

METHODS

We characterized the genomic and immune landscape of BCBrM from a cohort of 42 patients by sequencing whole-exome DNA (WES) and total RNA libraries from frozen and FFPE BrM and FFPE extracranial tumors (ECT). Analyses included PAM50 intrinsic subtypes, somatic mutations, copy number variations (CNV), pathway alterations, immune cell type deconvolution, and associations with clinical outcomes RESULTS: Intrinsic subtype calls were concordant for the majority of BrM-ECT pairs (60%). Across all BrM and ECT samples, the most common somatic gene mutation was TP53 (64%, 30/47). For patients with matched FFPE BrM-FFPE ECT, alterations tended to be conserved across tissue type, although differential somatic mutations and CNV in specific genes were observed. Several genomic pathways were differentially expressed between patient-matched BrM-ECT; MYC targets, DNA damage repair, cholesterol homeostasis, and oxidative phosphorylation were higher in BrM, while immune-related pathways were lower in BrM. Deconvolution of immune populations between BrM-ECT demonstrated activated dendritic cell populations were higher in BrM compared to ECT. Increased expression of several oncogenic preselected pathways in BrM were associated with inferior survival, including DNA damage repair, inflammatory response, and oxidative phosphorylation CONCLUSIONS: Collectively, this study illustrates that while some genomic alterations are shared between BrM and ECT, there are also unique aspects of BrM including somatic mutations, CNV, pathway alterations, and immune landscape. A deeper understanding of differences inherent to BrM will contribute to the development of BrM-tailored therapeutic strategies. Additional analyses are warranted in larger cohorts, particularly with additional matched BrM-ECT.

Multiple data sets to explore the key molecules and mechanism of lymph node metastasis in gastric cancer

OBJECTIVE

To explore the key molecules and regulatory mechanisms of lymph node metastasis in gastric cancer.

METHODS

The differential genes and key genes of lymph node metastasis in gastric cancer were analyzed by utilizing multiple data sets. The key genes were analyzed by GSEA analysis, transcription factor analysis, nomogram prediction model construction, immune infiltration analysis, GSVA analysis, drug sensitive analysis and single cell data analysis.

RESULTS

Abnormal expression of key genes including CDRT15P1, DENND3, F2R, FNDC3B, IRAK3, MS4A2, PDK4, PKIA and activation of related signaling pathways might be the result of ultraviolet radiation-induced DNA damage, which was closely related to lymph node metastasis in gastric cancer. The key genes were regulated by a variety of transcription factors, which were strongly connected with the invasion of immune cells and the sensitivity of a variety of drugs. The nomogram prediction model, which is based on the key genes associated with lymph node metastasis and the TNM of gastric cancer, demonstrated a high level of predictive efficiency.

CONCLUSION

CDRT15P1, DENND3, F2R, FNDC3B, IRAK3, MS4A2, PDK4 and PKIA may be the key genes affecting lymph node metastasis in gastric cancer, and F2R has higher biological importance.

Multimodal data integration in early-stage breast cancer

The use of biomarkers in breast cancer has significantly improved patient outcomes through targeted therapies, such as hormone therapy anti-Her2 therapy and CDK4/6 or PARP inhibitors. However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors. The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers. This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification. We examined the primary challenges and opportunities of these multimodal data integration algorithms, including their advantages, limitations, and critical considerations for future research. We aimed to describe models that are not only academically and preclinically relevant, but also applicable to clinical settings.

Manganese-induced Precocious Puberty Alters Mammary Epithelial Cell Proliferation in Female Rats

Precocious puberty (PP) is an established breast cancer risk factor. In the normal mammary gland, hormone receptor-positive (HR+) cells rarely proliferate. In breast cancer, proliferating epithelial cells are often HR+. It is not known if PP can modify this population of proliferating HR+ cells. Previously, we established a manganese-induced precocious puberty (MnPP) model to study the effects of PP on mammary gland development in female rats. Here, we characterized the distribution of HR+ proliferating mammary epithelial cells in prepubertal and adult rodents, in association with precocious puberty. Female rats were exposed daily to 10 mg/kg manganese chloride or saline (control) from postnatal day (PND) 12 to PND 30. Mammary glands were collected on PNDs 30 and 120, processed for western blot analysis and double immunofluorescence staining for proliferating cell nuclear antigen and progesterone receptor or estrogen receptor. MnPP increased the percentage of HR+ mammary epithelial cells coexpressing proliferating cell nuclear antigen relative to normally developed controls at PND 30. This correlated with increased expression of estrogen receptor-regulated proteins in MnPP mammary glands relative to controls at PND 30, including FOXA1, AREG, and c-Myc. Conversely, at PND 120 relative to PND 30, proliferating HR+ cells remained chronically elevated in MnPP mammary glands at PND 120, which coincided with decreased expression of cell-cycle regulator, p27, and increased expression of progesterone receptor-regulated markers, EREG and sp1. Collectively, these results suggest early puberty alters steroidal regulation of classic proliferative mechanisms in the prepubertal gland with increased prevalence of high-risk proliferating HR+ cells.

Lymphatic transport in anti-tumor immunity and metastasis

Although lymphatic vessels (LVs) are present in many tumors, their importance in cancer has long been underestimated. In contrast to the well-studied tumor-associated blood vessels, LVs were previously considered to function as passive conduits for tumor metastasis. However, emerging evidence over the last two decades has shed light on their critical role in locally shaping the tumor microenvironment (TME). Here we review the involvement of LVs in tumor progression, metastasis, and modulation of anti-tumor immune response.

Brd7 loss reawakens dormant metastasis initiating cells in lung by forging an immunosuppressive niche

Metastasis in cancer is influenced by epigenetic factors. Using an in vivo screen, we demonstrate that several subunits of the polybromo-associated BAF (PBAF) chromatin remodeling complex, particularly Brd7, are required for maintaining breast cancer metastatic dormancy in the lungs of female mice. Brd7 loss induces metastatic reawakening, along with modifications in epigenomic landscapes and upregulated oncogenic signaling. Breast cancer cells harboring Brd7 inactivation also reprogram the surrounding immune microenvironment by downregulating MHC-1 expression and promoting a pro-metastatic cytokine profile. Flow cytometric and single-cell analyses reveal increased levels of pro-tumorigenic inflammatory and transitional neutrophils, CD8+ exhausted T cells, and CD4+ stress response T cells in lungs from female mice harboring Brd7-deficient metastases. Finally, attenuating this immunosuppressive milieu by neutrophil depletion, neutrophil extracellular trap (NET) inhibition, or immune checkpoint therapy abrogates metastatic outgrowth. These findings implicate Brd7 and PBAF in triggering metastatic outgrowth in cancer, pointing to targetable underlying mechanisms involving specific immune cell compartments.

