An immune-related prognostic signature for predicting breast cancer recurrence

Multiple roles of S100P in pan carcinoma: Biological functions and mechanisms (Review)

This article examines the multifaceted roles of the S100P gene in pan‑cancer, with the aim of exploring its biological functions and related mechanisms in depth. S100P is a small calcium‑binding protein that recent studies have identified as playing a significant role in the occurrence and progression of various cancers. As research on cancer biomarkers advances, the relationship between S100P expression levels and cancer prognosis, metastasis and invasiveness has garnered increasing attention. However, the specific mechanisms underlying the role of S100P in different cancer types remain elusive and related research is still in the exploratory phase. Therefore, this review systematically summarizes the biological functions of S100P, clarifying its signaling pathways and regulatory mechanisms. This work provides new insights and strategies for targeted therapy and establishes a theoretical basis for subsequent clinical applications. Through this summary, the present review aims to enhance personalized treatment approaches for S100P‑related cancers and strengthen future explorations of S100P.

Predicting Treatment Outcomes in Glioblastoma: A Risk Score Model for TMZ Resistance and Immune Checkpoint Inhibition

Glioblastoma (GBM) presents significant therapeutic challenges due to its invasive nature and resistance to standard chemotherapy, i.e., temozolomide (TMZ). This study aimed to identify gene signatures that predict poor TMZ response and high PD-L1/PD-1 tumor expression, and explore potential sensitivity to alternative drugs. We analyzed The Cancer Genome Atlas (TCGA) biopsy data to identify differentially expressed genes (DEGs) linked to these characteristics. Among 33 upregulated DEGs, 5 were significantly correlated with overall survival. A risk score model was built using these 5 DEGs, classifying patients into low-, medium-, and high-risk groups. We assessed immune cell infiltration, immunosuppressive mediators, and epithelial-mesenchymal transition (EMT) markers in each group using correlation analysis, Gene Set Enrichment Analysis (GSEA), and machine learning. The model demonstrated strong predictive power, with high-risk patients exhibiting poorer survival and increased immune infiltration. GSEA revealed upregulation of immune and EMT-related pathways in high-risk patients. Our analyses suggest that high-risk patients may exhibit limited response to PD-1 inhibitors, but could show sensitivity to etoposide and paclitaxel. This risk score model provides a valuable tool for guiding therapeutic decisions and identifying alternative chemotherapy options to enable the development of personalized and cost-effective treatments for GBM patients.

Significance of Midkine Signaling in Women's Cancers: Novel Biomarker and Therapeutic Target

Midkine (MDK) is a multifunctional protein that is secreted into the extracellular space. It functions as a cytokine or growth factor, modulating a variety of signaling pathways implicated in angiogenesis, antitumor immunity, metastasis, and therapy resistance. MDK overexpression has been documented in a variety of cancers, including those that affect women. MDK mediates its effects through activation of key signaling pathways such as MAPK/ERK, PI3K/AKT, and STAT3, which are pivotal for cell cycle progression, survival, and maintenance of stemness. Obesity and estrogen signaling, a known critical driver of women's cancer, further elevate the levels of MDK. MDK's effects are mediated by a variety of membrane receptors, such as integrins, protein tyrosine phosphatase ζ (PTPζ), anaplastic lymphoma kinase (ALK), and neurogenic locus notch homolog protein 2 (Notch2). Recently published studies have indicated that MDK is a potential therapeutic target and a biomarker for the progression of women's cancer. In this review, we have provided a concise summary of the most recent papers that have examined the potential biomarker and therapeutic utility of MDK signaling in women's cancer.

Transfer learning for accelerated failure time model with microarray data

BACKGROUND

In microarray prognostic studies, researchers aim to identify genes associated with disease progression. However, due to the rarity of certain diseases and the cost of sample collection, researchers often face the challenge of limited sample size, which may prevent accurate estimation and risk assessment. This challenge necessitates methods that can leverage information from external data (i.e., source cohorts) to improve gene selection and risk assessment based on the current sample (i.e., target cohort).

