PLAC8 Correlates with Prognosis, Immune Inltration, and T Cell Exhaustion in Breast Cancer

Background: Lysosomal protein placenta-specic 8 (PLAC8) with abundant cysteine, also referred to as onzin, participates in numerous cancers, and its effect is greatly determined by the cellular and tumor microenvironment (TME). Ourstudy focused on investigating the prognostic signicance of PLAC8 and examined the association between PLAC8, immune inltration, and T cells function in multiple malignancies comprehensively, particularly in breast cancer (BRCA). Methods: PLAC8 expression in various malignancies was analyzed using TIMER. PrognoScan, Kaplan-Meier Plotter, and GEPIA2 were utilized to explore the signicance of PLAC8 in prognostic prediction. Moreover, PLAC8 functions were systematically analyzed through cancerSEA. Additionally, TISIDB, TIMER, and GEPIA2 were also employed for analyzing the associations among PLAC8, immune inltration, related gene marker sets, and clinical stages. Finally, PLAC8 and its co-expressed genes biological process and KEGG were analyzed. Results: PLAC8 expression decreased in most malignancies and was related to poor prognosis in BRCA. PLAC8 signicantly affected the survival of BRCA with ER status – array, PR status – IHC, HER2 status – array, Intrinsic subtype, Grade, and Pietenpol subtype. Increased PLAC8 expression positively correlated with the increased immune inltration levels within immune cells and many functional T cells (such as exhausted T cells). In BRCA cells, PLAC8 functional phenotypesshowed a negative correlation with invasion, metastasis, apoptosis, DNA damage, and DNA repair. Besides, PD-1, TIM-3, TIGIT, LAG3, and GZMB, critical genes of exhausted T cells, interacted with PLAC8. Further analysis indicated that PLAC8 was related to T cell activation, proliferation and adhesion of leukocytes,adaptive immune response, cell adhesion molecules (CAMs), cytotoxicity-mediated by natural killer cells, and the NF-kappa B signal transduction pathway. Conclusion:PLAC8 is a prognostic indicator in pan-cancers, especially BRCA. Elevated PLAC8 level marker correlation analysis within LUAD samples. Normal, correlation analysis in normal tissue of TCGA.Cor, R-value obtained upon Spearman’s correlation.

adopted to analyze selected gene expression, showing a negative correlation with tumor purity among all cancer types [25]. Herein, "Diff Exp module" and "Gene module" were used to detect PLAC8 expression in pan-cancers and investigate its association with six TIIC subset abundance. Wilcoxon test was adopted to determine the statistical signi cance of differential PLAC8 expression. In addition, the relationship of PLAC8 level with immune in ltration was also evaluated through the purity-adjusted partial Spearman correlation. Besides, tumor-in ltration degrees were compared among tumors with diverse somatic copy number alterations (SCNAs) of PLAC8 using the "SCNA module." "SCNA module" is de ned by GISTIC 2.0, including high ampli cation (2), arm-level gain (1), diploid/normal (0), arm-level deletion (− 1), and deep deletion (− 2). "Correlation module" was used to examine further PLAC8 expression relationship with TIIC gene markers, including B cells, neutrophils, effector Treg cells, T cells, central memory T cells, CD8 + T cells, resident memory T cells, effector T cells, resting Treg cells, exhausted T cells, natural killer cells (NK cells), effector memory T cells, Th1, macrophages, DCs and mast cells according to previous literature [26 -29]. Functionally, this module could plot expression scatter plots between PLAC8 in speci c cancer types, along with Spearman correlation and statistical signi cance. Additionally, we presented gene expression data in the form of log2 RSEM (RNA-Seq by Expectation-Maximization).

PrognoScan Database Analysis
As a freely accessible database, PrognoScan provides diverse cancer microarray datasets to assess the biological association of gene expression with the patient prognostic out come and the candidate diagnostic biomarkers or the related therapeutic targets [30]. In this study, PrognoScan was employed to investigate the relationship ofPLAC8level with cancer prognosis. Hazard ratios (HRs), related 95% con dence intervals (CIs), and COX P-values were determined. The PLAC8 prognostic prediction performance was also assessed.