Understanding metastasis mixed-treatment responses through genomic analyses

Early-stage and metastatic breast cancers (MBC) can exhibit genomic heterogeneity, even within the same individual. Response to therapy in metastatic breast cancer patients with multiple metastases can also be heterogeneous, with different degrees of responsiveness to the same drug(s) across metastatic sites, termed "mixed response," within the same patient. Whether this treatment response variability is influenced by factors such as intrinsic tumor characteristics of metastatic lesions and/or the microenvironment is unknown. Through genomic analysis of multiple metastases from the same patient, assayed in 6 different patients who had exhibited mixed response on imaging, we identified that higher regulatory T cells (T reg) and CDKN2A gene expression values correlate with non-response, while the KRAS gene, KRAS amplicon, and CD8T cells were associated with response in individual metastases. These genomic features may explain mixed clinical responses and provide valuable insights into intrapatient variations in treatment sensitivity.

Loss of SGK1 supports metastatic colonization in hepatocellular carcinoma by promoting resistance to T cell-mediated immunity

BACKGROUND & AIMS

Immune evasion by tumor cells is a principal obstacle to effectively targeting metastasis in hepatocellular carcinoma (HCC). However, the specific molecular mechanisms facilitating immune escape during metastatic seeding are not fully elucidated.

METHODS

Utilizing in vivo CRISPR library screening in murine HCC metastasis models under conditions of both intact and depleted T-cell immunity, we identified genes critical to tumor immune evasion during metastatic colonization and investigated intrinsic mechanisms using several experimental approaches.

RESULTS

Our screens identified Sgk1 as an essential suppressor of metastatic colonization under T-cell immunosurveillance. Sgk1-deficient tumor cells displayed significantly enhanced metastatic capacity in the presence of CD8+ T cells, underscoring the role of Sgk1 in regulating immune escape. Clinical analyses corroborated these findings, showing markedly lower SGK1 expression in circulating tumor cells and metastatic lesions relative to matched primary tumors in patients with HCC, with low SGK1 expression associating with compromised T-cell function and poorer clinical outcomes. Mechanistically, Sgk1 inactivation in tumor cells attenuated CD8+ T cell-mediated, RIPK1-dependent necroptosis - a cell death pathway essential for cytotoxic T cell-mediated restriction of metastasis. Loss of Sgk1 consequently enabled tumor cells to circumvent T cell-induced cytotoxicity, thereby promoting metastatic colonization. Furthermore, the outgrowth of Sgk1-deficient metastatic cells induced a microenvironmental shift toward terminal T-cell exhaustion, establishing conditions conducive to sustained immune evasion.

CONCLUSIONS

These findings establish SGK1 as a crucial regulator of immune-mediated control over metastatic growth in HCC. SGK1 expression in metastatic lesions may serve as a predictive biomarker for response to immune checkpoint inhibitors, presenting new avenues for therapeutic intervention to overcome immune resistance in metastatic HCC.

IMPACT AND IMPLICATIONS

Despite metastasis being a common occurrence and lethal determinant in cancers, the mechanism underlying tumor immune evasion during metastatic seeding is unclear. Our study reveals that loss of Sgk1 confers metastatic tumor cells with a survival advantage by abrogating CD8+ T cell-induced RIPK1-dependent necroptosis. Growth of Sgk1-silenced metastasis led to infiltration of terminally exhausted CD8+ T cells, which could be reversed by immune checkpoint inhibitors administered at an early stage of metastatic seeding. These findings provide valuable insights into potential therapeutic strategies targeting resistance to T-cell immunity in cancer metastasis.

Inosine monophosphate dehydrogenase 2 (IMPDH2) modulates response to therapy and chemo-resistance in triple negative breast cancer

Triple negative breast cancer (TNBC) is one of the deadliest subtypes of breast cancer, whose high frequency of relapse is often due to resistance to chemotherapy. Here, we identify inosine monophosphate dehydrogenase 2 (IMPDH2) as a contributor to doxorubicin resistance, in multiple TNBC models. Analysis of publicly available datasets reveals elevated IMPDH2 expression to associate with worse overall TNBC prognosis in the clinic, including lower recurrence-free survival post adjuvant/neoadjuvant therapy. Importantly, both genetic depletion and pharmacological inhibition of IMPDH2 leads to reduction of pro-tumorigenic phenotypes in multiple doxorubicin-resistant TNBC models, both in vitro and in vivo. Overall, we propose IMPDH2 as a novel vulnerability that could be leveraged therapeutically to suppress and/or prevent the growth of chemo-resistant lesions.

Pan-cancer drivers of metastasis

Metastasis remains a leading cause of cancer-related mortality, irrespective of the primary tumour origin. However, the core gene regulatory program governing distinct stages of metastasis across cancers remains poorly understood. We investigate this through single-cell transcriptome analysis encompassing over two hundred patients with metastatic and non-metastatic tumours across six cancer types. Our analysis revealed a prognostic core gene signature that provides insights into the intricate cellular dynamics and gene regulatory networks driving metastasis progression at the pan-cancer and single-cell level. Notably, the dissection of transcription factor networks active across different stages of metastasis, combined with functional perturbation, identified SP1 and KLF5 as key regulators, acting as drivers and suppressors of metastasis, respectively, at critical steps of this transition across multiple cancer types. Through in vivo and in vitro loss of function of SP1 in cancer cells, we revealed its role in driving cancer cell survival, invasive growth, and metastatic colonisation. Furthermore, tumour cells and the microenvironment increasingly engage in communication through WNT signalling as metastasis progresses, driven by SP1. Further validating these observations, a drug repurposing analysis identified distinct FDA-approved drugs with anti-metastasis properties, including inhibitors of WNT signalling across various cancers.

