ZNF689 deficiency promotes intratumor heterogeneity and immunotherapy resistance in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive disease characterized by remarkable intratumor heterogeneity (ITH), which poses therapeutic challenges. However, the clinical relevance and key determinant of ITH in TNBC are poorly understood. Here, we comprehensively characterized ITH levels using multi-omics data across our center's cohort (n = 260), The Cancer Genome Atlas cohort (n = 134), and four immunotherapy-treated cohorts (n = 109). Our results revealed that high ITH was associated with poor patient survival and immunotherapy resistance. Importantly, we identified zinc finger protein 689 (ZNF689) deficiency as a crucial determinant of ITH formation. Mechanistically, the ZNF689-TRIM28 complex was found to directly bind to the promoter of long interspersed element-1 (LINE-1), inducing H3K9me3-mediated transcriptional silencing. ZNF689 deficiency reactivated LINE-1 retrotransposition to exacerbate genomic instability, which fostered ITH. Single-cell RNA sequencing, spatially resolved transcriptomics and flow cytometry analysis confirmed that ZNF689 deficiency-induced ITH inhibited antigen presentation and T-cell activation, conferring immunotherapy resistance. Pharmacological inhibition of LINE-1 significantly reduced ITH, enhanced antitumor immunity, and eventually sensitized ZNF689-deficient tumors to immunotherapy in vivo. Consistently, ZNF689 expression positively correlated with favorable prognosis and immunotherapy response in clinical samples. Altogether, our study uncovers a previously unrecognized mechanism underlying ZNF689 deficiency-induced ITH and suggests LINE-1 inhibition combined with immunotherapy as a novel treatment strategy for TNBC.

Emerging therapies in cancer metabolism.

Metabolic reprogramming in cancer is not only a biological hallmark but also reveals treatment vulnerabilities. Numerous metabolic molecules have shown promise as treatment targets to impede tumor progression in preclinical studies, with some advancing to clinical trials. However, the intricacy and adaptability of metabolic networks hinder the effectiveness of metabolic therapies. This review summarizes the metabolic targets for cancer treatment and provides an overview of the current status of clinical trials targeting cancer metabolism. Additionally, we decipher crucial factors that limit the efficacy of metabolism-based therapies and propose future directions. With advances in integrating multi-omics, single-cell, and spatial technologies, as well as the ability to track metabolic adaptation more precisely and dynamically, clinicians can personalize metabolic therapies for improved cancer treatment.

Evaluation and prediction method of railway passenger long-term vibration comfort under complex operating conditions.

Vibration contributes large increases in railway passenger discomfort during long-term sitting. Discomfort caused by vibration may differ in different operation conditions. This paper conducted field measurements to investigate the interrelationships between the three. Participants completed a 240-min train journey with their whole-body vibration, subjective comfort ratings and train operating parameters being recorded. A large correlation was observed between the estimated vibration dose value and subjective comfort. The relationship that vibration magnitude significantly increases with increasing the train speed and tunnel density was also found and quantified. A vibration exposure limit of 2.08 m/s1.75 corresponding to the boundary between subjective ratings of comfortable and discomfortable was obtained. Based on the exposure limit and the quantified relationship, a vibration comfort prediction method that can calculate the passenger's maximum tolerance time under a given operation condition was proposed and may help in determining the optimal operating speed and tunnels distribution to alleviate vibration discomfort. Practitioner summary: Similar to the guide to effect of vibration on health in current standard, a vibration exposure limit regarding comfort was provided for reference when assessing long-term vibration comfort. Meanwhile, a prediction method was proposed for determining the best train operating speed and tunnels distribution, thereby alleviating railway passengers' vibration discomfort.

O-GlcNAcylation of MORC2 at threonine 556 by OGT couples TGF-ß signaling to breast cancer progression.

MORC family CW-type zinc finger 2 (MORC2) is a newly identified chromatin-remodeling enzyme involved in DNA damage response and gene transcription, and its dysregulation has been linked with Charcot-Marie-Tooth disease, neurodevelopmental disorder, and cancer. Despite its functional importance, how MORC2 is regulated remains enigmatic. Here, we report that MORC2 is O-GlcNAcylated by O-GlcNAc transferase (OGT) at threonine 556. Mutation of this site or pharmacological inhibition of OGT impairs MORC2-mediated breast cancer cell migration and invasion in vitro and lung colonization in vivo. Moreover, transforming growth factor-ß1 (TGF-ß1) induces MORC2 O-GlcNAcylation through enhancing the stability of glutamine-fructose-6-phosphate aminotransferase (GFAT), the rate-limiting enzyme for producing the sugar donor for OGT. O-GlcNAcylated MORC2 is required for transcriptional activation of TGF-ß1 target genes connective tissue growth factor (CTGF) and snail family transcriptional repressor 1 (SNAIL). In support of these observations, knockdown of GFAT, SNAIL or CTGF compromises TGF-ß1-induced, MORC2 O-GlcNAcylation-mediated breast cancer cell migration and invasion. Clinically, high expression of OGT, MORC2, SNAIL, and CTGF in breast tumors is associated with poor patient prognosis. Collectively, these findings uncover a previously unrecognized mechanistic role for MORC2 O-GlcNAcylation in breast cancer progression and provide evidence for targeting MORC2-dependent breast cancer through blocking its O-GlcNAcylation.

