SPAG5 as a prognostic biomarker and chemotherapy sensitivity predictor in breast cancer: a retrospective, integrated genomic, transcriptomic, and protein analysis

GSDME-mediated pyroptosis promotes anti-tumor immunity of neoadjuvant chemotherapy in breast cancer

Paclitaxel and anthracycline-based chemotherapy is one of the standard treatment options for breast cancer. However, only about 6-30% of breast cancer patients achieved a pathological complete response (pCR), and the mechanism responsible for the difference is still unclear. In this study, random forest algorithm was used to screen feature genes, and artificial neural network (ANN) algorithm was used to construct an ANN model for predicting the efficacy of neoadjuvant chemotherapy for breast cancer. Furthermore, digital pathology, cytology, and molecular biology experiments were used to verify the relationship between the efficacy of neoadjuvant chemotherapy and immune ecology. It was found that paclitaxel and doxorubicin, an anthracycline, could induce typical pyroptosis and bubbling in breast cancer cells, accompanied by gasdermin E (GSDME) cleavage. Paclitaxel with LDH release and Annexin V/PI doubule positive cell populations, and accompanied by the increased release of damage-associated molecular patterns, HMGB1 and ATP. Cell coculture experiments also demonstrated enhanced phagocytosis of macrophages and increased the levels of IFN-γ and IL-2 secretion after paclitaxel treatment. Mechanistically, GSDME may mediate paclitaxel and doxorubicin-induced pyroptosis in breast cancer cells through the caspase-9/caspase-3 pathway, activate anti-tumor immunity, and promote the efficacy of paclitaxel and anthracycline-based neoadjuvant chemotherapy. This study has practical guiding significance for the precision treatment of breast cancer, and can also provide ideas for understanding molecular mechanisms related to the chemotherapy sensitivity.

Sperm-Associated Antigen 5 Knockout Reduces Doxorubicin and Docetaxel Resistance in Triple-Negative Breast Cancer MDA-MB-231 and BT549 Cells

Sperm-associated antigen 5 (SPAG5), also known as Astrin, was previously demonstrated as a biomarker for cellular resistance to major breast cancer therapies, including chemo-, endocrine- and targeted therapy. However, the contribution of SPAG5 to anthracycline- and taxane-based chemotherapy in triple-negative breast cancer (TNBC) remains controversial. In the present study, the SPAG5 knockout cell model was established by using clustered regularly interspaced palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) system in MDA-MB-231 and BT549 TNBC cell lines. The knockout of SPAG5 was confirmed on both gene and protein levels using genomic PCR, DNA sequencing and western blotting. The functional loss of SPAG5 was determined by colony-formation assay. SPAG5-regulated doxorubicin- and docetaxel-resistance was assessed by MTT and apoptosis assays. The results indicated that all the SPAG5 knockout MDA-MB-231 and BT549 clones were biallelic, where one allele was replaced by the donor template, and the other allele had the same "T" insertion (indel) adjacent to the cutting sites of gRNAs at the exon 1 boundary, irrespective of the gRNAs and cell lines. The locus of indel interrupted the SPAG5 transcription by damaging the GT-AG mRNA processing rule. Deletion of SPAG5 decreased clonogenicity in both MDA-MB-231 and BT549 cells. SPAG5 was able to regulate the resistance and the drug-induced apoptosis of both doxorubicin and docetaxel. In conclusion, recombinant plasmid-based CRISPR-Cas9 technology can be used to delete the SPAG5 gene in the TNBC cell lines. SPAG5 has an important role in regulating cell proliferation and doxorubicin- and docetaxel-resistance in MDA-MB-231 and BT549 cells.

The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination

Introduction

Early diagnosis of sepsis and discrimination from SIRS is crucial for clinicians to provide appropriate care, management and treatment to critically ill patients. We describe identification of mRNA biomarkers from peripheral blood leukocytes, able to identify severe, systemic inflammation (irrespective of origin) and differentiate Sepsis from SIRS, in adult patients within a multi-center clinical study.

Methods

Participants were recruited in Intensive Care Units (ICUs) from multiple UK hospitals, including fifty-nine patients with abdominal sepsis, eighty-four patients with pulmonary sepsis, forty-two SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), sampled at four time points, in addition to thirty healthy control donors. Multiple clinical parameters were measured, including SOFA score, with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools.

Results

Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed 'indicators of inflammation' (I°I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC>0.99). Twenty entities, termed 'SIRS or Sepsis' (S°S) biomarkers, were differentially expressed between sepsis and SIRS (FC>2·0, p-value<0.05).

Discussion

The best performing signature for discriminating sepsis from SIRS was CMTM5/CETP/PLA2G7/MIA/MPP3 (AUC=0.9758). The I°I and S°S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study/assay platform.

KNSTRN Is a Prognostic Biomarker That Is Correlated with Immune Infiltration in Breast Cancer and Promotes Cell Cycle and Proliferation

Kinetochore-localized astrin/SPAG5-binding protein (KNSTRN) promotes the progression of bladder cancer and lung adenocarcinoma. However, its expression and biological function in breast cancer remain largely unknown. Therefore, this study aimed to analyze KNSTRN expression, prognoses, correlation with immune infiltration, expression-associated genes, and regulated signaling pathways to characterize its role in regulating the cell cycle using both bioinformatics and in vitro functional experiments. Analyses of The Cancer Genome Atlas, Gene Expression Omnibus, TIMER, and The Human Protein Atlas databases revealed a significant upregulation of KNSTRN transcript and protein levels in breast cancer. Kaplan-Meier survival analyses demonstrated a significant association between high expression of KNSTRN and poor overall survival, relapse-free survival, post-progression survival, and distant metastases-free survival in patients with breast cancer. Furthermore, multivariate Cox regression analyses confirmed that KNSTRN is an independent prognostic factor for breast cancer. Immune infiltration analysis indicated a positive correlation between KNSTRN expression and T regulatory cell infiltration while showing a negative correlation with Tgd and natural killer cell infiltration. Gene set enrichment analysis along with single-cell transcriptome data analysis suggested that KNSTRN promoted cell cycle progression by regulating the expression of key cell cycle proteins. The overexpression and silencing of KNSTRN in vitro, respectively, promoted and inhibited the proliferation of breast cancer cells. The overexpression of KNSTRN enhanced the expression of key cell cycle regulators, including CDK4, CDK6, and cyclin D3, thereby accelerating the G1/S phase transition and leading to aberrant proliferation of breast cancer cells. In conclusion, our study demonstrates that KNSTRN functions as an oncogene in breast cancer by regulating immune response, promoting G1/S transition, and facilitating breast cancer cell proliferation. Moreover, KNSTRN has potential as a molecular biomarker for diagnostic and prognostic prediction in breast cancer.

Identification and validation of a novel necroptosis-related molecular signature to evaluate prognosis and immune features in breast cancer

Necroptosis has been shown to play an important role in the development of tumors. However, the characteristics of the necroptosis-related subtypes and the associated immune cell infiltration in the tumor microenvironment (TME) of breast cancer (BRCA) remain unclear. In this study, we identified three clusters related to necroptosis using the expression patterns of necroptosis-relevant genes (NRGs), and found that these three clusters had different clinicopathological features, prognosis and immune cell infiltration in the TME. Cluster 2 was characterized by less infiltration of immune cells in the TME and was associated with a worse prognosis. Then, a necroptosis risk score (NRS) composed of 14 NRGs was constructed using the least absolute shrinkage and selection operator regression (LASSO) Cox regression method. Based on NRS, all BRCA patients in the TCGA datasets were classified into a low-risk group and a high-risk group. Patients in the low-risk group were characterized by longer overall survival (OS), lower mutation burden, and higher infiltration level of immune cells in the TME. Moreover, the NRS was significantly associated with chemotherapeutic drug sensitivity. Finally, the knockdown of VDAC1 reduced the proliferation and migration of BRCA cells, and promoted cell death induced by necroptosis inducer. This study identified a novel necroptosis-related subtype of BRCA, and a comprehensive analysis of NRGs in BRCA revealed its potential roles in prognosis, clinicopathological features, TME, chemotherapy, tumor proliferation, and tumor necroptosis. These results may improve our understanding of NRGs in BRCA and provide a reference for developing individualized therapeutic strategies.

Combining the tumor-stroma ratio with tumor-infiltrating lymphocytes improves the prediction of pathological complete response in breast cancer patients

PURPOSE

The tumor-stroma ratio (TSR) is a common histological parameter that measures stromal abundance and is prognostic in breast cancer (BC). However, more evidence is needed on the predictive value of the TSR for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). The purpose of this study was to determine the importance of the TSR in predicting pCR in NAC settings.

METHOD

We evaluated the TSR on pretreatment biopsies of 912 BC patients from four independent Chinese hospitals and investigated the potential value of the TSR for predicting pCR. Meanwhile, stromal tumor-infiltrating lymphocytes (sTILs) were assessed, and we evaluated the predictive value of the combination of sTILs and TSR (TSRILs).

RESULTS

Patients with low stroma showed a higher pCR rate than those with high stroma among the four independent hospitals, and in multivariate analysis, the TSR was proven to be an independent predictor for pCR to NAC with an odds ratio of 1.945 (95% CI 1.230-3.075, P = 0.004). Moreover, we found that TSRILs could improve the area under the curve (AUC) for predicting pCR from 0.750 to 0.785 (P = 0.039); especially in HER2-negative BCs, the inclusion of TSRILs increased the AUC from 0.801 to 0.835 in the discovery dataset (P = 0.048) and 0.734 to 0.801 in the validation dataset (P = 0.003).