Quantitative Systems Pharmacology Modeling in Immuno-Oncology: Hypothesis Testing, Dose Optimization, and Efficacy Prediction

Despite an increasing number of clinical trials, cancer is one of the leading causes of death worldwide in the past decade. Among all complex diseases, clinical trials in oncology have among the lowest success rates, in part due to the high intra- and inter-tumoral heterogeneity. There are more than a thousand cancer drugs and treatment combinations being investigated in ongoing clinical trials for various cancer subtypes, germline mutations, metastasis, etc. Particularly, treatments relying on the (re)activation of the immune system have become increasingly present in the clinical trial pipeline. However, the complexities of the immune response and cancer-immune interactions pose a challenge to the development of these therapies. Quantitative systems pharmacology (QSP), as a computational approach to predict tumor response to treatments of interest, can be used to conduct in silico clinical trials with virtual patients (and emergent use of digital twins) in place of real patients, thus lowering the time and cost of clinical trials. In line with improved mechanistic understanding of the human immune system and promising results from recent cancer immunotherapy, QSP models can play critical roles in model-informed drug development in immuno-oncology. In this chapter, we discuss how QSP models were designed to serve different study objectives, including hypothesis testing, dose optimization, and efficacy prediction, via case studies in immuno-oncology.

Genomic predictors of radiation response: recent progress towards personalized radiotherapy for brain metastases

Radiotherapy remains a key treatment modality for both primary and metastatic brain tumors. Significant technological advances in precision radiotherapy, such as stereotactic radiosurgery and intensity-modulated radiotherapy, have contributed to improved clinical outcomes. Notably, however, molecular genetics is not yet widely used to inform brain radiotherapy treatment. By comparison, genetic testing now plays a significant role in guiding targeted therapies and immunotherapies, particularly for brain metastases (BM) of lung cancer, breast cancer, and melanoma. Given increasing evidence of the importance of tumor genetics to radiation response, this may represent a currently under-utilized means of enhancing treatment outcomes. In addition, recent studies have shown potentially actionable mutations in BM which are not present in the primary tumor. Overall, this suggests that further investigation into the pathways mediating radiation response variability is warranted. Here, we provide an overview of key mechanisms implicated in BM radiation resistance, including intrinsic and acquired resistance and intratumoral heterogeneity. We then discuss advances in tumor sampling methods, such as a collection of cell-free DNA and RNA, as well as progress in genomic analysis. We further consider how these tools may be applied to provide personalized radiotherapy for BM, including patient stratification, detection of radiotoxicity, and use of radiosensitization agents. In addition, we describe recent developments in preclinical models of BM and consider their relevance to investigating radiation response. Given the increase in clinical trials evaluating the combination of radiotherapy and targeted therapies, as well as the rising incidence of BM, it is essential to develop genomically informed approaches to enhance radiation response.

Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction

Cancer transcriptional patterns reflect both unique features and shared hallmarks across diverse cancer types, but whether differences in these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that these shared transcriptomic signatures reflect repurposed versions of functional tasks performed by normal tissues. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2- breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable but is hindered by the limited performance of existing biomarkers. Here, we leveraged in silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We evaluated and quantified the performance of 90 biomarker candidates, including various cellular and molecular species, at different cutoffs by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pretreatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.

A multi-modal single-cell and spatial expression map of metastatic breast cancer biopsies across clinicopathological features

Although metastatic disease is the leading cause of cancer-related deaths, its tumor microenvironment remains poorly characterized due to technical and biospecimen limitations. In this study, we assembled a multi-modal spatial and cellular map of 67 tumor biopsies from 60 patients with metastatic breast cancer across diverse clinicopathological features and nine anatomic sites with detailed clinical annotations. We combined single-cell or single-nucleus RNA sequencing for all biopsies with a panel of four spatial expression assays (Slide-seq, MERFISH, ExSeq and CODEX) and H&E staining of consecutive serial sections from up to 15 of these biopsies. We leveraged the coupled measurements to provide reference points for the utility and integration of different experimental techniques and used them to assess variability in cell type composition and expression as well as emerging spatial expression characteristics across clinicopathological and methodological diversity. Finally, we assessed spatial expression and co-localization features of macrophage populations, characterized three distinct spatial phenotypes of epithelial-to-mesenchymal transition and identified expression programs associated with local T cell infiltration versus exclusion, showcasing the potential of clinically relevant discovery in such maps.

Mediator Subunit Med4 Enforces Metastatic Dormancy in Breast Cancer

Long term survival of breast cancer patients is limited due to recurrence from metastatic dormant cancer cells. However, the mechanisms by which these dormant breast cancer cells survive and awaken remain poorly understood. Our unbiased genome-scale genetic screen in mice identified Med4 as a novel cancer-cell intrinsic gatekeeper in metastatic reactivation. MED4 haploinsufficiency is prevalent in metastatic breast cancer patients and correlates with poorer prognosis. Syngeneic xenograft models revealed that Med4 enforces breast cancer dormancy. Contrary to the canonical function of the Mediator complex in activating gene expression, Med4 maintains 3D chromatin compaction and enhancer landscape, by preventing enhancer priming or activation through the suppression of H3K4me1 deposition. Med4 haploinsufficiency disrupts enhancer poise and reprograms the enhancer dynamics to facilitate extracellular matrix (ECM) gene expression and integrin-mediated mechano-transduction, driving metastatic growth. Our findings establish Med4 as a key regulator of cellular dormancy and a potential biomarker for high-risk metastatic relapse.

USP1-mediated deubiquitination of KDM1A promotes the malignant progression of triple-negative breast cancer

Previous research has indicated the highly expressed lysine-specific histone demethylase 1A (KDM1A) in several human malignancies, including triple-negative breast cancer (TNBC). However, its detailed mechanisms in TNBC development remain poorly understood. The mRNA levels of KDM1A and Yin Yang 1 (YY1) were determined by RT-qPCR analysis. Western blot was performed to measure KDM1A and ubiquitin-specific protease 1 (USP1) protein expression. Cell proliferation, apoptosis, invasion, migration and stemness were evaluated by MTT assay, EdU assay, flow cytometry, transwell invasion assay, wound-healing assay and sphere-formation assay, respectively. ChIP and dual-luciferase reporter assays were conducted to determine the relationship between YY1 and KDM1A. Xenograft tumor experiment and IHC were carried out to investigate the roles of USP1 and KDM1A in TNBC development in vivo. The highly expressed KDM1A was demonstrated in TNBC tissues and cells, and KDM1A knockdown significantly promoted cell apoptosis, and hampered cell proliferation, invasion, migration, and stemness in TNBC cells. USP1 could increase the stability of KDM1A via deubiquitination, and USP1 depletion restrained the progression of TNBC cells through decreasing KDM1A expression. Moreover, YY1 transcriptionally activated KDM1A expression by directly binding to its promoter in TNBC cells. Additionally, USP1 inhibition reduced KDM1A expression to suppress tumor growth in TNBC mice in vivo. In conclusion, YY1 upregulation increased KDM1A expression via transcriptional activation. USP1 stabilized KDM1A through deubiquitination to promote TNBC progression.