METHOD

We propose a transfer learning method for the accelerated failure time (AFT) model to enhance the fit on the target cohort by adaptively borrowing information from the source cohorts. We use a Leave-One-Out cross validation based procedure to evaluate the relative stability of selected genes and overall predictive power.

CONCLUSION

In simulation studies, the transfer learning method for the AFT model can correctly identify a small number of genes, its estimation error is smaller than the estimation error obtained without using the source cohorts. Furthermore, the proposed method demonstrates satisfactory accuracy and robustness in addressing heterogeneity across the cohorts compared to the method that directly combines the target and the source cohorts in the AFT model. We analyze the GSE88770 and GSE25055 data using the proposed method. The selected genes are relatively stable, and the proposed method can make an overall satisfactory risk prediction.

Selection of breast cancer subtypes to improve benefits of intensive dose‑dense chemotherapy: A systematic meta‑analysis

Breast cancer (BC) is the most commonly diagnosed cancer and the second leading cause of cancer mortality among women worldwide. A large number of patients experience recurrence and BC-associated mortality following adjuvant chemotherapy. The present study aimed to determine the most suitable pathological subtype of BC to benefit from intensive dose-dense (DD) chemotherapy. A total of four electronic databases were searched from inception up to March 10, 2023. Randomized controlled trials (RCTs) and retrospective studies comparing DD chemotherapy with standard chemotherapy in patients with BC were included. Pairwise random effects and network meta-analyses were performed to summarize efficacy and safety outcomes. A total of 27 original studies including 27,580 patients with BC were included. In terms of efficacy, the present study evaluated overall survival, disease-free survival, event-free survival, recurrence-free survival, pathological complete response and objective remission rate. Significant differences were identified in overall, hormone receptor+ (HR+) and HR- subgroups. Furthermore, from the network analysis, the HR+ and Her2- subgroups had the highest ranking, and these findings suggested that HR+/Her2- patients with BC should adhere to a treatment strategy including intensive DD chemotherapy, which is also characterized by an acceptable safety profile. In conclusion, patients with HR+ and Her2- BC were revealed to be the most suitable pathological type and are most likely to benefit from intense DD chemotherapy. The present study was registered with PROSPERO, CRD2022420351567.

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Background

High relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. To optimize the surveillance regimen for distant recurrence after neoadjuvant chemotherapy (NAC), we conducted a comprehensive analysis using bioinformatics and machine learning approaches.

Materials and methods

Microarray data were retrieved from the GEO database, and differential expression analysis was performed with the R package 'Limma'. We used the Metascape tool for enrichment analyses, and 'WGCNA' was utilized to establish co-expression networks, selecting the soft threshold power with the 'pickSoftThreshold' algorithm. We integrated ten machine learning algorithms and 101 algorithm combinations to identify key genes associated with distant recurrence in BC. Unsupervised clustering was performed with the R package 'ConsensusCluster Plus'. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the Genetic Perturbation Similarity Analysis (GPSA) database. Single-cell RNA sequencing (scRNA-seq) analysis was conducted through the Tumour Immune Single-cell Hub (TISCH) database, and the XSum algorithm was used to screen candidate small molecule drugs based on the Connectivity Map (CMAP) database. Molecular docking processes were conducted using Schrodinger software. GMT files containing gene sets associated with metabolism and senescence were obtained from GSEA MutSigDB database. The GSVA score for each gene set across diverse samples was computed using the ssGSEA function implemented in the GSVA package.

Results

Our analysis, which combined Limma, WGCNA, and machine learning approaches, identified 16 RCB-relevant gene signatures influencing distant recurrence-free survival (DRFS) in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) with different distant recurrence risks. This molecular subtyping scheme was found to be closely associated with tumor metabolism and cellular senescence. Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60-6.29; log-rank test p < 0.0001). High GATA3 expression, high levels of resting mast cell infiltration, and a high proportion of estrogen receptor (ER)-positive patients contributed to better DRFS in cluster C1. We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95-0.86), with a C-index of 0.85 (95% CI: 0.81-0.90). Entinostat was identified as a potential small molecule compound to reverse high RCB after NAC. We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients.