PDSS1-Mediated Activation of CAMK2A-STAT3 Signaling Promotes Metastasis in Triple-Negative Breast Cancer.

Genomic alterations are crucial for the development and progression of human cancers. Copy-number gains found in genes encoding metabolic enzymes may induce triple-negative breast cancer (TNBC) adaptation. However, little is known about how metabolic enzymes regulate TNBC metastasis. Using our previously constructed multiomic profiling of a TNBC cohort, we identified decaprenyl diphosphate synthase subunit 1 (PDSS1) as an essential gene for TNBC metastasis. PDSS1 expression was significantly upregulated in TNBC tissues compared with adjacent normal tissues and was positively associated with poor survival among patients with TNBC. PDSS1 knockdown inhibited TNBC cell migration, invasion, and distant metastasis. Mechanistically, PDSS1, but not a catalytically inactive mutant, positively regulated the cellular level of coenzyme Q10 (CoQ10) and intracellular calcium levels, thereby inducing CAMK2A phosphorylation, which is essential for STAT3 phosphorylation in the cytoplasm. Phosphorylated STAT3 entered the nucleus, promoting oncogenic STAT3 signaling and TNBC metastasis. STAT3 phosphorylation inhibitors (e.g., Stattic) effectively blocked PDSS1-induced cell migration and invasion in vitro and tumor metastasis in vivo. Taken together, our study highlights the importance of targeting the previously uncharacterized PDSS1/CAMK2A/STAT3 oncogenic signaling axis, expanding the repertoire of precision medicine in TNBC. SIGNIFICANCE: A novel metabolic gene PDSS1 is highly expressed in triple-negative breast cancer tissues and contributes to metastasis, serving as a potential therapeutic target for combating metastatic disease.

Bulk and single-cell transcriptome profiling reveal the metabolic heterogeneity in human breast cancers.

An emerging view regarding cancer metabolism is that it is heterogeneous and context-specific, but it remains to be elucidated in breast cancers. In this study, we characterized the energy-related metabolic features of breast cancers through integrative analyses of multiple datasets with genomics, transcriptomics, metabolomics, and single-cell transcriptome profiling. Energy-related metabolic signatures were used to stratify breast tumors into two prognostic clusters: cluster 1 exhibits high glycolytic activity and decreased survival rate, and the signatures of cluster 2 are enriched in fatty acid oxidation and glutaminolysis. The intertumoral metabolic heterogeneity was reflected by the clustering among three independent large cohorts, and the complexity was further verified at the metabolite level. In addition, we found that the metabolic status of malignant cells rather than that of nonmalignant cells is the major contributor at the single-cell resolution, and its interactions with factors derived from the tumor microenvironment are unanticipated. Notably, among various immune cells and their clusters with distinguishable metabolic features, those with immunosuppressive function presented higher metabolic activities. Collectively, we uncovered the heterogeneity in energy metabolism using a classifier with prognostic and therapeutic value. Single-cell transcriptome profiling provided novel metabolic insights that could ultimately tailor therapeutic strategies based on patient- or cell type-specific cancer metabolism.

A Spatial Autoregressive Quantile Regression to Examine Quantile Effects of Regional Factors on Crash Rates.

Spatial autocorrelation and skewed distribution are the most frequent issues in crash rate modelling analysis. Previous studies commonly focus on the spatial autocorrelation between adjacent regions or the relationships between crash rate and potentially risky factors across different quantiles of crash rate distribution, but rarely both. To overcome the research gap, this study utilizes the spatial autoregressive quantile (SARQ) model to estimate how contributing factors influence the total and fatal-plus-injury crash rates and how modelling relationships change across the distribution of crash rates considering the effects of spatial autocorrelation. Three types of explanatory variables, i.e., demographic, traffic networks and volumes, and land-use patterns, were considered. Using data collected in New York City from 2017 to 2019, the results show that: (1) the SARQ model outperforms the traditional quantile regression model in prediction and fitting performance; (2) the effects of variables vary with the quantiles, mainly classifying three types: increasing, unchanged, and U-shaped; (3) at the high tail of crash rate distribution, the effects commonly have sudden increases/decrease. The findings are expected to provide strategies for reducing the crash rate and improving road traffic safety.