CONCLUSION

TSR and sTILs can be easily measured in pathological routines and provide predictive information without additional cost; with more evidence from clinical trials, TSRILs could be a candidate to better stratify patients in NAC settings.

ForestSubtype: a cancer subtype identifying approach based on high-dimensional genomic data and a parallel random forest

BACKGROUND

Cancer subtype classification is helpful for personalized cancer treatment. Although, some approaches have been developed to classifying caner subtype based on high dimensional gene expression data, it is difficult to obtain satisfactory classification results. Meanwhile, some cancers have been well studied and classified to some subtypes, which are adopt by most researchers. Hence, this priori knowledge is significant for further identifying new meaningful subtypes.

RESULTS

In this paper, we present a combined parallel random forest and autoencoder approach for cancer subtype identification based on high dimensional gene expression data, ForestSubtype. ForestSubtype first adopts the parallel RF and the priori knowledge of cancer subtype to train a module and extract significant candidate features. Second, ForestSubtype uses a random forest as the base module and ten parallel random forests to compute each feature weight and rank them separately. Then, the intersection of the features with the larger weights output by the ten parallel random forests is taken as our subsequent candidate features. Third, ForestSubtype uses an autoencoder to condenses the selected features into a two-dimensional data. Fourth, ForestSubtype utilizes k-means++ to obtain new cancer subtype identification results. In this paper, the breast cancer gene expression data obtained from The Cancer Genome Atlas are used for training and validation, and an independent breast cancer dataset from the Molecular Taxonomy of Breast Cancer International Consortium is used for testing. Additionally, we use two other cancer datasets for validating the generalizability of ForestSubtype. ForestSubtype outperforms the other two methods in terms of the distribution of clusters, internal and external metric results. The open-source code is available at https://github.com/lffyd/ForestSubtype .

CONCLUSIONS

Our work shows that the combination of high-dimensional gene expression data and parallel random forests and autoencoder, guided by a priori knowledge, can identify new subtypes more effectively than existing methods of cancer subtype classification.

The clinical significance of cyclin B1 (CCNB1) in invasive breast cancer with emphasis on its contribution to lymphovascular invasion development

BACKGROUND

Lymphovascular invasion (LVI) is regulated through complex molecular mechanisms. Cyclin B1 (CCNB1) was previously determined as being associated with LVI using large cohorts of breast cancer (BC) and artificial neural network (ANN) technique. In this study, we aimed to assess the association between CCNB1 and LVI, other clinicopathological and other LVI-related biomarkers at the molecular (RNA transcriptomic) and proteomic levels in BC.

METHODS

Two transcriptomic BC cohorts (n = 2834) were used to assess the association between the expression of CCNB1 at the mRNA level and clinicopathological characteristics and patient outcome. Tissue microarrays (TMAs) from a well-characterised BC cohort (n = 2480) with long-term outcome were also used to assess the clinical significance of CCNB1 protein expression using immunohistochemistry.

RESULTS

High CCNB1 mRNA expression was associated with aggressive tumour behaviour, including LVI, larger size, higher tumour grade, high lymph nodal stage, hormonal receptor negativity, HER2 positivity and poor clinical outcome (all p < 0.0001). Similarly, high CCNB1 protein expression was associated with higher tumour grade, hormonal receptor negativity and HER2 positivity (all p < 0.0001). Additionally, there was a significant association between CCNB1- and LVI-related biomarkers including N-cadherin, P-cadherin and TWIST2 at the transcriptomic and proteomic level. Multivariate analysis revealed that CCNB1 was an independent predictor of shorter BC-specific survival (HR = 1.3; 95% CI 1.2-1.5; p = 0.010).

CONCLUSION

CCNB1 is a key gene associated with LVI in BC and has prognostic value. More functional studies are warranted to unravel the mechanistic role of CCNB1 in the development of LVI.

CCHCR1-astrin interaction promotes centriole duplication through recruitment of CEP72

BACKGROUND

The centrosome is one of the most important non-membranous organelles regulating microtubule organization and progression of cell mitosis. The coiled-coil alpha-helical rod protein 1 (CCHCR1, also known as HCR) gene is considered to be a psoriasis susceptibility gene, and the protein is suggested to be localized to the P-bodies and centrosomes in mammalian cells. However, the exact cellular function of HCR and its potential regulatory role in the centrosomes remain unexplored.

RESULTS

We found that HCR interacts directly with astrin, a key factor in centrosome maturation and mitosis. Immunoprecipitation assays showed that the coiled-coil region present in the C-terminus of HCR and astrin respectively mediated the interaction between them. Astrin not only recruits HCR to the centrosome, but also protects HCR from ubiquitin-proteasome-mediated degradation. In addition, depletion of either HCR or astrin significantly reduced centrosome localization of CEP72 and subsequent MCPH proteins, including CEP152, CDK5RAP2, and CEP63. The absence of HCR also caused centriole duplication defects and mitotic errors, resulting in multipolar spindle formation, genomic instability, and DNA damage.

CONCLUSION

We conclude that HCR is localized and stabilized at the centrosome by directly binding to astrin. HCR are required for the centrosomal recruitment of MCPH proteins and centriolar duplication. Both HCR and astrin play key roles in keeping normal microtubule assembly and maintaining genomic stability.

SPAG5 as a novel biomarker and potential therapeutic target via regulating AKT pathway in multiple myeloma

SPAG5, as a spindle-associated protein in mitosis, has been observed to have oncogenic activities in solid tumors. Here, we identified that SPAG5 expression was correlated with the deterioration of plasma cell malignancy and SPAG5 overexpression (OE) predicted unfavorable outcomes in multiple myeloma (MM). SPAG5 knockdown led to anti-MM effects in MM cell lines and animal xenograft models by regulating cell growth and apoptosis. Furthermore, gene set enrichment analysis (GSEA) revealed that PI3K/AKT/mTOR pathway was enriched in MM samples with highly expressed SPAG5 from GSE datasets. There was a concurrent downregulation of phosphorylation levels in the AKT/mTOR pathway. Yet OE of SPAG5 could restore the cell growth and p-AKT levels in MM cells after treatment with the AKT inhibitor MK2206. Taken together, SPAG5 could serve as a novel biomarker, and targeting the SPAG5 might have therapeutic potential in MM.

Construction of long non-coding RNA- and microRNA-mediated competing endogenous RNA networks in alcohol-related esophageal cancer

The current study aimed to explore the lncRNA–miRNA–mRNA networks associated with alcohol-related esophageal cancer (EC). RNA-sequencing and clinical data were downloaded from The Cancer Genome Atlas and the differentially expressed genes (DEGs), long non-coding RNAs (lncRNAs, DELs), and miRNAs (DEMs) in patients with alcohol-related and non-alcohol-related EC were identified. Prognostic RNAs were identified by performing Kaplan–Meier survival analyses. Weighted gene co-expression network analysis was employed to build the gene modules. The lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) networks were constructed based on our in silico analyses using data from miRcode, starBase, and miRTarBase databases. Functional enrichment analysis was performed for the genes in the identified ceRNA networks. A total of 906 DEGs, 40 DELs, and 52 DEMs were identified. There were eight lncRNAs and miRNAs each, including ST7-AS2 and miR-1269, which were significantly associated with the survival rate of patients with EC. Of the seven gene modules, the blue and turquoise modules were closely related to disease progression; the genes in this module were selected to construct the ceRNA networks. SNHG12–miR-1–ST6GAL1, SNHG3–miR-1–ST6GAL1, SPAG5-AS1–miR-133a–ST6GAL1, and SNHG12–hsa-miR-33a–ST6GA interactions, associated with the N-glycan biosynthesis pathway, may have key roles in alcohol-related EC. Thus, the identified biomarkers provide a novel insight into the molecular mechanism of alcohol-related EC.

CLUH controls astrin-1 expression to couple mitochondrial metabolism to cell cycle progression

Proliferating cells undergo metabolic changes in synchrony with cell cycle progression and cell division. Mitochondria provide fuel, metabolites, and ATP during different phases of the cell cycle, however it is not completely understood how mitochondrial function and the cell cycle are coordinated. CLUH (clustered mitochondria homolog) is a post-transcriptional regulator of mRNAs encoding mitochondrial proteins involved in oxidative phosphorylation and several metabolic pathways. Here, we show a role of CLUH in regulating the expression of astrin, which is involved in metaphase to anaphase progression, centrosome integrity, and mTORC1 inhibition. We find that CLUH binds both the SPAG5 mRNA and its product astrin, and controls the synthesis and the stability of the full-length astrin-1 isoform. We show that CLUH interacts with astrin-1 specifically during interphase. Astrin-depleted cells show mTORC1 hyperactivation and enhanced anabolism. On the other hand, cells lacking CLUH show decreased astrin levels and increased mTORC1 signaling, but cannot sustain anaplerotic and anabolic pathways. In absence of CLUH, cells fail to grow during G1, and progress faster through the cell cycle, indicating dysregulated matching of growth, metabolism, and cell cycling. Our data reveal a role of CLUH in coupling growth signaling pathways and mitochondrial metabolism with cell cycle progression.