Conclusion

This study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.

ACO1 and IREB2 downregulation confer poor prognosis and correlate with autophagy-related ferroptosis and immune infiltration in KIRC

Background

ACO1 and IREB2 are two homologous cytosolic regulatory proteins, which sense iron levels and change iron metabolism–linked molecules. These two genes were noticeably decreased in kidney renal clear cell carcinoma (KIRC), which confer poor survival. Meanwhile, there is a paucity of information about the mechanisms and clinical significance of ACO1 and IREB2 downregulation in renal cancers.

Methods

The expression profiles of ACO1 and IREB2 were assessed using multiple public data sets via several bioinformatics platforms. Clinical and pathological information was utilized to stratify cohorts for comparison. Patient survival outcomes were evaluated using the Kaplan–Meier plotter, a meta-analysis tool. The correlations of ACO1 and IREB2 with ferroptosis were further evaluated in The Cancer Genome Atlas (TCGA)–KIRC database. Tumor immune infiltration was analyzed using the CIBERSORT, TIMER, and GEPIA data resources. ACO1 antagonist sodium oxalomalate (OMA) and IREB2 inhibitor sodium nitroprusside (SNP) was used to treat renal cancer ACHN cells together with sorafenib.

Results

KIRC patients with low ACO1 or IREB2 contents exhibited a remarkably worse survival rate in contrast with those with high expression in Kaplan–Meier survival analyses. Meanwhile, ACO1 and IREB2 regulate autophagy-linked ferroptosis along with immune cell invasion in the tumor microenvironment in KIRC patients. Blocking the activation of these two genes by their inhibitors OMA and SNP ameliorated sorafenib-triggered cell death, supporting that ACO1 and IREB2 could be participated in its cytotoxic influence on renal cancer cells.

Conclusion

ACO1 and IREB2 downregulation in renal cancers were correlated with cancer aggressiveness, cellular iron homeostasis, cytotoxic immune cell infiltration, and patient survival outcomes. Our research is integral to verify the possible significance of ACO1 and IREB2 contents as a powerful signature for targeted treatment or novel immunotherapy in clinical settings.

Prognostic Characteristics of Immune-Related Genes and the Related Regulatory Axis in Patients With Stage N+M0 Breast Cancer

Breast cancer (BRCA) has the highest incidence rate among female tumours. The function of the immune system affects treatment efficacy and prognosis in patients with BRCA. However, the exact role of immune-related genes (IRGs) in stage N+M0 BRCA is unknown. We constructed a predictive risk scoring model with five IRGs (CDH1, FGFR3, INHBA, S100B, and SCG2) based on the clinical, mutation, and RNA sequencing data of individuals with stage N+M0 BRCA sourced from The Cancer Genome Atlas. Results from the Shandong Cancer Hospital and Institute validation cohort suggested that regardless of clinical stage, tumour size, or the number of lymph node metastases, this model was able to reliably discriminate low-risk patients from high-risk ones and assess the prognosis of patients with stage N+M0 BRCA, and low-risk patients could benefit more from immunotherapy than high-risk patients. In addition, significant inter-group variations in immunocyte infiltration and the tumour microenvironment were observed. Moreover, risk score and age were found to be independent factors in multivariate COX regression analysis, which influenced the outcome of patients with stage N+M0 BRCA. Based on the above findings, we plotted a prognostic nomogram. Finally, we constructed a lncRNA KCNQ1OT1-LINC00665-TUG1/miR-9-5p/CDH1 regulatory axis of the ceRNA network to explore the mechanism of BRCA progression. In summary, we conducted a systemic and extensive bioinformatics investigation and established an IRG-based prognostic scoring model. Finally, we constructed a ceRNA regulatory axis that might play a significant role in BRCA development. More research is required to confirm this result. Scoring system-based patient grouping can help predict the outcome of patients with stage N+M0 BRCA more effectively and determine their sensitivity to immunotherapies, which will aid the development of personalised therapeutic strategies and inspire the research and development of novel medications.

CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients

BACKGROUND

The foremost cause of death of breast cancer (BC) patients is metastasis, and the first site to which BC predominantly metastasizes is the axillary lymph node (ALN). Thus, ALN status is a key prognostic indicator at diagnosis. The immune system has an essential role in cancer progression and dissemination, so its evaluation in ALNs could have significant applications. In the present study we aimed to investigate the association of clinical-pathological and immune variables in the primary tumour and non-metastatic ALNs (ALNs^-) of a cohort of luminal A and triple-negative BC (TNBC) patients with cancer-specific survival (CSS) and time to progression (TTP).

METHODS

We analysed the differences in the variables between patients with different outcomes, created univariate and multivariate Cox regression models, validated them by bootstrapping and multiple imputation of missing data techniques, and used Kaplan-Meier survival curves for a 10-years follow-up.

RESULTS

We found some clinical-pathological variables at diagnosis (tumour diameter, TNBC molecular profile and presence of ALN metastasis), and the levels of several immune markers in the two studied sites, to be associated with worse CSS and TTP. Nevertheless, only CD68 and CD83 in ALNs^- were confirmed as independent prognostic factors for TTP.

CONCLUSIONS

The study identified the importance of macrophage and dendritic cell markers as prognostic factors of relapse for BC. We highlight the importance of studying the immune response in ALNs^-, which could be relevant to the prediction of BC patients' outcome.

miR‑302d‑3p regulates the viability, migration and apoptosis of breast cancer cells through regulating the TMBIM6‑mediated ERK signaling pathway

MicroRNAs (miRs/miRNAs) play important roles in the occurrence, metastasis and prognosis of multiple types of cancers. However, the specific role of miR-302d-3p and its underlying mechanism in breast cancer (BC) have not yet been reported. The present study aimed to identify the role of miR-302D-3p in BC and its potential mechanism using BC cell lines MCF7 and MDA-MB-231 and normal breast epithelial cell MCF-10A. Cancer and paracancerous tissue from patients with BC were also used. Reverse transcription-quantitative PCR was performed to detect the expression of miR-302d-3p and transmembrane Bax inhibitor motif containing 6 (TMBIM6). Dual-luciferase reporter assays verified the binding sites of miR-302d-3p and TMBIM6. Immunohistochemistry was used to measure the expression of TMBIM6. Cell transfection techniques were used to overexpress or interfere with miR-302d-3p and TMBIM6. A Cell Counting Kit-8 assay was performed to detect cell viability, and migration was measured using a wound healing assay. Apoptosis was detected by flow cytometry. The expression levels of apoptosis-related proteins and pathway-related proteins were detected by western blotting. The expression of miR-302d-3p in BC cell lines was found to be downregulated. It was also demonstrated that miR-302d-3p could inhibit cell viability and migration and promote apoptosis. The expression of TMBIM6 in BC cell lines and tissues was upregulated. Upregulated miR-302d-3p was shown to inhibit viability and migration, and promote apoptosis by targeting TMBIM6, during which extracellular signal-regulated kinase (ERK) and its phosphorylation were inhibited in the ERK signaling pathway in cells. Overall, the present study demonstrated that miR-302d-3p could regulate the viability, migration and apoptosis of BC cells through regulating TMBIM6-mediated ERK signaling pathway.

Identification and Validation of a Five-Gene Signature Associated With Overall Survival in Breast Cancer Patients

BACKGROUND

Recent years, the global prevalence of breast cancer (BC) was still high and the underlying molecular mechanisms remained largely unknown. The investigation of prognosis-related biomarkers had become an urgent demand.