Associations amongst genes, molecules, cells, and organs in breast cancer metastasis

This paper is a cross fertilization of ideas about the importance of molecular aspects of breast cancer metastasis by basic scientists, a pathologist, and clinical oncologists at the Henry Ford Health symposium. We address four major topics: (i) the complex roles of lymphatic endothelial cells and the molecules that stimulate them to enhance lymph node and systemic metastasis and influence the anti-tumor immunity that might inhibit metastasis; (ii) the interaction of molecules and cells when breast cancer spreads to bone, and how bone metastases may themselves spread to internal viscera; (iii) how molecular expression and morphologic subtypes of breast cancer assist clinicians in determining which patients to treat with more or less aggressive therapies; (iv) how the outcomes of patients with oligometastases in breast cancer are different from those with multiple metastases and how that could justify the aggressive treatment of these patients with the hope of cure.

LncRNA ZFHX4-AS1 as a novel biomarker in adrenocortical carcinoma

Background

Adrenocortical carcinoma (ACC) is a rare and highly aggressive malignant tumor. Currently, there is a lack of reliable prognostic markers in clinical practice. Extensive research has shown that long non-coding RNA (lncRNA) are critical factors in the initiation and progression of cancer, closely associated with early diagnosis and prognosis. Previous studies have identified that ZFHX4 antisense RNA 1 (ZFHX4-AS1) is aberrantly expressed in various cancers and is associated with poor outcomes. This study investigates whether ZFHX4-AS1 affects the prognosis of ACC patients and, if so, the potential mechanisms involved.

Methods

In this study, utilizing four multi-center cohorts from The Cancer Genome Atlas (TCGA) program and Gene Expression Omnibus (GEO), we validated the prognostic capability of ZFHX4-AS1 in ACC patients through Kaplan-Meier survival analysis, cox regression models, and nomograms. Then, we explored the biological functions of ZFHX4-AS1 using gene set enrichment analysis (GSEA), competing endogenous RNA (ceRNA) networks, and analyses of somatic mutations and copy number variation (CNV). Finally, in vitro experiments were conducted to further validate the impact of ZFHX4-AS1 on proliferation and migration capabilities of ACC cell lines.

Results

Survival analysis indicated that patients in the high ZFHX4-AS1 expression group of ACC had worse prognosis. Cox regression analyses suggested that ZFHX4-AS1 levels were independent risk factors for prognosis. Subsequently, we constructed nomograms based on clinical features and ZFHX4-AS1 levels, demonstrating good predictive performance under the time-dependent receiver operating characteristic (ROC) curve. Analysis based on somatic mutations and CNV revealed that CTNNB1 and 9p21.3-Del drove the expression of ZFHX4-AS1. Cell Counting Kit-8 (CCK-8), colony formation, and Transwell assays confirmed that knockdown of ZFHX4-AS1 inhibited proliferation and migration of ACC cells.

Conclusions

This study demonstrates that ZFHX4-AS1 has a reliable predictive value for the prognosis of ACC patients and is a promising biomarker.

From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling

Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed to generate virtual patient populations using mechanistic models, there are limited number of applications in immuno-oncology research. Furthermore, due to the stricter requirements of digital twins, they are often generated in a study-specific manner with models customized to particular clinical settings (e.g., treatment, cancer, and data types). Here, we discuss the challenges for virtual patient generation in immuno-oncology with our most recent experiences, initiatives to develop digital twins, and how research on these two concepts can inform each other.

The endogenous association among MMP2/miR-1248/Circ_0087558/miR-643/ MAP2K6 axis can contribute to brain metastasis in basal-like subtype of breast cancer

Brain metastasis in basal-like breast cancer poses a significant challenge in cancer management due to its aggressive nature and limited treatment options. This study conducted a comprehensive analysis to explore the potential role of circular RNAs (circRNAs) as members of endogenous networks in developing breast cancer brain metastasis. Here, we utilized RNA sequencing data from primary breast cancer and brain metastasis tissue with basal-like subtype (n = 11). After quality controlling and preprocessing of fastq files, gene expression of mRNA and circRNAs were extracted from matched samples and normalized. Then, we employed the weighted gene co-expression network analysis approach to identify brain metastasis-associated circRNA modules ( S p e a r m a n Correlation > 0.5 , P - value < 0.05 ). Moreover, we found five protein-coding genes of PHLDA1, SLC12A2, MMP2, RGP1, and MAP2K6, significantly upregulated in brain metastatic tissues compared to primary breast cancer ( FDR < 0.05 ). These genes were enriched in the "GnRH signaling pathway" and "Fluid shear stress and atherosclerosis" pathways ( FDR < 0.05 ). Next, to explore the potential interactions between circRNAs and protein-coding genes, we reconstructed a competing endogenous RNA (ceRNA) network using mutual miRNAs between the circRNA module and upregulated mRNAs. Notably, we could detect two axes of circ_0087558/miR-604/MMP2 and MMP2/miR-1248/Circ_0087558/miR-643/MAP2K6 in ceRNA network. In conclusion, the identified circRNA-miRNA-mRNA axes might be therapeutic targets or diagnostic biomarkers for this challenging subtype of breast cancer. However, due to the small number of samples, further experimental validations are essential.

Loss of Kmt2c or Kmt2d drives brain metastasis via KDM6A-dependent upregulation of MMP3

KMT2C and KMT2D, encoding histone H3 lysine 4 methyltransferases, are among the most commonly mutated genes in triple-negative breast cancer (TNBC). However, how these mutations may shape epigenomic and transcriptomic landscapes to promote tumorigenesis is largely unknown. Here we describe that deletion of Kmt2c or Kmt2d in non-metastatic murine models of TNBC drives metastasis, especially to the brain. Global chromatin profiling and chromatin immunoprecipitation followed by sequencing revealed altered H3K4me1, H3K27ac and H3K27me3 chromatin marks in knockout cells and demonstrated enhanced binding of the H3K27me3 lysine demethylase KDM6A, which significantly correlated with gene expression. We identified Mmp3 as being commonly upregulated via epigenetic mechanisms in both knockout models. Consistent with these findings, samples from patients with KMT2C-mutant TNBC have higher MMP3 levels. Downregulation or pharmacological inhibition of KDM6A diminished Mmp3 upregulation induced by the loss of histone-lysine N-methyltransferase 2 (KMT2) and prevented brain metastasis similar to direct downregulation of Mmp3. Taken together, we identified the KDM6A-matrix metalloproteinase 3 axis as a key mediator of KMT2C/D loss-driven metastasis in TNBC.