Epigenome erosion and SOX10 drive neural crest phenotypic mimicry in triple-negative breast cancer

Intratumoral heterogeneity is caused by genomic instability and phenotypic plasticity, but how these features co-evolve remains unclear. SOX10 is a neural crest stem cell (NCSC) specifier and candidate mediator of phenotypic plasticity in cancer. We investigated its relevance in breast cancer by immunophenotyping 21 normal breast and 1860 tumour samples. Nuclear SOX10 was detected in normal mammary luminal progenitor cells, the histogenic origin of most TNBCs. In tumours, nuclear SOX10 was almost exclusive to TNBC, and predicted poorer outcome amongst cross-sectional (p = 0.0015, hazard ratio 2.02, n = 224) and metaplastic (p = 0.04, n = 66) cases. To understand SOX10’s influence over the transcriptome during the transition from normal to malignant states, we performed a systems-level analysis of co-expression data, de-noising the networks with an eigen-decomposition method. This identified a core module in SOX10’s normal mammary epithelial network that becomes rewired to NCSC genes in TNBC. Crucially, this reprogramming was proportional to genome-wide promoter methylation loss, particularly at lineage-specifying CpG-island shores. We propose that the progressive, genome-wide methylation loss in TNBC simulates more primitive epigenome architecture, making cells vulnerable to SOX10-driven reprogramming. This study demonstrates potential utility for SOX10 as a prognostic biomarker in TNBC and provides new insights about developmental phenotypic mimicry—a major contributor to intratumoral heterogeneity.

Ulcerated melanoma: Systems biology evidence of inflammatory imbalance towards pro-tumourigenicity

Microscopic ulceration is an independent predictor of melanoma death. Here, we used systems biology to query the role of host and tumour-specific processes in defining the phenotype. Albumin level as a measure of systemic inflammation was predictive of fewer tumour-infiltrating lymphocytes and poorer survival in the Leeds Melanoma Cohort. Ulcerated melanomas were thicker and more mitotically active (with corresponding transcriptomic upregulated cell cycle pathways). Sequencing identified tumoural p53 and APC mutations, and TUBB2B amplification as associated with the phenotype. Ulcerated tumours had perturbed expression of cytokine genes, consistent with protumourigenic inflammation and histological and transcriptomic evidence for reduced adaptive immune cell infiltration. Pathway/network analysis of multiomic data using neural networks highlighted a role for the β-catenin pathway in the ulceration, linking genomic changes in the tumour to immunosuppression and cell proliferation. In summary, the data suggest that ulceration is in part associated with genomic changes but that host factors also predict melanoma death with evidence of reduced immune responses to the tumour.

Downregulation of sperm-associated antigen 5 inhibits melanoma progression by regulating forkhead box protein M1/A disintegrin and metalloproteinase 17/NOTCH1 signaling

Sperm-associated antigen 5 (SPAG5) has been identified as a driver in several type of cancers. In this study, we aimed to reveal the role of SPAG5 in melanoma and clarify whether FOXM1 (forkhead box protein M1) /ADAM17 (A disintegrin and metalloproteinase 17) /NOTCH1 signaling was involved. The expression of SPAG5 in malignant melanoma (MM) tissues and matched normal tissues was detected using qRT-PCR, immunohistochemistry and Western blotting. Cell viability was tested using CCK-8 (Cell Count Kit-8), colony formation and EdU staining. Cell migration and epithelial to mesenchymal transition (EMT) were measured using transwell chambers and immunofluorescent staining. Cell cycle distribution and tumorigenesis were assessed by flow cytometry and in vivo tumor-bearing experiments, respectively. The results demonstrated that the expression of SPAG5 was increased in MM tissues and cells. Downregulation of SPAG5 inhibited cell viability, migration, invasion and EMT, and induced a G1-phase arrest. In addition, downregulation of SPAG5 decreased the expression of FOXM1, thereafter inhibiting the expression of ADAM17, NOTCH1 and HES1. Furthermore, deletion of SPAG5 expression decreased the tumorigenesis of MM A375 cells. In conclusion, this study demonstrated that SPAG5 was overexpressed in MM. Downregulation of SPAG5 repressed MM cell growth and EMT, which might be induced by inactivation of the FOXM1/ADAM17/NOTCH1 signaling.

SPAG5 Is Involved in Human Gliomagenesis Through the Regulation of Cell Proliferation and Apoptosis

Background

Glioma is the most frequent malignant primary brain tumor in adults.

Objective

To explore the role of sperm-associated antigen 5 (SPAG5) in glioma.

Methods

The association between SPAG5 expression and clinical features was investigated based on The Cancer Genome Atlas (TCGA) datasets. The function of SPAG5 in glioma was analyzed using U87 and U251 cells. Knockdown glioma cells were constructed by shRNA interference. qRT-PCR and Western blotting were used to measure the expression of SPAG5 and Cadherin 2 (CDH2). Cell proliferation and apoptosis were measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, caspase 3/7 assay, and high-content screening (HCS) proliferation analysis and colony formation assay. Transwell assays and wound-healing assays were used to investigate cell migration and invasion.

Results

The increased expression of SPAG5 was correlated with poor outcomes in glioma patients. Knocking down SPAG5 could inhibit the proliferation and colony formation and promoted the apoptosis of glioma cells. Knocking down SPAG5 could also inhibit cell migration and invasion and the expression of CDH2. Overexpression of CDH2 with SPAG5 depletion could restore the proliferation and inhibit the apoptosis of glioma cells, which also promoted cell migration and invasion.

Conclusions

SPAG5 is a promising prognostic factor and potential therapeutic target for clinical intervention in glioma.

An Immune-Associated Genomic Signature Effectively Predicts Pathologic Complete Response to Neoadjuvant Paclitaxel and Anthracycline-Based Chemotherapy in Breast Cancer

Breast cancer is now the leading cause of cancer morbidity and mortality among women worldwide. Paclitaxel and anthracycline-based neoadjuvant chemotherapy is widely used for the treatment of breast cancer, but its sensitivity remains difficult to predict for clinical use. In our study, a LASSO logistic regression method was applied to develop a genomic classifier for predicting pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer. The predictive accuracy of the signature classifier was further evaluated using four other independent test sets. Also, functional enrichment analysis of genes in the signature was performed, and the correlations between the prediction score of the signature classifier and immune characteristics were explored. We found a 25-gene signature classifier through the modeling, which showed a strong ability to predict pCR to neoadjuvant chemotherapy in breast cancer. For T/FAC-based training and test sets, and a T/AC-based test set, the AUC of the signature classifier is 1.0, 0.9071, 0.9683, 0.9151, and 0.7350, respectively, indicating that it has good predictive ability for both T/FAC and T/AC schemes. The multivariate model showed that 25-gene signature was far superior to other clinical parameters as independent predictor. Functional enrichment analysis indicated that genes in the signature are mainly enriched in immune-related biological processes. The prediction score of the classifier was significantly positively correlated with the immune score. There were also significant differences in immune cell types between pCR and residual disease (RD) samples. Conclusively, we developed a 25-gene signature classifier that can effectively predict pCR to paclitaxel and anthracycline-based neoadjuvant chemotherapy in breast cancer. Our study also suggests that the immune ecosystem is actively involved in modulating clinical response to neoadjuvant chemotherapy and is beneficial to patient outcomes.

Deep learning-based predictive biomarker of pathological complete response to neoadjuvant chemotherapy from histological images in breast cancer

Background

Pathological complete response (pCR) is considered a surrogate endpoint for favorable survival in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Predictive biomarkers of treatment response are crucial for guiding treatment decisions. With the hypothesis that histological information on tumor biopsy images could predict NAC response in breast cancer, we proposed a novel deep learning (DL)-based biomarker that predicts pCR from images of hematoxylin and eosin (H&E)-stained tissue and evaluated its predictive performance.

Methods

In total, 540 breast cancer patients receiving standard NAC were enrolled. Based on H&E-stained images, DL methods were employed to automatically identify tumor epithelium and predict pCR by scoring the identified tumor epithelium to produce a histopathological biomarker, the pCR-score. The predictive performance of the pCR-score was assessed and compared with that of conventional biomarkers including stromal tumor-infiltrating lymphocytes (sTILs) and subtype.

Results

The pCR-score derived from H&E staining achieved an area under the curve (AUC) of 0.847 in predicting pCR directly, and achieved accuracy, F1 score, and AUC of 0.853, 0.503, and 0.822 processed by the logistic regression method, respectively, higher than either sTILs or subtype; a prediction model of pCR constructed by integrating sTILs, subtype and pCR-score yielded a mean AUC of 0.890, outperforming the baseline sTIL-subtype model by 0.051 (0.839, P  =  0.001).

Conclusion

The DL-based pCR-score from histological images is predictive of pCR better than sTILs and subtype, and holds the great potentials for a more accurate stratification of patients for NAC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03020-z.