RESULTS

In this study, gene expression profiles and clinical information of breast cancer patients were downloaded from the TCGA database. The differentially expressed genes (DEGs) were estimated by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A risk score formula involving five novel prognostic associated biomarkers (EDN2, CLEC3B, SV2C, WT1, and MUC2) were then constructed by LASSO. The prognostic value of the risk model was further confirmed in the TCGA entire cohort and an independent external validation cohort. To explore the biological functions of the selected genes, in vitro assays were performed, indicating that these novel biomarkers could markedly influence breast cancer progression.

CONCLUSIONS

We established a predictive five-gene signature, which could be helpful for a personalized management in breast cancer patients.

Prognostic Significance of BIRC5/Survivin in Breast Cancer: Results from Three Independent Cohorts

Simple Summary

Survivin, coded by the BIRC5 gene, is the cell death preventing protein, which is important for cell division in normal and cancer cells. It is intensively studied as a cancer biomarker and target for antitumor therapy. In this study we asked if we could get clinically helpful information on how active BIRC5 is in breast cancer patients? We studied the BIRC5 protein level in tumor samples for breast cancer patients from a West Swedish cohort and its mRNA level in two different public gene expression databases. Survival analysis demonstrated that a higher BIRC5 protein or mRNA level was associated with poor survival in all cohorts and for different cancer subtypes. We show that BIRC5 is a promising independent cancer survival marker.

Abstract

Breast cancer (BC) histological and molecular classifications significantly improved the treatment strategy and prognosis. Inhibitor of apoptosis BIRC5/survivin is often overexpressed in cancers, however, indications of its importance in BC are inconsistent. We integrate BIRC5 protein and mRNA measures with clinical associates and long-term outcome in three independent cohorts Protein levels of BIRC5 were measured in primary lysates of 845 patients of the West Swedish BC cohort (VGR-BC) and linked to 5- and 27-years survival. The results were externally validated in transcriptomic data from METABRIC and SCAN-B cohorts. Survival analysis showed that high levels of BIRC5 were consistently associated with a poor probability of 5-year overall survival. High BIRC5 in VGR-BC contributed negatively to the disease-specific survival at 5 and 27 years. Subsets with different status by ER (estrogen receptor) expression and presence of nodal metastasis supported independent association of high BIRC5 with poor prognosis in all cohorts. In METABRIC and SCAN-B cohorts, high levels of BIRC5 mRNA were associated with the basal-like and luminal B molecular BC subtypes and with increasing histologic grade. BIRC5 is a sensitive survival marker that acts independent of ER and nodal status, and its levels need to be considered when making treatment decisions.

An immune-related prognostic signature for predicting breast cancer recurrence

Breast cancer (BC) is the most common cancer among women worldwide and is the second leading cause of cancer‐related deaths in women. Increasing evidence has validated the vital role of the immune system in BC development and recurrence. In this study, we identified an immune‐related prognostic signature of BRCA that could help delineate risk scores of poor outcome for each patient. This prognostic signature comprised information on five danger genes—TSLP, BIRC5, S100B, MDK, and S100P—and three protect genes RARRES3, BLNK, and ACO1. Kaplan‐Meier survival curve showed that patients classified as low‐risk according to optimum cut‐off risk score had better prognosis than those identified within the high‐risk group. ROC analysis indicated that the identified prognostic signature had excellent diagnostic efficiency for predicting 3‐ and 5‐years relapse‐free survival (RFS). Multivariate Cox regression analysis proved that the prognostic signature is independent of other clinical parameters. Stratification analysis demonstrated that the prognostic signature can be used to predict the RFS of BC patients within the same clinical subgroup. We also developed a nomogram to predict the RFS of patients. The calibration plots exhibited outstanding performance. The validation sets (GSE21653, GSE20711, and GSE88770) were used to external validation. More convincingly, the real time RT‐PCR results of clinical samples demonstrated that danger genes were significantly upregulated in BC samples, whereas protect genes were downregulated. In conclusion, we developed and validated an immune‐related prognostic signature, which exhibited excellent diagnostic efficiency in predicting the recurrence of BC, and will help to make personalized treatment decisions for patients at different risk score.