Metabolic-Pathway-Based Subtyping of Triple-Negative Breast Cancer Reveals Potential Therapeutic Targets.

Triple-negative breast cancer (TNBC) remains an unmet medical challenge. We investigated metabolic dysregulation in TNBCs by using our multi-omics database (n = 465, the largest to date). TNBC samples were classified into three heterogeneous metabolic-pathway-based subtypes (MPSs) with distinct metabolic features: MPS1, the lipogenic subtype with upregulated lipid metabolism; MPS2, the glycolytic subtype with upregulated carbohydrate and nucleotide metabolism; and MPS3, the mixed subtype with partial pathway dysregulation. These subtypes were validated by metabolomic profiling of 72 samples. These three subtypes had distinct prognoses, molecular subtype distributions, and genomic alterations. Moreover, MPS1 TNBCs were more sensitive to metabolic inhibitors targeting fatty acid synthesis, whereas MPS2 TNBCs showed higher sensitivity to inhibitors targeting glycolysis. Importantly, inhibition of lactate dehydrogenase could enhance tumor response to anti-PD-1 immunotherapy in MPS2 TNBCs. Collectively, our analysis demonstrated the metabolic heterogeneity of TNBCs and enabled the development of personalized therapies targeting unique tumor metabolic profiles.

Pregnancy-specific glycoprotein 9 acts as both a transcriptional target and a regulator of the canonical TGF-ß/Smad signaling to drive breast cancer progression.

Pregnancy-specific glycoprotein 9 (PSG9) is a placental glycoprotein essential for the maintenance of normal gestation in mammals. Bioinformatics analysis of multiple publicly available datasets revealed aberrant PSG9 expression in breast tumors, but its functional and mechanistic role in breast cancer remains unexplored. Here, we report that PSG9 expression levels were elevated in tumor tissues and plasma specimens from breast cancer patients, and were associated with poor prognosis. Gain- or loss-of-function studies demonstrated that PSG9 promoted breast cancer cell proliferation, migration, and invasionin vitro, and enhanced tumor growth and lung colonization in vivo. Mechanistically, transforming growth factor-ß1 (TGF-ß1) transcriptionally activated PSG9 expression through enhancing the enrichment of Smad3 and Smad4 onto PSG9 promoter regions containing two putative Smad-binding elements (SBEs). Mutation of both SBEs in the PSG9 promoter, or knockdown of TGF-ß receptor 1 (TGFBR1), TGFBR2, Smad3, or Smad4 impaired the ability of TGF-ß1 to induce PSG9 expression. Consequently, PSG9 contributed to TGF-ß1-induced epithelial-mesenchymal transition (EMT) and breast cancer cell migration and invasion. Moreover, PSG9 enhanced the stability of Smad2, Smad3, and Smad4 proteins by blocking their proteasomal degradation, and regulated the expression of TGF-ß1 target genes involved in EMT and breast cancer progression, thus further amplifying the canonical TGF-ß/Smad signaling in breast cancer cells. Collectively, these findings establish PSG9 as a novel player in breast cancer progressionvia hijacking the canonical TGF-ß/Smad signaling, and identify PSG9 as a potential plasma biomarker for the early detection of breast cancer.

The predictive value of the prognostic staging system in the 8th edition of the American Joint Committee on Cancer for triple-negative breast cancer: a SEER population-based analysis.

AIM: To examine the stage changes and survival differences among triple-negative breast cancer (TNBC) patients based on the prognostic staging system. METHODS: We used the SEER database to identify eligible patients with TNBC diagnosed between 2010 and 2014. Kaplan-Meier curves were drawn for comparison. The primary end point was breast cancer-specific survival. RESULTS: The median follow-up time was 26 months for 19,608 patients. The stages of all TNBC patients increased or remained unchanged during rearrangement from anatomic staging to prognostic staging. Stage IIA, IIIA and IIIC comprised the majority of patients. Several patients did not have prognostic staging. Stage IIIC incorporated six substages that contributed to high heterogeneity. Overall, the Kaplan-Meier curves still showed the favorable differentiation among stages and substages, with the exception of stage IIB and substage IIIA (T2N0, grade 2-3) patients. CONCLUSION: The prognostic information for breast cancer patients provided by the novel prognostic staging system may be less accurate for TNBC patients in our independent analysis. Moreover, stage IIB and substage IIIA (T2N0, grade 2-3) should possibly undergo further evaluation.

No survival improvement of contralateral prophylactic mastectomy among women with invasive lobular carcinoma.