An essential gene signature of breast cancer metastasis reveals targetable pathways

BACKGROUND

The differential gene expression profile of metastatic versus primary breast tumors represents an avenue for discovering new or underappreciated pathways underscoring processes of metastasis. However, as tumor biopsy samples are a mixture of cancer and non-cancer cells, most differentially expressed genes in metastases would represent confounders involving sample biopsy site rather than cancer cell biology.

METHODS

By paired analysis, we defined a top set of differentially expressed genes in breast cancer metastasis versus primary tumors using an RNA-sequencing dataset of 152 patients from The Breast International Group Aiming to Understand the Molecular Aberrations dataset (BIG-AURORA). To filter the genes higher in metastasis for genes essential for breast cancer proliferation, we incorporated CRISPR-based data from breast cancer cell lines.

RESULTS

A significant fraction of genes with higher expression in metastasis versus paired primary were essential by CRISPR. These 264 genes represented an essential signature of breast cancer metastasis. In contrast, nonessential metastasis genes largely involved tumor biopsy site. The essential signature predicted breast cancer patient outcome based on primary tumor expression patterns. Pathways underlying the essential signature included proteasome degradation, the electron transport chain, oxidative phosphorylation, and cancer metabolic reprogramming. Transcription factors MYC, MAX, HDAC3, and HCFC1 each bound significant fractions of essential genes.

CONCLUSIONS

Associations involving the essential gene signature of breast cancer metastasis indicate true biological changes intrinsic to cancer cells, with important implications for applying existing therapies or developing alternate therapeutic approaches.

Research autopsy programmes in oncology: shared experience from 14 centres across the world

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable, but is hindered by the limited performance of existing biomarkers. Here, we leveraged in-silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We tested 90 biomarker candidates, including various cellular and molecular species, by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pre-treatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.

Digital droplet PCR analysis of organoids generated from mouse mammary tumors demonstrates proof-of-concept capture of tumor heterogeneity

Breast cancer metastases exhibit many different genetic alterations, including copy number amplifications (CNA). CNA are genetic alterations that are increasingly becoming relevant to breast oncology clinical practice. Here we identify CNA in metastatic breast tumor samples using publicly available datasets and characterize their expression and function using a metastatic mouse model of breast cancer. Our findings demonstrate that our organoid generation can be implemented to study clinically relevant features that reflect the genetic heterogeneity of individual tumors.

Predictability of B cell clonal persistence and immunosurveillance in breast cancer

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Comprehensive genomic profiling to identify actionable alterations for breast cancer brain metastases in the Chinese population

BACKGROUND

Breast cancer brain metastasis (BCBM) is a crucial issue in the treatment of breast cancer and is associated with poor prognosis. Therefore, novel therapeutic targets are urgently needed in clinical practice. In this study, we aimed to identify potential actionable targets in brain metastases (BMs) utilising the FoundationOne® CDx (F1CDx).

PATIENTS AND METHODS

Formalin-fixed paraffin-embedded archived specimens including 16 primary breast tumours (PTs), 49 BCBMs and 7 extracranial metastases (ECMs) from 54 patients who underwent surgery for BCBM were tested using F1CDx. Tumour-infiltrated lymphocytes (TILs) of BMs were also tested using haematoxylin-eosin staining.

RESULTS

The median tumour mutational burden (TMB) and TILs in BMs were 5.0 (range 0-29) mut/Mb and 1.0% (range 0%-5.0%), respectively. High TMB (≥10 mut/Mb) was detected in four cases (8%). Genomic alterations (GAs) were detected in all samples. The top-ranked somatic mutations in BMs were TP53 (82%), PIK3CA (35%), MLL2 (22%), BRCA2 (14%) and ATM (14%) and the most prevalent copy number alterations were ERBB2 (64%), RAD21 (36%), CCND1 (32%), FGF19 (30%) and FGF3 (30%). The most prevalent GAs were relatively consistent between paired PTs and BMs. Actionable GAs were detected in 94% of all BMs. Consistent rate in actionable GAs was 38% (6/16) between paired PTs/ECMs and BMs. Compared to matched PTs/ECMs, additional actionable GAs (BRAF, FGFR1, PTEN, KIT and CCND1) were discovered in 31% (5/16) of the BMs.

CONCLUSIONS

TMB and TILs were relatively low in BCBMs. Comparable consistency in actionable GAs was identified between BCBMs and matched PTs/ECMs. It was, therefore, logical to carry out genomic testing for BCBMs to identify potential new therapeutic targets when BCBM specimens were available, as ∼31% of samples carried additional actionable GAs.

Stress in the metastatic journey - the role of cell communication and clustering in breast cancer progression and treatment resistance

Breast cancer stands as the most prevalent malignancy afflicting women. Despite significant advancements in its diagnosis and treatment, breast cancer metastasis continues to be a leading cause of mortality among women. To metastasize, cancer cells face numerous challenges: breaking away from the primary tumor, surviving in the circulation, establishing in a distant location, evading immune detection and, finally, thriving to initiate a new tumor. Each of these sequential steps requires cancer cells to adapt to a myriad of stressors and develop survival mechanisms. In addition, most patients with breast cancer undergo surgical removal of their primary tumor and have various therapeutic interventions designed to eradicate cancer cells. Despite this plethora of attacks and stresses, certain cancer cells not only manage to persist but also proliferate robustly, giving rise to substantial tumors that frequently culminate in the patient's demise. To enhance patient outcomes, there is an imperative need for a deeper understanding of the molecular and cellular mechanisms that empower cancer cells to not only survive but also expand. Herein, we delve into the intrinsic stresses that cancer cells encounter throughout the metastatic journey and the additional stresses induced by therapeutic interventions. We focus on elucidating the remarkable strategies adopted by cancer cells, such as cell-cell clustering and intricate cell-cell communication mechanisms, to ensure their survival.

