Regulated lytic cell death in breast cancer

Synergistic bioinformatics and sophisticated machine learning unveil ferroptosis-driven regulatory pathways and immunotherapy potential in breast carcinoma

BACKGROUND

The intersection of aberrant iron metabolism and the rapidly advancing field of immunotherapy has emerged as a critical focus in breast cancer (BRCA) therapeutics. Ferroptosis, a distinct form of iron-dependent cell death driven by lipid peroxidation, has garnered increasing attention for its pivotal role in cancer progression.

METHODS

Utilizing extensive datasets from TCGA and GEO, this research extracted a wealth of biological data, including mRNA splicing indices, genomic aberrations, copy number variations (CNV), tumor mutational burden (TMB), and diverse clinical information. Through precise Lasso regression analysis, this research constructed a prognostic model that elucidates the molecular interactions of FRGs in BRCA. Concurrent co-expression network analyses were performed to explore the dynamic interplay between gene expression patterns and FRGs, revealing potential regulatory mechanisms.

RESULTS

This research analysis revealed significant overexpression of FRGs in high-risk BRCA samples, highlighting their prognostic relevance beyond traditional clinical parameters. GSVA identified immune response and cancer-related pathways as predominantly active in high-risk groups, suggesting ferroptosis as a central modulator within the tumor microenvironment. Notably, genes such as ACTL8, VGF, and CPLX2 emerged as markers of tumorigenesis, while IL33 and TP63 were identified as potential key regulators of cancer progression, each exhibiting distinct expression profiles across risk levels. Furthermore, this research incorporated gene correlations, CNV profiles, SNP arrays, and drug susceptibility analyses, contributing to the advancement of precision oncology.

CONCLUSIONS

The integration of bioinformatics and machine learning in this study underscores a strong correlation between FRG expression patterns and BRCA prognosis, affirming their potential as precise biomarkers for personalized immunotherapy.

ATF4/NUPR1 axis promotes cancer cell survival and mediates immunosuppression in clear cell renal cell carcinoma

Cancer cells encounter unavoidable stress during tumor growth. The stress-induced transcription factor, activating transcription factor 4 (ATF4), has been reported to upregulate various adaptive genes involved in salvage pathways to alleviate stress and promote tumor progression. However, this effect is unknown in clear cell renal cell carcinoma (ccRCC). In this study, we found that ATF4 expression was remarkably upregulated in tumor tissues and associated with poor ccRCC outcomes. ATF4 depletion significantly impaired ccRCC cell proliferation, migration, and invasion in vitro and in vivo by inhibiting the AKT/mTOR and epithelial-mesenchymal transition (EMT)-related signaling pathway. RNA sequencing and functional studies identified nuclear protein 1 (NUPR1) as a key downstream target of ATF4 for repressing ferroptosis and promoting ccRCC cell survival. In addition, targeting ATF4 or pharmacological inhibition using NUPR1 inhibitor ZZW115 promoted antitumor immunity in syngeneic graft mouse models, represented by increased infiltration of CD4+ and CD8+ T cells. Furthermore, ZZW115 could improve the response to the PD-1 immune checkpoint blockade. The results demonstrate that the ATF4/NUPR1 signaling axis promotes ccRCC survival and facilitates tumor-mediated immunosuppression, providing a set of potential targets and prognostic indicators for ccRCC patients.

Golgi protein ACBD3 downregulation sensitizes cells to ferroptosis

Ferroptosis, a form of cell death driven by iron-dependent lipid peroxidation, is emerging as a promising target in cancer therapy. It is regulated by a network of molecules and pathways that modulate lipid metabolism, iron homeostasis and redox balance, and related processes. However, there are still numerous regulatory molecules intricately involved in ferroptosis that remain to be identified. Here, we indicated that suppression of Golgi protein acyl-coenzyme A binding domain A containing 3 (ACBD3) increased the sensitivity of Henrieta Lacks and PANC1 cells to ferroptosis. ACBD3 knockdown increases labile iron levels by promoting ferritinophagy. This increase in free iron, coupled with reduced levels of glutathione peroxidase 4 due to ACBD3 knockdown, leads to the accumulation of reactive oxygen species and lipid peroxides. Moreover, ACBD3 knockdown also results in elevated levels of polyunsaturated fatty acid-containing glycerophospholipids through mechanisms that remain to be elucidated. Furthermore, inhibition of ferrtinophagy in ACBD3 downregulated cells by knocking down the nuclear receptor co-activator 4 or Bafilomycin A1 treatment impeded ferroptosis. Collectively, our findings highlight the pivotal role of ACBD3 in governing cellular resistance to ferroptosis and suggest that pharmacological manipulation of ACBD3 levels is a promising strategy for cancer therapy.