Comprehensive proteomic analysis reveals distinct functional modules associated with skull base and supratentorial meningiomas and perturbations in collagen pathway components

Meningiomas are brain tumors that originate from the meninges and has been primarily classified into three grades by the current WHO guidelines. Although widely prevalent and can be managed by surgery there are instances when the tumors are located in difficult regions. This results in considerable challenges for complete surgical resection and further clinical management. While the genetic signature of the skull base tumors is now known to be different from the non-skull base tumors, there is a lack of information at the functional aspects of these tumors at the proteomic level. Thus, the current study thereby aims to obtain mechanistic insights between the two radiologically distinct groups of meningiomas, namely the skull base & supratentorial (non-skull base-NSB) regions. We have employed a comprehensive mass spectrometry-based label-free quantitative proteomic analysis in Skull base and supratentorial meningiomas. Further, we have used an Artificial Neural Networking employing a sparse Multilayer perceptron (MLP) architecture to predict protein concordance. A patient-derived spectral library has been employed for a novel peptide-level validation of proteins that are specific to the radiological regions using the SRM assay based targeted proteomics approach. The comprehensive proteomics enabled the identification of nearly 4000 proteins with high confidence (1%FDR ≥ 2 unique peptides) among which 170 proteins were differentially abundant in Skull base vs Supratentorial tumors (p-value ≤0.05). In silico analysis enabled mapping of the major alterations and hinted towards an overall perturbation of extracellular matrix and collagen biosynthesis components in the non-skull base meningiomas and a prominent perturbation of molecular trafficking in the skull base meningiomas. Therefore, this study has yielded novel insights into the functional association of the proteins that are differentially abundant in the two radiological subgroups. SIGNIFICANCE: In the current study, we have performed label-free proteomic analysis on fresh frozen tissue of 14 Supratentorial (NSB) and 7 Skull base meningiomas to assess perturbations in the global proteome, we have further employed an in-depth in silico analysis to map the pathways that have enabled functional mapping of the differentially abundant proteins in the Skull base and Supratentorial tumors. The findings from the above were also subjected to a machine learning-based neural networking to find out the proteins that have the most concordance of occurrence to determine the most influential proteins of the network. We further validated the differential abundance of identified protein markers in a larger patient cohort of Skull base and Supratentorial employing targeted proteomics approach to validate key protein candidates emerging from ours and other recent studies. The previous studies that have explored the skull base and convexity meningiomas have been able to reveal alterations in the genetic mutations in these tumor types. However, there are not many studies that have explored the functional aspects of these tumors, especially at the proteome level. We have attempted for the first time to map the functional modules associated with altered proteins in these tumors and have been able to identify that there is a possibility that the Skull base meningiomas to be considerably different from the Non-skull base (NSB) tumors in terms of the perturbed pathways. Our study employed global as well as targeted proteomics to examine the proteomic alterations in these two tumor groups. The study indicates that proteins that were more abundant in Skull base tumors were part of molecular transport components, non-skull base proteins majorly mapped to the components of extracellular matrix remodeling pathways. In conclusion, this study substantiates the distinction in the proteomic signatures in the skull base and supratentorial meningiomas paving way for further investigation of the identified markers for determining if some of these proteins can be used for therapeutic interventions for cases that pose considerable challenges for complete resection.

Fe-doped chrysotile nanotubes containing siRNAs to silence SPAG5 to treat bladder cancer

BACKGROUND

For certain human cancers, sperm associated antigen 5 (SPAG5) exerts important functions for their development and progression. However, whether RNA interference (RNAi) targeting SPAG5 has antitumor effects has not been determined clinically.

RESULTS

The results indicated that Fe-doped chrysotile nanotubes (FeSiNTs) with a relatively uniform outer diameter (15-25 nm) and inner diameter (7-8 nm), and a length of several hundred nanometers, which delivered an siRNA against the SPAG5 oncogene (siSPAG5) efficiently. The nanomaterials were designed to prolong the half-life of siSPAG5 in blood, increase tumor cell-specific uptake, and maximize the efficiency of SPAG5 silencing. In vitro, FeSiNTs carrying siSPAG5 inhibited the growth, migration, and invasion of bladder cancer cells. In vivo, the FeSiNTs inhibited growth and metastasis in three models of bladder tumors (a tail vein injection lung metastatic model, an in-situ bladder cancer model, and a subcutaneous model) with no obvious toxicities. Mechanistically, we showed that FeSiNTs/siSPAG5 repressed PI3K/AKT/mTOR signaling, which suppressed the growth and progression of tumor cells.

CONCLUSIONS

The results highlight that FeSiNTs/siSPAG5 caused no activation of the innate immune response nor any systemic toxicity, indicating the possible therapeutic utility of FeSiNTs/siSPAG5 to deliver siSPAG5 to treat bladder cancer.

MiR-133a-3p attenuates resistance of non-small cell lung cancer cells to gefitinib by targeting SPAG5

Background

Gefitinib is an epidermal growth factor receptor tyrosine kinase inhibitor (EGFR‐TKI), clinically used to treat patients with non‐small cell lung cancer driven by EGFR mutations. Unfortunately, EGFR‐TKI resistance has become a clinical problem for the effective treatment of NSCLC patients. The purpose of this study was to explore the effect and mechanism of miR‐133a‐3p on the gefitinib sensitivity of NSCLC cells.

Methods

The gefitinib‐resistant PC9 (PC9/GR) cells were established through repeated long‐term exposure to gefitinib for half a year. Then, PC9/GR cells were transfected with miR‐133a‐3p mimics and PC9 cells were transfected with miR‐133a‐3p inhibitors to increase or decrease the expression of miR‐133a‐3p. CCK‐8 assay, colony formation assay, and caspase‐3 activity assay were employed to detect cell resistance to gefitinib. Quantitative real‐time PCR and Western blotting were used to evaluate the levels of miR‐133a‐3p, SPAG5, and other related genes. Starbase database was used to predict the target gene of miR‐133a‐3p and the prognosis of NSCLC patients. Target gene of miR‐133a‐3p was verified through dual‐luciferase reporter gene assay.

Results

MiR‐133a‐3p was significantly downregulated in gefitinib‐resistant cell line PC9/GR vs. gefitinib‐sensitive cell line PC9. Overexpression of miR‐133a‐3p increased the sensitivity of NSCLC cells to gefitinib and vice versa. Furthermore, SPAG5 is an important target gene of miR‐133a‐3p, and SPAG5 can reverse miR‐133a‐3p‐mediated gefitinib sensitivity of NSCLC cells.

Conclusions

These findings indicated that miR‐133a‐3p/SPAG5 axis played a vital role in acquired resistance to gefitinib in NSCLC cells, and miR‐133a‐3p may represent a potential therapeutic strategy for the treatment of human NSCLC.

Aberrant transcriptional and post-transcriptional regulation of SPAG5, a YAP-TAZ-TEAD downstream effector, fuels breast cancer cell proliferation

Sperm-associated antigen 5 (SPAG5) is an important driver of the cell mitotic spindle required for chromosome segregation and progression into anaphase. SPAG5 has been identified as an important proliferation marker and chemotherapy-sensitivity predictor, especially in estrogen receptor-negative breast cancer subtypes. Here, we report that SPAG5 is a direct target of miR-10b-3p, and its aberrantly high expression associates with poor disease-free survival in two large cohorts of breast cancer patients. SPAG5 depletion strongly impaired cancer cell cycle progression, proliferation, and migration. Interestingly, high expression of SPAG5 pairs with a YAP/TAZ-activated signature in breast cancer patients. Reassuringly, the depletion of YAP, TAZ, and TEAD strongly reduced SPAG5 expression and diminished its oncogenic effects. YAP, TAZ coactivators, and TEAD transcription factors are key components of the Hippo signaling pathway involved in tumor initiation, progression, and metastasis. Furthermore, we report that SPAG5 is a direct transcriptional target of TEAD/YAP/TAZ, and pharmacological targeting of YAP and TAZ severely reduces SPAG5 expression. Collectively, our data uncover an oncogenic feedback loop, comprising miR-10b-3p, SPAG5, and YAP/TAZ/TEAD, which fuels the aberrant proliferation of breast cancer.

High expression of sperm-associated antigen 5 correlates with poor survival in ovarian cancer

OBJECTIVES

Sperm-associated antigen 5 (SPAG5), a spindle-binding protein, regulates the process of mitosis. The present study focused on the relationship between SPAG5 expression and the clinicopathological characteristics and prognosis of ovarian cancer.

METHODS

First, we used the Gene Expression Omnibus (GEO) database to analyze SPAG5 expression in ovarian cancer and its clinical relevance. Subsequently, qPCR test was used to detect SPAG5 mRNA expression in 20 cases of ovarian cancer. The expression of SPAG5 protein in a tissue microarray containing 102 cases of ovarian cancer was detected by immunohistochemistry. Cox regression and Kaplan-Meier survival analyses were performed to identify the prognostic factors for the 102 ovarian cancer patients.

RESULTS

In the GEO datasets, SPAG5 mRNA expression was significantly higher in ovarian cancer tissues than that in normal ovarian tissues (P < 0.001). qPCR and immunohistochemistry showed that SPAG5 expression in ovarian cancer tissues was significantly higher than that in paracancerous tissues (P = 0.002, P < 0.001). The high expression of SPAG5 in ovarian cancer was correlated with histological type (P = 0.009), lymph node metastasis (P = 0.001), distant metastasis (P = 0.001), TNM stage (P = 0.001), and prognosis (P = 0.001). The Kaplan-Meier curve indicated that rates of disease-free survival (DFS) and overall survival (OS) were even lower in patients with high SPAG5 expression. Multivariate analysis showed that SPAG5 expression (P = 0.001) and TNM staging (P = 0.002) were independent prognostic factors for the DFS of ovarian cancer.

CONCLUSIONS

These results suggest that high SPAG5 expression was correlated with multiple clinicopathological features of ovarian cancer and can be used as an evaluation indicator for a poor ovarian cancer prognosis.