Drivers of cancer metastasis - Arise early and remain present

Cancer and its metastases arise from mutations of genes, drivers that promote a tumor's growth. Analyses of driver events provide insights into cancer cell history and may lead to a better understanding of oncogenesis. We reviewed 27 metastatic research studies, including pan-cancer studies, individual cancer studies, and phylogenetic analyses, and summarized our current knowledge of metastatic drivers. All of the analyzed studies had a high level of consistency of driver mutations between primary tumors and metastasis, indicating that most drivers appear early in cancer progression and are maintained in metastatic cells. Additionally, we reviewed data from around 50,000 metastatic cancer patients and compiled a list of genes altered in metastatic lesions. We performed Gene Ontology analysis and confirmed that the most significantly enriched processes in metastatic lesions were the epigenetic regulation of gene expression, signal transduction, cell cycle, programmed cell death, DNA damage, hypoxia and EMT. In this review, we explore the most recent discoveries regarding genetic factors in the advancement of cancer, specifically those that drive metastasis.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

Genetic Intratumor Heterogeneity Remodels the Immune Microenvironment and Induces Immune Evasion in Brain Metastasis of Lung Cancer

INTRODUCTION

Brain metastasis, with the highest incidence in patients with lung cancer, significantly worsens prognosis and poses challenges to clinical management. To date, how brain metastasis evades immune elimination remains unknown.

METHODS

Whole-exome sequencing and RNA sequencing were performed on 30 matched brain metastasis, primary lung adenocarcinoma, and normal tissues. Data from The Cancer Genome Atlas primary lung adenocarcinoma cohort, including multiplex immunofluorescence, were used to support the findings of bioinformatics analysis.

RESULTS

Our study highlights the key role of intratumor heterogeneity of genomic alterations in the metastasis process, mainly caused by homologous recombination deficiency or other somatic copy number alteration-associated mutation mechanisms, leading to increased genomic instability and genomic complexity. We further proposed a selection model of brain metastatic evolution in which intratumor heterogeneity drives immune remodeling, leading to immune escape through different mechanisms under local immune pressure.

CONCLUSIONS

Our findings provide novel insights into the metastatic process and immune escape mechanisms of brain metastasis and pave the way for precise immunotherapeutic strategies for patients with lung cancer with brain metastasis.

Thinking (Metastasis) outside the (Primary Tumor) Box

The metastasis of tumor cells into vital organs is a major cause of death from diverse types of malignancies [...].

Application of Machine Learning in Predicting Hepatic Metastasis or Primary Site in Gastroenteropancreatic Neuroendocrine Tumors

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) account for 80% of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). GEP-NETs are well-differentiated tumors, highly heterogeneous in biology and origin, and are often diagnosed at the metastatic stage. Diagnosis is commonly through clinical symptoms, histopathology, and PET-CT imaging, while molecular markers for metastasis and the primary site are unknown. Here, we report the identification of multi-gene signatures for hepatic metastasis and primary sites through analyses on RNA-SEQ datasets of pancreatic and small intestinal NETs tissue samples. Relevant gene features, identified from the normalized RNA-SEQ data using the mRMRe algorithm, were used to develop seven Machine Learning models (LDA, RF, CART, k-NN, SVM, XGBOOST, GBM). Two multi-gene random forest (RF) models classified primary and metastatic samples with 100% accuracy in training and test cohorts and >90% accuracy in an independent validation cohort. Similarly, three multi-gene RF models identified the pancreas or small intestine as the primary site with 100% accuracy in training and test cohorts, and >95% accuracy in an independent cohort. Multi-label models for concurrent prediction of hepatic metastasis and primary site returned >98.42% and >87.42% accuracies on training and test cohorts, respectively. A robust molecular signature to predict liver metastasis or the primary site for GEP-NETs is reported for the first time and could complement the clinical management of GEP-NETs.

Integrated Multimodal Analyses of DNA Damage Response and Immune Markers as Predictors of Response in Metastatic Triple-Negative Breast Cancer in the TNT Trial (NCT00532727)

PURPOSE

The TNT trial (NCT00532727) showed no evidence of carboplatin superiority over docetaxel in metastatic triple-negative breast cancer (mTNBC), but carboplatin benefit was observed in the germline BRCA1/2 mutation subgroup. Broader response-predictive biomarkers are needed. We explored the predictive ability of DNA damage response (DDR) and immune markers.

EXPERIMENTAL DESIGN

Tumor-infiltrating lymphocytes were evaluated for 222 of 376 patients. Primary tumors (PT) from 186 TNT participants (13 matched recurrences) were profiled using total RNA sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective response rate (ORR) and progression-free survival (PFS). Conditional inference forest clustering was applied to integrate multimodal data. The biology of subgroups was characterized by 693 gene expression modules and other markers.

RESULTS

Transcriptional DDR-related biomarkers were not predictive of ORR to either treatment overall. Changes from PT to recurrence were demonstrated; in chemotherapy-naïve patients, transcriptional DDR markers separated carboplatin responders from nonresponders (P values = 0.017; 0.046). High immune infiltration was associated with docetaxel ORR (interaction P values < 0.05). Six subgroups were identified; the immune-enriched cluster had preferential docetaxel response [62.5% (D) vs. 29.4% (C); P = 0.016]. The immune-depleted cluster had preferential carboplatin response [8.0% (D) vs. 40.0% (C); P = 0.011]. DDR-related subgroups were too small to assess ORR.

CONCLUSIONS

High immune features predict docetaxel response, and high DDR signature scores predict carboplatin response in treatment-naïve mTNBC. Integrating multimodal DDR and immune-related markers identifies subgroups with differential treatment sensitivity. Treatment options for patients with immune-low and DDR-proficient tumors remains an outstanding need. Caution is needed using PT-derived transcriptional signatures to direct treatment in mTNBC, particularly DDR-related markers following prior chemotherapy.

Implications of tumour heterogeneity on cancer evolution and therapy resistance: lessons from breast cancer

Tumour heterogeneity is pervasive amongst many cancers and leads to disease progression, and therapy resistance. In this review, using breast cancer as an exemplar, we focus on the recent advances in understanding the interplay between tumour cells and their microenvironment using single cell sequencing and digital spatial profiling technologies. Further, we discuss the utility of lineage tracing methodologies in pre-clinical models of breast cancer, and how these are being used to unravel new therapeutic vulnerabilities and reveal biomarkers of breast cancer progression. © 2023 The Pathological Society of Great Britain and Ireland.