Identification of clinical prognostic factors and analysis of ferroptosis-related gene signatures in the bladder cancer immune microenvironment

BACKGROUND

Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and poses a significant burden in terms of both incidence and mortality rates on a global scale. Among all BLCA cases, non-muscle invasive bladder cancer constitutes approximately 75% of the total. In recent years, the concept of ferroptosis, an iron-dependent form of regulated cell death marked by the accumulation of lipid peroxides, has captured the attention of researchers worldwide. Nevertheless, the precise involvement of ferroptosis-related genes (FRGs) in the anti-BLCA response remains inadequately elucidated.

METHODS

The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of FRGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and FRGs, unraveling their functional relevance and potential implications in BLCA.

RESULTS

FRGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including MYBPH, SOST, SPRR2A, and CRNN, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CYP4F8, PDZD3, CRTAC1, and LRTM1 were identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles.

CONCLUSIONS

FRGs are associated with the onset and progression of BLCA. A FRGs signature offers a viable alternative to predict BLCA, and these FRGs show a prospective research area for BLCA targeted treatment in the future.

Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication

BACKGROUND

Deep learning models can infer cancer patient prognosis from molecular and anatomic pathology information. Recent studies that leveraged information from complementary multimodal data improved prognostication, further illustrating the potential utility of such methods. However, current approaches: 1) do not comprehensively leverage biological and histomorphological relationships and 2) make use of emerging strategies to "pretrain" models (i.e., train models on a slightly orthogonal dataset/modeling objective) which may aid prognostication by reducing the amount of information required for achieving optimal performance. In addition, model interpretation is crucial for facilitating the clinical adoption of deep learning methods by fostering practitioner understanding and trust in the technology.

METHODS

Here, we develop an interpretable multimodal modeling framework that combines DNA methylation, gene expression, and histopathology (i.e., tissue slides) data, and we compare performance of crossmodal pretraining, contrastive learning, and transfer learning versus the standard procedure.

RESULTS

Our models outperform the existing state-of-the-art method (average 11.54% C-index increase), and baseline clinically driven models (average 11.7% C-index increase). Model interpretations elucidate consideration of biologically meaningful factors in making prognosis predictions.

DISCUSSION

Our results demonstrate that the selection of pretraining strategies is crucial for obtaining highly accurate prognostication models, even more so than devising an innovative model architecture, and further emphasize the all-important role of the tumor microenvironment on disease progression.

Immunogenic cell death in cancer immunotherapy

Cancer immunotherapy has been acknowledged as a new paradigm for cancer treatment, with notable therapeutic effects on certain cancer types. Despite their significant potential, clinical studies over the past decade have revealed that cancer immunotherapy has low response rates in the majority of solid tumors. One of the key causes for poor responses is known to be the relatively low immunogenicity of solid tumors. Because most solid tumors are immune desert 'cold tumors' with antitumor immunity blocked from the onset of innate immunity, combination therapies that combine validated T-based therapies with approaches that can increase tumor-immunogenicity are being considered as relevant therapeutic options. This review paper focuses on immunogenic cell death (ICD) as a way of enhancing immunogenicity in tumor tissues. We will thoroughly review how ICDs such as necroptosis, pyroptosis, and ferroptosis can improve anti-tumor immunity and outline clinical trials targeting ICD. Finally, we will discuss the potential of ICD inducers. as an adjuvant for cancer immunotherapy.[BMB Reports 2023; 56(5): 275-286].

Immunogenic cell death in cancer immunotherapy

Cancer immunotherapy has been acknowledged as a new paradigm for cancer treatment, with notable therapeutic effects on certain cancer types. Despite their significant potential, clinical studies over the past decade have revealed that cancer immunotherapy has low response rates in the majority of solid tumors. One of the key causes for poor responses is known to be the relatively low immunogenicity of solid tumors. Because most solid tumors are immune desert 'cold tumors' with antitumor immunity blocked from the onset of innate immunity, combination therapies that combine validated T-based therapies with approaches that can increase tumor-immunogenicity are being considered as relevant therapeutic options. This review paper focuses on immunogenic cell death (ICD) as a way of enhancing immunogenicity in tumor tissues. We will thoroughly review how ICDs such as necroptosis, pyroptosis, and ferroptosis can improve anti-tumor immunity and outline clinical trials targeting ICD. Finally, we will discuss the potential of ICD inducers. as an adjuvant for cancer immunotherapy.[BMB Reports 2023; 56(5): 275-286].