A novel signature predicts recurrence risk and therapeutic response in breast cancer patients

Acetylserotonin O-methyltransferase (ASMT) is a key enzyme in the synthesis of melatonin. Although melatonin has been shown to exhibit anticancer activity and prevents endocrine resistance in breast cancer, the role of ASMT in breast cancer progression remains unclear. In this retrospective study, we analyzed gene expression profiles in 27 data sets on 7244 patients from 11 countries. We found that ASMT expression was significantly reduced in breast cancer tumors relative to healthy tissue. Among breast cancer patients, those with higher levels of ASMT expression had better relapse-free survival outcomes and longer metastasis-free survival times. Following treatment with tamoxifen, patients with greater ASMT expression experienced longer periods before relapse or distance recurrence. Motivated by these results, we devised an ASMT gene signature that can correctly identify low-risk cases with a sensitivity and specificity of 0.997 and 0.916, respectively. This signature was robustly validated using 23 independent breast cancer mRNA array data sets from different platforms (consisting of 5800 patients) and an RNAseq data set from TCGA (comprising 1096 patients). Intriguingly, patients who are classified as high-risk by the signature benefit from adjuvant chemotherapy, and those with grade II tumors who are classified as low-risk exhibit improved overall survival and distance relapse-free outcomes following endocrine therapy. Together, our findings more clearly elucidate the roles of ASMT, provide strategies for improving the efficacy of tamoxifen treatment and help to identify those patients who may maximally benefit from adjuvant or endocrine therapies.

The androgen receptor is a tumor suppressor in estrogen receptor-positive breast cancer

The role of the androgen receptor (AR) in estrogen receptor (ER)-α-positive breast cancer is controversial, constraining implementation of AR-directed therapies. Using a diverse, clinically relevant panel of cell-line and patient-derived models, we demonstrate that AR activation, not suppression, exerts potent antitumor activity in multiple disease contexts, including resistance to standard-of-care ER and CDK4/6 inhibitors. Notably, AR agonists combined with standard-of-care agents enhanced therapeutic responses. Mechanistically, agonist activation of AR altered the genomic distribution of ER and essential co-activators (p300, SRC-3), resulting in repression of ER-regulated cell cycle genes and upregulation of AR target genes, including known tumor suppressors. A gene signature of AR activity positively predicted disease survival in multiple clinical ER-positive breast cancer cohorts. These findings provide unambiguous evidence that AR has a tumor suppressor role in ER-positive breast cancer and support AR agonism as the optimal AR-directed treatment strategy, revealing a rational therapeutic opportunity.

A novel prognostic two-gene signature for triple negative breast cancer

The absence of a robust risk stratification tool for triple negative breast cancer (TNBC) underlies imprecise and nonselective treatment of these patients with cytotoxic chemotherapy. This study aimed to interrogate transcriptomes of TNBC resected samples using next generation sequencing to identify novel biomarkers associated with disease outcomes. A subset of cases (n = 112) from a large, well-characterized cohort of primary TNBC (n = 333) were subjected to RNA-sequencing. Reads were aligned to the human reference genome (GRCH38.83) using the STAR aligner and gene expression quantified using HTSEQ. We identified genes associated with distant metastasis-free survival and breast cancer-specific survival by applying supervised artificial neural network analysis with gene selection to the RNA-sequencing data. The prognostic ability of these genes was validated using the Breast Cancer Gene-Expression Miner v4. 0 and Genotype 2 outcome datasets. Multivariate Cox regression analysis identified a prognostic gene signature that was independently associated with poor prognosis. Finally, we corroborated our results from the two-gene prognostic signature by their protein expression using immunohistochemistry. Artificial neural network identified two gene panels that strongly predicted distant metastasis-free survival and breast cancer-specific survival. Univariate Cox regression analysis of 21 genes common to both panels revealed that the expression level of eight genes was independently associated with poor prognosis (p < 0.05). Adjusting for clinicopathological factors including patient's age, grade, nodal stage, tumor size, and lymphovascular invasion using multivariate Cox regression analysis yielded a two-gene prognostic signature (ACSM4 and SPDYC), which was associated with poor prognosis (p < 0.05) independent of other prognostic variables. We validated the protein expression of these two genes, and it was significantly associated with patient outcome in both independent and combined manner (p < 0.05). Our study identifies a prognostic gene signature that can predict prognosis in TNBC patients and could potentially be used to guide the clinical management of TNBC patients.

A nine-lncRNA signature predicts distant relapse-free survival of HER2-negative breast cancer patients receiving taxane and anthracycline-based neoadjuvant chemotherapy

Multi-gene prognostic signatures of long non-coding RNAs (lncRNAs) provide new insights into mechanisms of HER2-negative breast cancer development and progression, and predict distant relapse-free survival (DRFS) of patients receiving taxane and anthracycline-based neoadjuvant chemotherapy. The aim of this study was to develop such a multi-lncRNAs signature. Optimal multiple candidate signature lncRNAs associated with DRFS were firstly identified by a univariate Cox proportional hazard regression survival analysis and a robust likelihood-based survival analysis of the GEO dataset GSE25055. A nine-lncRNA prognostic risk score model Risk Score = 0.0289 × EXP_LOC100507388 - 0.0814 × EXP_LINC00094 - 0.2422 × EXP_SMG7-AS1 - 0.2433 × EXP_PP14571 + 0.4690 × EXP_ASAP1-IT1 - 0.2483 × EXP_LOC103344931 - 0.2464 × EXP_FAM182A + 0.3349 × EXP_HCG26 - 0.0216 × EXP_LINC00963 was built according to the coefficients of multivariate survival analysis of the association between the candidate lncRNAs and survival. EXP_lncRNA was the standardized log2-transformed expression level of the gene. According to this model, higher scores predicted lower survival probability. The area under Receiver operating characteristic (ROC) curve (AUC) was 0.777 to 0.823 from 1- to 7- year survival rate. The model and its individual lncRNAs differentiated survival probability between the higher scores (expression) and the lower scores (expression). The nine-lncRNA signature had the robust prognostic power compared with ER, PR, tumor size (T), lymph node invasion (N), TNM stage, pathologic response, chemosensitivity prediction and PAM50 signature. These results were consistent with those based on the GEO dataset GSE25065. The predictive nomograms integrating both the nine-lncRNA signature classifier and clinical-pathological risk factors were robust in predicting 1-, 3- and 5- year survival probabilities. These results supported that the nine-lncRNA signature was a robust and effective model in predicting DRFS of patients with HER2-negative breast cancer following taxane and anthracycline-based neoadjuvant chemotherapy.

A 38-gene model comprised of key TET2-associated genes shows additive utility to high-risk prostate cancer cases in the prognostication of biochemical recurrence

BACKGROUND

Early treatment of patients at risk for developing aggressive prostate cancer is able to delay metastasis and reduce mortality; as such, up-front identification of these patients is critical. Several risk classification systems, including CAPRA-S, are currently used for disease prognostication. However, high-risk patients identified by these systems can still exhibit wide-ranging disease outcomes, leading to overtreatment of some patients in this group.

METHODS

The master methylation regulator TET2 is downregulated in prostate cancer, where its loss is linked to aggressive disease and poor outcome. Using a random forest strategy, we developed a model based on the expression of 38 genes associated with TET2 utilizing 100 radical prostatectomy samples (training cohort) with a 49% biochemical recurrence rate. This 38-gene model was comprised of both upregulated and downregulated TET2-associated genes with a binary outcome, and was further assessed in an independent validation (n = 423) dataset for association with biochemical recurrence.

RESULTS

38-gene model status was able to correctly identify patients exhibiting recurrence with 81.4% sensitivity in the validation cohort, and added significant prognostic utility to the high-risk CAPRA-S classification group. Patients considered high-risk by CAPRA-S with negative 38-gene model status exhibited no statistically significant difference in time to recurrence from low-risk CAPRA-S patients, indicating that the expression of TET2-associated genes is able to separate truly high-risk cases from those which have a more benign disease course.

CONCLUSIONS

The 38-gene model may hold potential in determining which patients would truly benefit from aggressive treatment course, demonstrating a novel role for genes linked to TET2 in the prognostication of PCa and indicating the importance of TET2 dysregulation among high-risk patient groups.

Astrin: A Key Player in Mitosis and Cancer

Astrin, which is a spindle-associated protein, was found to be closely related to mitotic spindle formation and maintenance. It interacts with other spindle-related proteins to play a key role in maintaining the attachment of the kinetochore-microtubule and integrity of centrosomes and promoting the centriole duplication. In addition, Astrin was quite recently found to be abnormally highly expressed in a variety of cancers. Astrin promotes the development of cancer by participating in various molecular pathways and is considered as a potential prognostic and survival predictor.

SPAG5 is associated with unfavorable prognosis in patients with lung adenocarcinoma and promotes proliferation, motility and autophagy in A549 cells

Sperm-associated antigen 5 (SPAG5) is involved in the tumorigenesis of multiple cancer types. However, the role of SPAG5 during lung adenocarcinoma (LUAD) progression remains to be fully elucidated. In the present study, the expression of SPAG5 in tumor tissues of patients with LUAD from public cancer databases was analyzed using the online software Gene Expression Profiling Interactive Analysis and University of Alabama Cancer Database. The association of SPAG5 expression levels with the prognosis of patients with LUAD was analyzed using Kaplan-Meier Plotter. In addition, the role of SPAG5 in the LUAD cell line A549 was determined by knocking down its expression with specific small interfering RNA. The results demonstrated that SPAG5 expression was upregulated in LUAD tissues and its high expression was associated with unfavorable prognosis. Furthermore, in A549 cells, SPAG5 promoted proliferation, migration, invasion and autophagy, but inhibited apoptosis. The present results suggest that SPAG5 has an oncogenic role in LUAD and may be a potential prognostic predictor and therapeutic target for LUAD.