BACKGROUND AND OBJECTIVE: The prognosis of contralateral prophylactic mastectomy (CPM) in women with breast cancer has been widely reported. Here, we evaluated the survival outcome among patients with invasive lobular carcinoma (ILC) to determine the potential benefit of CPM. METHODS: We used the Surveillance, Epidemiology, and End Results database to identify patients with ILC diagnosed between 1998 and 2010. Survival differences were compared between unilateral mastectomy and CPM. Propensity score matching and risk-stratified subgroup analyses were conducted to reduce selection bias. RESULTS: Among 10 226 patients with ILC, 21.8% women underwent CPM, and the rate of CPM nearly tripled over a 13-year period. Kaplan-Meier curves and hazard ratio (HR) of non-breast cancer-specific survival (non-BCSS) in multivariate analysis reflected a pre-existing selection bias in the present cohort. A Cox proportional hazard model confirmed that patients who received CPM had significantly better BCSS and overall survival (OS) in the prematching population (BCSS: HR = 0.90; OS: HR = 0.93). However, the survival improvement could not be achieved in the postmatching cohort. None of the defined subgroups had OS benefits when CPM was performed. CONCLUSIONS: CPM offers no survival advantage to patients with ILC. The role of CPM among ILC women should be further investigated by incorporating more objective factors.

Survival following breast-conserving therapy is equal to that following mastectomy in young women with early-stage invasive lobular carcinoma.

BACKGROUND: Previous observational studies reported the superior survival of patients with early-stage breast cancer who underwent breast-conserving therapy (BCT, lumpectomy plus postsurgical radiation) compared to that of those who underwent mastectomy. Invasive lobular carcinoma (ILC) is not the same disease as invasive ductal carcinoma (IDC) as it has distinct biologic features and thus requires unique consideration and research. METHODS: We selected women (≤50 years of age) from the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with stage T1-2, N0-1, M0 primary breast cancer with invasive lobular features between 1998 and 2011, that were treated with either BCT or mastectomy with and without radiation. We assessed survival proportions using the Kaplan-Meier method and hazard ratios using Cox proportional hazards models. Breast cancer-specific survival (BCSS) served as the primary endpoint. RESULTS: A total of 3393 eligible young ILC patients were identified, 1391 (41%) of which underwent lumpectomy followed by radiation. The 10-year BCSS rates for patients who received BCT, mastectomy alone and mastectomy with radiation were 95.7%, 94.2% and 89.3%, respectively. Multivariate analysis showed that BCSS was not improved in patients assigned to mastectomy alone group (HR = 0.86; 95% CI 0.57-1.28) or mastectomy with postsurgical radiation group (HR = 0.97; 95% CI 0.58-1.62) compared to that in those who underwent BCT. The results did not changed when evaluating the 1998-2004 and 2005-2011 time periods separately. CONCLUSION: None of the treatment demonstrated an absolute superiority in young women with early-stage ILC. Future studies with more detailed analyses of the confounding factors are worthwhile.

Role of tumor microenvironment in triple-negative breast cancer and its prognostic significance.

Breast cancer has been shown to live in the tumor microenvironment, which consists of not only breast cancer cells themselves but also a significant amount of pathophysiologically altered surrounding stroma and cells. Diverse components of the breast cancer microenvironment, such as suppressive immune cells, re-programmed fibroblast cells, altered extracellular matrix (ECM) and certain soluble factors, synergistically impede an effective anti-tumor response and promote breast cancer progression and metastasis. Among these components, stromal cells in the breast cancer microenvironment are characterized by molecular alterations and aberrant signaling pathways, whereas the ECM features biochemical and biomechanical changes. However, triple-negative breast cancer (TNBC), the most aggressive subtype of this disease that lacks effective therapies available for other subtypes, is considered to feature a unique microenvironment distinct from that of other subtypes, especially compared to Luminal A subtype. Because these changes are now considered to significantly impact breast cancer development and progression, these unique alterations may serve as promising prognostic factors of clinical outcome or potential therapeutic targets for the treatment of TNBC. In this review, we focus on the composition of the TNBC microenvironment, concomitant distinct biological alteration, specific interplay between various cell types and TNBC cells, and the prognostic implications of these findings.

A Low Power, Parallel Wearable Multi-Sensor System for Human Activity Evaluation.

In this paper, the design of a low power heterogeneous wearable multi-sensor system, built with Zynq System-on-Chip (SoC), for human activity evaluation is presented. The powerful data processing capability and flexibility of this SoC represent significant improvements over our previous ARM based system designs. The new system captures and compresses multiple color images and sensor data simultaneously. Several strategies are adopted to minimize power consumption. Our wearable system provides a new tool for the evaluation of human activity, including diet, physical activity and lifestyle.