Targeting pyroptosis in breast cancer: biological functions and therapeutic potentials on It

Pyroptosis is a lytic and inflammatory type of programmed cell death that is mediated by Gasdermin proteins (GSDMs). Attractively, recent evidence indicates that pyroptosis involves in the development of tumors and can serve as a new strategy for cancer treatment. Here, we present a basic knowledge of pyroptosis, and an overview of the expression patterns and roles of GSDMs in breast cancer. In addition, we further summarize the available evidence of pyroptosis in breast cancer progression and give insight into the clinical potential of applying pyroptosis in anticancer strategies for breast cancer. This review will deepen our understanding of the relationship between pyroptosis and breast cancer, and provide a novel potential therapeutic avenue for breast cancer.

Identification of Clinical Prognostic Regulators and Analysis of Ferroptosis-Related Signatures in the Tumor Immune Microenvironment in Lung Squamous Cell Carcinoma

Objective

Lung squamous cell carcinoma (LUSC) is a common respiratory malignancy and presents an increasing prevalence. Ferroptosis is a newly identified controlled cell death that has captured clinical attention worldwide. However, the ferroptosis-related lncRNA expression in LUSC and its relevance to prognosis remain elusive.

Methods

The research measured predictive ferroptosis-related lncRNAs in LUSC samples from the TCGA datasets. Data on the stemness indices (mRNAsi) and corresponding clinical characteristics were obtained from TCGA. A prognosis model was established using the LASSO regression. Changes within the neoplasm microenvironment (TME) and medicine association were examined to grasp higher immune cell infiltration in numerous risk teams. In line with coexpression studies, the expression of lncRNAs is closely associated with that of ferroptosis. They were overexpressed in unsound people in the absence of alternative clinical symptoms.

Results

The low-risk and speculative teams were considered to have substantial differences in CCR and inflammation-promoting genes. C10orf55, AC016924.1, AL161431.1, LUCAT1, AC104248.1, and MIR3945HG were highly expressed in the high-risk group, suggesting their involvement in the oncology process of LUSC. Moreover, AP006545.2 and AL122125.1 were considerably higher in the low-risk group, implying the potential of these genes as LUSC tumor suppressor genes. The biomarkers listed above may serve as therapeutic targets for LUSC. lncRNAs were also linked to patient outcomes in the LUSC trial.

Conclusion

lncRNAs of ferroptosis were overexpressed in the high-risk cohort without other clinical signs, implying their potential to predict BLCA prognosis. GSEA highlighted immunological and tumor-related pathways in the high-risk group. LUSC occurrence and progression are linked to lncRNAs of ferroptosis. Corresponding prognostic models help forecast the prognosis of LUSC patients. lncRNAs of ferroptosis and associated immune cell infiltration in the tumor microenvironment (TME) may serve as potential therapeutic targets in LUSC, which requires further trials. In addition, the lncRNAs of ferroptosis signature offer a viable alternative to predict LUSC, and these ferroptosis-lncRNAs show a prospective research area for LUSC-targeted treatment in the future.

Potential biomarkers for predicting the overall survival outcome of kidney renal papillary cell carcinoma: an analysis of ferroptosis-related LNCRNAs

Background

Kidney renal papillary cell carcinoma (KIRP) is a dangerous cancer, which accounts for 15–20% of all kidney malignancies. Ferroptosis is a rare kind of cell death that overcomes medication resistance. Ferroptosis-related long non-coding RNAs (LNCRNAs) in KIRP, remain unknown.

Method

We wanted to express how ferroptosis-related LNCRNAs interact with immune cell infiltration in KIRP. Gene set enrichment analysis in the GO and KEGG databases were used to explore gene expression enrichment. The prognostic model was constructed using Lasso regression. In addition, we also analyzed the modifications in the tumor microenvironment (TME) and immunological association.

Result

The expression of LNCRNA was closely connected to the ferroptosis, according to co-expression analyses. CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were found to be significantly increased in the high-risk group, indicating that all of these markers implicates the malignancy processes for KIRP patients and may be cancer-promoting variables. LNCTAM34A and AC024022.1 were shown to be significantly elevated in the low-risk group; these might represent as the KIRP tumor suppressor genes. According to the TCGA, CCR, and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of CD160, TNFSF4, CD80, BTLA, and TNFRSF9 was different in the two risk groups.

Conclusion

LNCRNAs associated with ferroptosis were linked to the occurrence and progression of KIRP. Ferroptosis-related LNCRNAs and immune cell infiltration in the TME may be potential biomarkers in KIRP that should be further investigated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01037-0.