Comprehending Meningioma Signaling Cascades Using Multipronged Proteomics Approaches & Targeted Validation of Potential Markers

Meningiomas are one of the most prevalent primary brain tumors. Our study aims to obtain mechanistic insights of meningioma pathobiology using mass spectrometry-based label-free quantitative proteome analysis to identifying druggable targets and perturbed pathways for therapeutic intervention. Label-free based proteomics study was done from peptide samples of 21 patients and 8 non-tumor controls which were followed up with Phosphoproteomics to identify the kinases and phosphorylated components of the perturbed pathways. In silico approaches revealed perturbations in extracellular matrix remodeling and associated cascades. To assess the extent of influence of Integrin and PI3K-Akt pathways, we used an Integrin Linked Kinase inhibitor on patient-derived meningioma cell line and performed a transcriptomic analysis of the components. Furthermore, we designed a Targeted proteomics assay which to the best of our knowledge for very first-time enables identification of peptides from 54 meningioma patients via SRM assay to validate the key proteins emerging from our study. This resulted in the identification of peptides from CLIC1, ES8L2, and AHNK many of which are receptors and kinases and are difficult to be characterized using conventional approaches. Furthermore, we were also able to monitor transitions for proteins like NEK9 and CKAP4 which have been reported to be associated with meningioma pathobiology. We believe, this study can aid in designing peptide-based validation assays for meningioma patients as well as IHC studies for clinical applications.

Investigation of the SPAG5 gene expression and amplification related to the NuMA mRNA levels in breast ductal carcinoma

Background

The cell proliferative markers are very important in breast cancer. Since SPAG5 and NuMA proteins play a significant role in the mitosis regulatory network and cell division, we aimed to study their mRNA levels as well as SPAG5 gene amplification correlated to clinicopathological status in ductal carcinoma of the breast.

Methods

SPAG5 and NuMA gene expressions were investigated in 40 breast cancer tissues and normal adjacent tissues via real-time PCR. PUM1 was selected as the reference gene. QMF PCR method was applied to study SPAG5 gene amplification and AGBL2, BOD1L, and POR were designated as internal control genes. Gene amplification was determined by calculating a dosage quotient for each DNA fragment.

Results

Increased SPAG5 mRNA expression was detected in breast cancer tissues (p = 0.005) and related to tumor size. No significant difference was observed between NuMA gene expression level in tumor tissue and the normal adjacent tissue (p = 0.56). However, we observed that NuMA expression was significantly increased in ER-positive tumor tissues. There was no clear correlation pattern between SPAG5 and NuMA mRNA levels (r = 0.33). Seventeen percent of tissues showed complete amplification in SPAG5 gene fragments.

Conclusion

Our results were consistent with the previous publications regarding SPAG5 gene expression and amplification in breast cancer with an emphasis on the prominent role of this protein in tumor pathogenesis. Our results failed to yield any correlation between SPAG5 and NuMA mRNA levels which implies independence of these genes in breast cancer pathogenesis.

Resistance to Neoadjuvant Treatment in Breast Cancer: Clinicopathological and Molecular Predictors

Neoadjuvant Chemotherapy (NAC) in Breast Cancer (BC) has proved useful for the reduction in tumor burden prior to surgery, allowing for a more extensive breast preservation and the eradication of subjacent micrometastases. However, the impact on prognosis is highly dependent on the establishment of Pathological Complete Response (pCR), in particular for Triple Negative (TN) and Hormonal Receptor negative/Human Epidermal growth factor Receptor 2 positive (HR-/HER2+) subtypes. Several pCR predictors, such as PAM50, Integrative Cluster (IntClust), mutations in PI3KCA, or the Trastuzumab Risk model (TRAR), are useful molecular tools for estimating response to treatment and are prognostic. Major evolution events during BC NAC that feature the Residual Disease (RD) are the loss of HR and HER2, which are prognostic of bad outcome, and stemness and immune depletion-related gene expression aberrations. This dynamic nature of the determinants of response to BC NAC, together with the extensive heterogeneity of BC, raises the need to discern the individual and subtype-specific determinants of resistance. Moreover, refining the current approaches for a comprehensive monitoring of tumor evolution during treatment, RD, and eventual recurrences is essential for identifying new actionable alterations and the integral best management of the disease.

Transcriptomic insight into salinomycin mechanisms in breast cancer cell lines: synergistic effects with dasatinib and induction of estrogen receptor β

BACKGROUND

Tumors are heterogeneous in nature, composed of different cell populations with various mutations and/or phenotypes. Using a single drug to encounter cancer progression is generally ineffective. To improve the treatment outcome, multiple drugs of distinctive mechanisms but complementary anticancer activities (combination therapy) are often used to enhance antitumor efficacy and minimize the risk of acquiring drug resistance. We report here the synergistic effects of salinomycin (a polyether antibiotic) and dasatinib (a Src kinase inhibitor).

METHODS

Functionally, both drugs induce cell cycle arrest, intracellular reactive oxygen species (iROS) production, and apoptosis. We rationalized that an overlapping of the drug activities should offer an enhanced anticancer effect, either through vertical inhibition of the Src-STAT3 axis or horizontal suppression of multiple pathways. We determined the toxicity induced by the drug combination and studied the kinetics of iROS production by fluorescence imaging and flow cytometry. Using genomic and proteomic techniques, including RNA-sequencing (RNA-seq), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and Western Blot, we subsequently identified the responsible pathways that contributed to the synergistic effects of the drug combination.

RESULTS

Compared to either drug alone, the drug combination showed enhanced potency against MDA-MB-468, MDA-MB-231, and MCF-7 human breast cancer (BC) cell lines and tumor spheroids. The drug combination induces both iROS generation and apoptosis in a time-dependent manner, following a 2-step kinetic profile. RNA-seq data revealed that the drug combination exhibited synergism through horizontal suppression of multiple pathways, possibly through a promotion of cell cycle arrest at the G1/S phase via the estrogen-mediated S-phase entry pathway, and partially via the BRCA1 and DNA damage response pathway.

CONCLUSION

Transcriptomic analyses revealed for the first time, that the estrogen-mediated S-phase entry pathway partially contributed to the synergistic effect of the drug combination. More importantly, our studies led to the discoveries of new potential therapeutic targets, such as E2F2, as well as a novel drug-induced targeting of estrogen receptor β (ESR2) approach for triple-negative breast cancer treatment, currently lacking of targeted therapies.

Association of Sperm-Associated Antigen 5 and Treatment Response in Patients With Estrogen Receptor-Positive Breast Cancer

Importance

There is no proven test that can guide the optimal treatment, either endocrine therapy or chemotherapy, for estrogen receptor-positive breast cancer.

Objective

To investigate the associations of sperm-associated antigen 5 (SPAG5) transcript and SPAG5 protein expressions with treatment response in systemic therapy for estrogen receptor-positive breast cancer.

Design, Settings, and Participants

This retrospective cohort study included patients with estrogen receptor-positive breast cancer who received 5 years of adjuvant endocrine therapy with or without neoadjuvant anthracycline-based combination chemotherapy (NACT) derived from 11 cohorts from December 1, 1986, to November 28, 2019. The associations of SPAG5 transcript and SPAG5 protein expression with pathological complete response to NACT were evaluated, as was the association of SPAG5 mRNA expression with response to neoadjuvant endocrine therapy. The associations of distal relapse-free survival with SPAG5 transcript or SPAG5 protein expressions were analyzed. Data were analyzed from September 9, 2015, to November 28, 2019.

Main Outcomes and Measures

The primary outcomes were breast cancer-specific survival, distal relapse-free survival, pathological complete response, and clinical response. Outcomes were examined using Kaplan-Meier, multivariable logistic, and Cox regression models.

Results

This study included 12 720 women aged 24 to 78 years (mean [SD] age, 58.46 [12.45] years) with estrogen receptor-positive breast cancer, including 1073 women with SPAG5 transcript expression and 361 women with SPAG5 protein expression of locally advanced disease stage IIA through IIIC. Women with SPAG5 transcript and SPAG5 protein expressions achieved higher pathological complete response compared with those without SPAG5 transcript or SPAG5 protein expressions (transcript: odds ratio, 2.45 [95% CI, 1.71-3.51]; P < .001; protein: odds ratio, 7.32 [95% CI, 3.33-16.22]; P < .001). Adding adjuvant anthracycline chemotherapy to adjuvant endocrine therapy for SPAG5 mRNA expression in estrogen receptor-positive breast cancer was associated with prolonged 5-year distal relapse-free survival in patients without lymph node involvement (hazard ratio, 0.34 [95% CI, 0.14-0.87]; P = .03) and patients with lymph node involvement (hazard ratio, 0.35 [95% CI, 0.18-0.68]; P = .002) compared with receiving 5-year endocrine therapy alone. Mean (SD) SPAG5 transcript was found to be downregulated after 2 weeks of neoadjuvant endocrine therapy compared with pretreatment levels in 68 of 92 patients (74%) (0.23 [0.18] vs 0.34 [0.24]; P < .001).