Distinct shared and compartment-enriched oncogenic networks drive primary versus metastatic breast cancer

Metastatic breast-cancer is a major cause of death in women worldwide, yet the relationship between oncogenic drivers that promote metastatic versus primary cancer is still contentious. To elucidate this relationship in treatment-naive animals, we hereby describe mammary-specific transposon-mutagenesis screens in female mice together with loss-of-function Rb, which is frequently inactivated in breast-cancer. We report gene-centric common insertion-sites (gCIS) that are enriched in primary-tumors, in metastases or shared by both compartments. Shared-gCIS comprise a major MET-RAS network, whereas metastasis-gCIS form three additional hubs: Rho-signaling, Ubiquitination and RNA-processing. Pathway analysis of four clinical cohorts with paired primary-tumors and metastases reveals similar organization in human breast-cancer with subtype-specific shared-drivers (e.g. RB1-loss, TP53-loss, high MET, RAS, ER), primary-enriched (EGFR, TGFβ and STAT3) and metastasis-enriched (RHO, PI3K) oncogenic signaling. Inhibitors of RB1-deficiency or MET plus RHO-signaling cooperate to block cell migration and drive tumor cell-death. Thus, targeting shared- and metastasis- but not primary-enriched derivers offers a rational avenue to prevent metastatic breast-cancer.

Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer

Metabolic reprogramming to sustain immortality is a hallmark of cancer and glycolysis is an important way to attain this. Thus, we investigate the association of glycolysis and associated pathways in the survival of breast cancer. A total of 5,176 breast cancer patients from multiple independent cohorts were analyzed. We determined the glycolytic signaling score by the degree of enrichment by Gene Set Variant Analysis and the median was used to divide each cohort into high vs low score groups. Glycolysis high breast cancer significantly enriched the hallmark cell proliferation-related gene sets (E2F targets, G2M checkpoint, and MYC targets v1 and v2) and was associated with high MKI67 expression. In all cohorts, triple-negative breast cancer (TNBC) was associated with the highest glycolysis score. It was found that in TNBC, glycolysis high breast cancer was associated with worse survival but in ER-positive/HER2-negative breast cancer this was not observed consistently. The glycolysis high TNBC enriched multiple pro-cancerous gene sets and was infiltrated with a low level of B-cells and anti-cancerous immune cells, and significantly associated with a decreased level of cytolytic activity. It was also observed that the glycolysis was higher in the metastatic sites than in the primary breast cancer and the survival was not affected by the metastatic sites. In conclusion, accelerated glycolysis is associated with cancer cell proliferation and worse survival in TNBC.

A transcriptome-informed QSP model of metastatic triple-negative breast cancer identifies predictive biomarkers for PD-1 inhibition

Triple-negative breast cancer (TNBC), a highly metastatic breast cancer subtype, has limited treatment options. While a small number of patients attain clinical benefit with single-agent checkpoint inhibitors, identifying these patients before the therapy remains challenging. Here, we developed a transcriptome-informed quantitative systems pharmacology model of metastatic TNBC by integrating heterogenous metastatic tumors. In silico clinical trial with an anti-PD-1 drug, pembrolizumab, predicted that several features, such as the density of antigen-presenting cells, the fraction of cytotoxic T cells in lymph nodes, and the richness of cancer clones in tumors, could serve individually as biomarkers but had a higher predictive power as combinations of two biomarkers. We showed that PD-1 inhibition neither consistently enhanced all antitumorigenic factors nor suppressed all protumorigenic factors but ultimately reduced the tumor carrying capacity. Collectively, our predictions suggest several candidate biomarkers that might effectively predict the response to pembrolizumab monotherapy and potential therapeutic targets to develop treatment strategies for metastatic TNBC.

Insights into the metastatic cascade through research autopsies

Metastasis is a complex process and the leading cause of cancer-related death globally. Recent studies have demonstrated that genomic sequencing data from paired primary and metastatic tumours can be used to trace the evolutionary origins of cells responsible for metastasis. This approach has yielded new insights into the genomic alterations that engender metastatic potential, and the mechanisms by which cancer spreads. Given that the reliability of these approaches is contingent upon how representative the samples are of primary and metastatic tumour heterogeneity, we review insights from studies that have reconstructed the evolution of metastasis within the context of their cohorts and designs. We discuss the role of research autopsies in achieving the comprehensive sampling necessary to advance the current understanding of metastasis.

Familial CCM Genes Might Not Be Main Drivers for Pathogenesis of Sporadic CCMs-Genetic Similarity between Cancers and Vascular Malformations

Cerebral cavernous malformations (CCMs) are abnormally dilated intracranial capillaries that form cerebrovascular lesions with a high risk of hemorrhagic stroke. Recently, several somatic "activating" gain-of-function (GOF) point mutations in PIK3CA (phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit p110α) were discovered as a dominant mutation in the lesions of sporadic forms of cerebral cavernous malformation (sCCM), raising the possibility that CCMs, like other types of vascular malformations, fall in the PIK3CA-related overgrowth spectrum (PROS). However, this possibility has been challenged with different interpretations. In this review, we will continue our efforts to expound the phenomenon of the coexistence of gain-of-function (GOF) point mutations in the PIK3CA gene and loss-of-function (LOF) mutations in CCM genes in the CCM lesions of sCCM and try to delineate the relationship between mutagenic events with CCM lesions in a temporospatial manner. Since GOF PIK3CA point mutations have been well studied in reproductive cancers, especially breast cancer as a driver oncogene, we will perform a comparative meta-analysis for GOF PIK3CA point mutations in an attempt to demonstrate the genetic similarities shared by both cancers and vascular anomalies.

Molecular landscape and emerging therapeutic strategies in breast cancer brain metastasis

Breast cancer (BC) is the most commonly diagnosed cancer worldwide. Advanced BC with brain metastasis (BM) is a major cause of mortality with no specific or effective treatment. Therefore, better knowledge of the cellular and molecular mechanisms underlying breast cancer brain metastasis (BCBM) is crucial for developing novel therapeutic strategies and improving clinical outcomes. In this review, we focused on the latest advances and discuss the contribution of the molecular subtype of BC, the brain microenvironment, exosomes, miRNAs/lncRNAs, and genetic background in BCBM. The blood–brain barrier and blood–tumor barrier create challenges to brain drug delivery, and we specifically review novel approaches to bypass these barriers. Furthermore, we discuss the potential application of immunotherapies and genetic editing techniques based on CRISPR/Cas9 technology in treating BCBM. Emerging techniques and research findings continuously shape our views of BCBM and contribute to improvements in precision therapies and clinical outcomes.

Molecular aspects of brain metastases in breast cancer

Brain metastases (BM) are a common and devastating manifestation of breast cancer (BC). BM are particularly frequent in the HER2-positive and triple-negative breast cancer phenotypes and usually occur following the metastatic spread to extracranial sites. Several genes mediating BM and biomarkers predicting their risk in BC have been reported in the past decade. These findings have advanced the understanding of BM pathobiology and paved the way for developing new therapeutic strategies but they still warrant a thorough clinical validation. Hence, a better understanding of the mechanistic aspects of BM and delineating the interactions of tumor cells with the brain microenvironment are of utmost importance. This review discusses the molecular basis of the metastatic cascade: the epithelial-mesenchymal transition, cancer, and tumor microenvironment interaction and intravasation, priming of the metastatic niche in the brain, and survival in the new site. We also outline the postulated mechanisms of BC cells' brain tropism. Finally, we discuss advances in the field of biomarkers (both tissue-based and liquid-based) that predict BM from BC.