Conclusions and Relevance

These findings suggest that SPAG5 transcript and SPAG5 protein expressions could be used to guide the optimal therapies for estrogen receptor-positive breast cancer. Retrospective and prospective clinical trials are warranted.

Predictors of Neoadjuvant Chemotherapy Response in Breast Cancer: A Review

Neoadjuvant chemotherapy (NAC) largely increases operative chances and improves prognosis of the local advanced breast cancer patients. However, no specific means have been invented to predict the therapy responses of patients receiving NAC. Therefore, we focus on the alterations of tumor tissue-related microenvironments such as stromal tumor-infiltrating lymphocytes status, cyclin-dependent kinase expression, non-coding RNA transcription or other small molecular changes, in order to detect potentially predicted biomarkers which reflect the therapeutic efficacy of NAC in different subtypes of breast cancer. Further, possible mechanisms are also discussed to discover feasible treatment targets. Thus, these findings will be helpful to promote the prognosis of breast cancer patients who received NAC and summarized in this review.

Micro RNA-363 inhibits esophageal squamous cell carcinoma progression by directly targeting sperm-associated antigen 5

OBJECTIVE

Micro RNA (miR)-363 has many important biological functions in cancers, but its roles in esophageal squamous cell carcinoma (ESCC) remain unclear.

METHODS

We used reverse transcription PCR to quantify the expression of miR-363 in 80 ESCC tissues and analyzed its relationship with clinicopathological factors and overall survival. The effects of miR-363 on cell proliferation, apoptosis, and invasion were detected using the MTT assay, flow cytometry, and Transwell invasion assays, respectively. Further, we investigated the post-transcriptional regulation of sperm-associated antigen 5 (SPAG5) expression by miR-363 using luciferase reporter assays. Finally, the effects of SPAG5 on miR-363 were studied by SPAG5 overexpression.

RESULTS

miR-363 expression was decreased in both ESCC specimens and cell lines, compared with controls, and correlated with lymph node metastasis and tumor differentiation. Low miR-363 expression was identified as an independent prognostic factor for ESCC. miR-363 overexpression decreased ESCC cell proliferation and invasion and increased apoptosis, while the opposite was seen after miR-363 inhibition. Moreover, SPAG5 was identified as a direct target of miR-363, and the reintroduction of SPAG5 restored miR-363-induced effects.

CONCLUSIONS

miR-363 acts as a tumor suppressor by post-transcriptionally regulating SPAG5 expression, suggesting its potential as a diagnostic biomarker and therapeutic target for ESCC.

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study

Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytogenetic abnormalities and gene mutations are important predictors of outcome, 50% to 70% of AMLs harbor normal or risk-indeterminate karyotypes. Therefore, identifying more effective biomarkers predictive of treatment success and failure is essential for informing tailored therapeutic decisions. We applied an artificial neural network (ANN)-based machine learning approach to a publicly available data set for a discovery cohort of 593 adults with nonpromyelocytic AML. ANN analysis identified a parsimonious 3-gene expression signature comprising CALCRL, CD109, and LSP1, which was predictive of event-free survival (EFS) and overall survival (OS). We computed a prognostic index (PI) using normalized gene-expression levels and β-values from subsequently created Cox proportional hazards models, coupled with clinically established prognosticators. Our 3-gene PI separated the adult patients in each European LeukemiaNet cytogenetic risk category into subgroups with different survival probabilities and identified patients with very high-risk features, such as those with a high PI and either FLT3 internal tandem duplication or nonmutated nucleophosmin 1. The PI remained significantly associated with poor EFS and OS after adjusting for established prognosticators, and its ability to stratify survival was validated in 3 independent adult cohorts (n = 905 subjects) and 1 cohort of childhood AML (n = 145 subjects). Further in silico analyses established that AML was the only tumor type among 39 distinct malignancies for which the concomitant upregulation of CALCRL, CD109, and LSP1 predicted survival. Therefore, our ANN-derived 3-gene signature refines the accuracy of patient stratification and the potential to significantly improve outcome prediction.

SPAG5: An Emerging Oncogene

Sperm-associated Antigen 5 (SPAG5) is a mitotic spindle protein. Recent studies have found that it is overexpressed in many human cancers and functions as an oncogene. Here, we summarize the current underlying mechanisms for its oncogenic roles in regulating cellular behaviors of cancer cells and discuss the possibility of targeting SPAG5 for cancer treatment.

Co-Expression Network Analysis Identified Genes Associated with Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma

Objective: Cancer stem cells are self-renewal cells in tumors and can produce heterogeneous tumor cells, which play an important role in the development of lung squamous cell carcinoma (LSCC). In our research, we aimed to explore the expression of genes related to LSCC stem cells.Methods: We downloaded the RNAseq data, the pathological and prognostic profiles of LSCC cases from the public database TCGA. The mRNA expression-based stiffness index (mRNAsi) of LSCC was calculated and the prognostic value of mRNAsi was discussed. Then, we constructed a weighted gene co-expression network analysis (WGCNA) to screen key genes related to mRNAsi of LSCC.Results: MRNAsi is an independent prognostic factor in LSCC. We screened 5 key genes (BUB1, BIRC5, CCNB2, KIF15 and SPAG5) related to mRNAsi of LSCC based on WGCNA. The key genes were highly expressed in the tumor samples compared to the normal samples. In addition, there is a strong interaction between proteins of these key genes and a strong co-expression relationship at the transcriptional level.Conclusions: To conclude, mRNAsi play an important role in LSCC. Five key genes (BUB1, BIRC5, CCNB2, KIF15 and SPAG5) related to mRNAsi were screened, which may act as therapeutic targets for inhibiting the stem cell characteristics of LSCC.

MicroRNA-367-3p overexpression represses the proliferation and invasion of cervical cancer cells through downregulation of SPAG5-mediated Wnt/β-catenin signalling

MicroRNA-367-3p (miR-367-3p) has been previously reported as a cancer-related miRNA that is dysregulated in various cancer types and functions either as an oncogenic or as tumour suppressive miRNA. However, whether miR-367-3p is dysregulated in cervical cancer and, further, whether it contributes to the development and progression of the disease remains unknown. Here, our results demonstrated that miR-367-3p expression was markedly decreased in both cervical cancer tissues and cell lines compared with corresponding controls. In vitro experiments revealed that miR-367-3p overexpression repressed the proliferation and invasion of cervical cancer cells. Notably, sperm-associated antigen 5 (SPAG5) was identified as a target gene of miR-367-3p. Moreover, decreased expression of miR-367-3p was correlated with high expression of SPAG5 in cervical cancer tissue specimens. SPAG5 inhibition or miR-367-3p overexpression significantly downregulated Wnt/β-catenin signalling in cervical cancer cells. However, the antitumour effect mediated by miR-367-3p overexpression was partially reversed by SPAG5 overexpression. Overall, these findings demonstrate that miR-367-3p overexpression restricts the proliferation and invasion of cervical cancer cells through targeting SPAG5 to downregulate Wnt/β-catenin signalling, suggesting a mechanism for the tumour suppressive function of miR-367-3p in cervical cancer. Our study highlights the involvement of miR-367-3p/SPAG5/Wnt/β-catenin signalling axis in regulating the malignant progression of cervical cancer.

Dopamine and cAMP-regulated phosphoprotein 32 kDa (DARPP-32) and survival in breast cancer: a retrospective analysis of protein and mRNA expression

Dopamine and cAMP regulated phosphoprotein 32 kDa (DARPP-32) also known as phosphoprotein phosphatase-1 regulatory subunit 1B and encoded by the PPP1R1B gene is an inhibitor of protein phosphatase-1 and protein kinase A. DARPP-32 is expressed in a wide range of epithelial cells and some solid tumours; however, its role in breast cancer is only partially defined. DARPP-32 expression was determined using immunohistochemistry in two independent cohorts of early stage invasive breast cancer patients (discovery n = 1352; validation n = 1655), and 112 HER2 positive breast cancer patients treated with trastuzumab and adjuvant chemotherapy. PPP1R1B mRNA expression was assessed in the METABRIC cohort (n = 1980), using artificial neural network analysis to identify associated genes. In the discovery cohort, low nuclear expression of DARPP-32 was significantly associated with shorter survival (P = 0.041), which was independent of other prognostic variables (P = 0.019). In the validation cohort, low cytoplasmic and nuclear expression was significantly associated with shorter survival (both P = 0.002), with cytoplasmic expression independent of other prognostic variables (P = 0.023). Stronger associations with survival in oestrogen receptor (ER) positive disease were observed. In patients treated with trastuzumab, low nuclear expression was significantly associated with adverse progression-free survival (P = 0.031). In the METABRIC cohort, low PPP1R1B expression was associated with shortened survival of ER positive patients. Expression of CDC42 and GRB7, amongst others, were associated with PPP1R1B expression. This data suggests a role for DARPP-32 as a prognostic marker with clinical utility in breast cancer.

The prognostic association of SPAG5 gene expression in breast cancer patients with systematic therapy

Background

Despite much effort on the treatment of breast cancer over the decades, a great uncertainty regarding the appropriate molecular biomarkers and optimal therapeutic strategy still exists. This research was performed to analyze the association of SPAG5 gene expression with clinicopathological factors and survival outcomes.