Immunosuppressive reprogramming of neutrophils by lung mesenchymal cells promotes breast cancer metastasis

Neutrophils, the most abundant innate immune cells, function as crucial regulators of the adaptive immune system in diverse pathological conditions, including metastatic cancer. However, it remains largely unknown whether their immunomodulatory functions are intrinsic or acquired within the pathological tissue environment. Here, using mouse models of metastatic breast cancer in the lungs, we show that, although neutrophils isolated from bone marrow (BM) or blood are minimally immunosuppressive, lung-infiltrating neutrophils are robustly suppressive of both T cells and natural killer (NK) cells. We found that this tissue-specific immunosuppressive capacity of neutrophils exists in the steady state and is reinforced by tumor-associated inflammation. Acquisition of potent immunosuppression activity by lung-infiltrating neutrophils was endowed by the lung-resident stroma, specifically CD140a+ mesenchymal cells (MCs) and largely via prostaglandin-endoperoxide synthase 2 (PTGS2), the rate-limiting enzyme for prostaglandin E2 (PGE2) biosynthesis. MC-specific deletion of Ptgs2 or pharmacological inhibition of PGE2 receptors reversed lung neutrophil-mediated immunosuppression and mitigated lung metastasis of breast cancer in vivo. These lung stroma-targeting strategies substantially improved the therapeutic efficacy of adoptive T cell-based immunotherapy in treating metastatic disease in mice. Collectively, our results reveal that the immunoregulatory effects of neutrophils are induced by tissue-resident stroma and that targeting tissue-specific stromal factors represents an effective approach to boost tissue-resident immunity against metastatic disease.

lncRNA BREA2 promotes metastasis by disrupting the WWP2-mediated ubiquitination of Notch1

Notch has been implicated in human cancers and is a putative therapeutic target. However, the regulation of Notch activation in the nucleus remains largely uncharacterized. Therefore, characterizing the detailed mechanisms governing Notch degradation will identify attractive strategies for treating Notch-activated cancers. Here, we report that the long noncoding RNA (lncRNA) BREA2 drives breast cancer metastasis by stabilizing the Notch1 intracellular domain (NICD1). Moreover, we reveal WW domain containing E3 ubiquitin protein ligase 2 (WWP2) as an E3 ligase for NICD1 at K1821 and a suppressor of breast cancer metastasis. Mechanistically, BREA2 impairs WWP2-NICD1 complex formation and in turn stabilizes NICD1, leading to Notch signaling activation and lung metastasis. BREA2 loss sensitizes breast cancer cells to inhibition of Notch signaling and suppresses the growth of breast cancer patient-derived xenograft tumors, highlighting its therapeutic potential in breast cancer. Taken together, these results reveal the lncRNA BREA2 as a putative regulator of Notch signaling and an oncogenic player driving breast cancer metastasis.

Integrating multi-type aberrations from DNA and RNA through dynamic mapping gene space for subtype-specific breast cancer driver discovery

Driver event discovery is a crucial demand for breast cancer diagnosis and therapy. In particular, discovering subtype-specificity of drivers can prompt the personalized biomarker discovery and precision treatment of cancer patients. Still, most of the existing computational driver discovery studies mainly exploit the information from DNA aberrations and gene interactions. Notably, cancer driver events would occur due to not only DNA aberrations but also RNA alternations, but integrating multi-type aberrations from both DNA and RNA is still a challenging task for breast cancer drivers. On the one hand, the data formats of different aberration types also differ from each other, known as data format incompatibility. On the other hand, different types of aberrations demonstrate distinct patterns across samples, known as aberration type heterogeneity. To promote the integrated analysis of subtype-specific breast cancer drivers, we design a "splicing-and-fusing" framework to address the issues of data format incompatibility and aberration type heterogeneity simultaneously. To overcome the data format incompatibility, the "splicing-step" employs a knowledge graph structure to connect multi-type aberrations from the DNA and RNA data into a unified formation. To tackle the aberration type heterogeneity, the "fusing-step" adopts a dynamic mapping gene space integration approach to represent the multi-type information by vectorized profiles. The experiments also demonstrate the advantages of our approach in both the integration of multi-type aberrations from DNA and RNA and the discovery of subtype-specific breast cancer drivers. In summary, our "splicing-and-fusing" framework with knowledge graph connection and dynamic mapping gene space fusion of multi-type aberrations data from DNA and RNA can successfully discover potential breast cancer drivers with subtype-specificity indication.

Glycolysis-related lncRNA TMEM105 upregulates LDHA to facilitate breast cancer liver metastasis via sponging miR-1208

Increased glycolysis is one of the key metabolic hallmarks of cancer cells. However, the roles of lncRNAs in energy metabolism and cancer metastasis remain unclear. Here, the expression of TMEM105 associated with glycolysis was dramatically elevated from normal to breast cancer to breast cancer liver metastasis tissues, and the survival analysis revealed that high TMEM105 expression was related to poor survival, especially in patients with liver metastasis. Moreover, TMEM105 facilitated the glycolysis of breast cancer cells and induced cell invasion and breast cancer liver metastasis (BCLM). Mechanistically, TMEM105 regulated LDHA expression by sponging miR-1208, which further promoted cell glycolysis and BCLM. Importantly, glycolytic production of lactate enhanced TMEM105 expression in breast cancer cells by activating the SHH-MAZ signaling pathway. These findings suggested that the lactate-responsive TMEM105 acted as a miRNA sponge, inducing BCLM via a glycolysis-mediated positive feedback loop, which might be a rational target for the treatment of BCLM patients.

Organoid generation from mouse mammary tumors captures the genetic heterogeneity of clinically relevant copy number alterations

Breast cancer metastases exhibit many different genetic alterations, including copy number amplifications. Using publicly available datasets, we identify copy number amplifications in metastatic breast tumor samples and using our organoid-based metastasis assays, and we validate FGFR1 is amplified in collectively migrating organoids. Because the heterogeneity of breast tumors is increasingly becoming relevant to clinical practice, we demonstrate our organoid method captures genetic heterogeneity of individual tumors.