Methods

We used a breast cancer database including 5667 patients with a mean follow-up of 69 months. Kaplan-Meier survival analyses for relapse free survival (RFS), overall survival (OS), and distant metastasis-free survival (DMFS) were performed. In addition, ROC analysis was performed to validate SPAG5 as a prognostic candidate gene.

Results

Mean SPAG5 expression value was significantly higher with some clinicopathological factors that resulted in tumor promotion and progression, including poor differentiated type, HER2 positive or TP53 mutated breast cancer. Based on ROC-analysis SPAG 5 is a suitable prognostic marker of poor survival. In patients who received chemotherapy alone, SPAG5 had only a moderate and not significant predictive impact on survival outcomes. However, in hormonal therapy, high SPAG5 expression could strongly predict prognosis with detrimental RFS (HR = 1.57, 95% CI 1.2–2.06, p = 0.001), OS (HR = 2, 95% CI 1.05–3.8, p = 0.03) and DMFS (HR = 2.36, 95% CI 1.57–3.54, p <  0.001), respectively. In addition, SPAG5 could only serve as a survival predictor in ER+, but not ER- breast cancer patients. Patients might also be at an increased risk of relapse despite being diagnosed with a lower grade cancer (well differentiated type).

Conclusions

SPAG5 could be used as an independent prognostic and predictive biomarker that might have clinical utility, especially in ER+ breast cancer patients who received hormonal therapy.

A four-mRNA model to improve the prediction of breast cancer prognosis

BACKGROUND

Breast cancer (BRCA) is the most prevalent cancer that threatens female health. A growing body of evidence has demonstrated the non-negligible effects of messenger RNAs (mRNAs) on biological processes involved in cancers; however, there is no definite conclusion regarding the role of mRNAs in predicting the prognosis of BRCA patients.

MATERIALS AND METHODS

We systematically screened the mRNA expression landscape and clinical data of samples from the Cancer Genome Atlas (TCGA). Univariate Cox analysis and robust likelihood-based survival analysis were conducted to identify key mRNAs associated with BRCA. Furthermore, risk scores based on multivariate Cox analysis divided the training set into high-risk and low-risk groups. ROC analysis determined the optimal cut-off point for patient classification of risk levels. The prognostic model was additionally validated in the testing set and complete dataset. Finally, we plotted the survival curves for the mRNAs used in our model.

RESULTS

We obtained the original expression data of 13,617 mRNAs from a total of 1088 samples. After comprehensive survival analysis, the four-mRNA (ACSL1, OTUD3, PKD1L2, and WISP1) prognosis risk assessment model was constructed. Furthermore, the area under cure (AUC) was 0.834, indicating that the model was meaningful and reasonable. In each dataset, analysis based on the four-mRNA signature risk score indicated that the survival status of the group with high risk score was worse than that of the group with low risk scores. Patients with strong mRNA expression of OTUD3, PKD1L2, and WISP1 tended to have good prognosis, whereas patients with high ACSL1 expression tended to have poor prognosis.

CONCLUSION

In summary, we constructed a four-mRNA prognosis risk assessment model for BRCA. The newly developed model offers more possibilities for assessing prognosis and guiding the selection of better treatment strategies for BRCA.

ERCC1 Is a Predictor of Anthracycline Resistance and Taxane Sensitivity in Early Stage or Locally Advanced Breast Cancers

Genomic instability could be a beneficial predictor for anthracycline or taxane chemotherapy. We interrogated 188 DNA repair genes in the METABRIC cohort (n = 1980) to identify genes that influence overall survival (OS). We then evaluated the clinicopathological significance of ERCC1 in early stage breast cancer (BC) (mRNA expression (n = 4640) and protein level, n = 1650 (test set), and n = 252 (validation)) and in locally advanced BC (LABC) (mRNA expression, test set (n = 2340) and validation (TOP clinical trial cohort, n = 120); and protein level (n = 120)). In the multivariate model, ERCC1 was independently associated with OS in the METABRIC cohort. In ER+ tumours, low ERCC1 transcript or protein level was associated with increased distant relapse risk (DRR). In ER−tumours, low ERCC1 transcript or protein level was linked to decreased DRR, especially in patients who received anthracycline chemotherapy. In LABC patients who received neoadjuvant anthracycline, low ERCC1 transcript was associated with higher pCR (pathological complete response) and decreased DRR. However, in patients with ER−tumours who received additional neoadjuvant taxane, high ERCC1 transcript was associated with a higher pCR and decreased DRR. High ERCC1 transcript was also linked to decreased DRR in ER+ LABC that received additional neoadjuvant taxane. ERCC1 based stratification is an attractive strategy for breast cancers.

A 23 gene-based molecular prognostic score precisely predicts overall survival of breast cancer patients

BACKGROUND

Although many prognosis-predicting molecular scores for breast cancer have been developed, they are applicable to only limited disease subtypes. We aimed to develop a novel prognostic score that is applicable to a wider range of breast cancer patients.

METHODS

We initially examined The Cancer Genome Atlas breast cancer cohort to identify potential prognosis-related genes. We then performed a meta-analysis of 36 international breast cancer cohorts to validate such genes. We trained artificial intelligence models (random forest and neural network) to predict prognosis precisely, and we finally validated our prediction with the log-rank test.

FINDINGS

We identified a comprehensive list of 184 prognosis-related genes, most of which have been not extensively studied to date. We then established a universal molecular prognostic score (mPS) that relies on the expression status of only 23 of these genes. The mPS system is almost universally applicable to breast cancer patients (log-rank P < 0.05) in a manner independent of platform (microarray or RNA sequencing).

INTERPRETATION

The mPS system is simple and cost-effective to apply and yet is able to reveal previously unrecognized heterogeneity among patient subpopulations in a platform-independent manner. The combination of mPS and clinical stage stratifies prognosis even more precisely and should prove of value for avoidance of overtreatment. In addition, the prognosis-related genes uncovered in this study are potential drug targets. FUND: This work was supported by KAKENHI grants from the Ministry of Education, Culture, Sports, Science, and Technology of Japan to H.S. (19K20403) and to K.I·N (18H05215).

Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray

: Breast cancer (BRCA) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers expressed during estradiol and tamoxifen treatment of BRCA. The microarray dataset of E-MTAB-4975 from Array Express database was downloaded, and the differential expressed genes (DEGs) between estradiol-treated BRCA sample and tamoxifen-treated BRCA sample were identified by limma package. The pathway and gene ontology (GO) enrichment analysis, construction of protein-protein interaction (PPI) network, module analysis, construction of target genes-miRNA interaction network and target genes-transcription factor (TF) interaction network were performed using bioinformatics tools. The expression, prognostic values, and mutation of hub genes were validated by SurvExpress database, cBioPortal, and human protein atlas (HPA) database. A total of 856 genes (421 up-regulated genes and 435 down-regulated genes) were identified in T47D (overexpressing Split Ends (SPEN) + estradiol) samples compared to T47D (overexpressing Split Ends (SPEN) + tamoxifen) samples. Pathway and GO enrichment analysis revealed that the DEGs were mainly enriched in response to lysine degradation II (pipecolate pathway), cholesterol biosynthesis pathway, cell cycle pathway, and response to cytokine pathway. DEGs (MCM2, TCF4, OLR1, HSPA5, MAP1LC3B, SQSTM1, NEU1, HIST1H1B, RAD51, RFC3, MCM10, ISG15, TNFRSF10B, GBP2, IGFBP5, SOD2, DHF and MT1H) , which were significantly up- and down-regulated in estradiol and tamoxifen-treated BRCA samples, were selected as hub genes according to the results of protein-protein interaction (PPI) network, module analysis, target genes-miRNA interaction network and target genes-TF interaction network analysis. The SurvExpress database, cBioPortal, and Human Protein Atlas (HPA) database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. A comprehensive bioinformatics analysis was performed, and potential therapeutic applications of estradiol and tamoxifen were predicted in BRCA samples. The data may unravel the future molecular mechanisms of BRCA.

p53 suppression is essential for oncogenic SPAG5 upregulation in lung adenocarcinoma

Aberrant expression of sperm-associated antigen 5 (SPAG5) is implicated to play oncogenic roles in several types of cancers. However, the functions of SPAG5 in lung adenocarcinoma remain unclear. In this study, we investigated the role of SPAG5 in lung adenocarcinoma. We found that SPAG5 was upregulated in most of the lung adenocarcinoma cell lines as compared to normal lung epithelial cells. SPAG5 knockdown suppressed proliferation, colony forming, and migration of lung adenocarcinoma A549 cells in vitro and inhibited tumor growth in vivo. These suggest that upregulated SPAG5 promotes lung tumor progression. Importantly, treatment with MDM2 inhibitor, Nutlin-3a, restored p53 and p21 expression and suppressed SPAG5 expression in wild-type p53 lung adenocarcinoma cells, A549 and H460, but not in p53-null lung cancer cells, H1299. This suggests that the p53 signal pathway is essential for SPAG5 suppression. In addition, knocking-down p53 or p21 in A549 and H460 cells attenuated Nutlin-3a-induced repression of SPAG5, which further supports that the p53-p21 axis is required for SPAG5 repression. Thus, SPAG5 can serve as a prognostic marker, and therapeutic strategy targeting the p53-p21-SPAG5 axis may have important clinical implications.