KM Plotter Database Analysis
KM Plotter database, a web-based resource, e ciently exploits the prognostic signi cance of gene expression in 21 malignancies, including four large datasets, that is breast (n = 6234), lung (n = 3452), ovarian (n = 2190) as well as gastric (n = 1440) cancer [31]. We thus exploited the PLAC8 expression relationship to survival in these four types of cancer from KM Plotter, manifested by survival curves, logrank P-value, and HR (95% CI).

GEPIA2 Database Analysis
GEPIA2 database is an online method to interactively analyze gene expression in tumor and normal tissue based on GTEx (Genotype-Tissue Expression) data and TCGA, characterized by offering tailored functions, such as differential expression, correlation, survival and dimensionality reduction analysis, pro ling plotting, and similar gene detection [32]. The "survival analysis" function examined the correlation of PLAC8 expression with survival in pan-cancers in TCGA. Spearman correlation coe cient from the "correlation analysis" function was utilized to determine the PLAC8 relationship with tumorin ltration immune cell gene markers.

CancerSEA Database Analysis
As the rst database for single-cell sequencing (scRNA-seq), CancerSEA contributes to the comprehensive exploration of tumor cell functional states at the single-cell level. Typically,results of scRNA-seqcollected into the CancerSEA database are obtained from altogether 72 datasets at GEO, SRA, and Array Express   websites. There are 41,900 cancer cell types originating from 25 cancers, while the results of functional  analysis obtained based on datasets like HCMDB, StemMapper, and Cyclebase, and altogether 14 functional states were rede ned [33]. As a result, this database was utilized to analyze the relationship between PLAC8 and BRCA.

TISIDB Database Analysis
TISIDB database is characterized by integrating high-throughput screening techniques with seven other retrieved public datasets. About 988 revealed immune-related anti-tumor genes, para-cancerous multiomics information, molecular pro les, and diverse resources for immunological data [34] to analyze the association between speci c genes and chemokines, immunomodulators as well as lymphocytes. TISIDB database was adopted to determine PLAC8 expression relationship to BRCA's clinical stages and investigate the possible relationship of PLAC8 expression with immunomodulators and lymphocytes.

MEXPRESS Database Analysis
MEXPRESS was designed as an approach to visualizedata, including TCGA level, clinical information, DNA methylation status, and the relationships between them [35]. Here, MEXPRESS was used to investigate the PLAC8 gene methylation status and the associations of PLAC8 mRNA level with diverse clinical features among BRCA cases.

LinkedOmics Database Analysis
"LinkFinder" module of LinkedOmics, statistically analyzed PLAC8 co-expression by Pearson's test and was presented as volcano, heat, or scatter plots. "LinkInterpreter" module of LinkedOmics was adopted for GO (Biological Process) analysis and KEGG pathways through GSEA. The criteria included false discovery rate (FDR) < 0.05, and simulations of 500 [36].

Statistical analysis
The KM Plotter, PrognoScan, TIMER, and GEPIA2 were employed to plot survival curves, whereas the logrank test was utilized to determine P-values, Cox P-values, and HRs. The two-sided Wilcoxon rank-sum test compared the in ltration degree of every SCNA category with normal tissue. Spearman's correlation assessed the association between PLAC8 level and other gene or immune in ltration levels in speci c cancer types. P ≤ 0.05 indicated statistical signi cance and is shown in the gures.

Prognostic Potential of PLAC8 in Cancers
This study examined PLAC8 level association with patient prognosis comprehensively in three large cancer datasets to assess the prognostic signi cance of PLAC8.
Considering the correlation of PLAC8 level with poor prognosis in BRCA patients, the KM Plotter database was employed to investigate the possible mechanisms to evaluate PLAC8 expression relationship to clinicopathological parameters. As a result, the PLAC8 level was signi cantly associated with OS, DFS, patient ER status -array, PR status -IHC, HER2 status -array, Intrinsic subtype, Grade, and Pietenpol subtype ( Table 2).

PLAC8 function in a single BRCA cell
Heterogeneity related to the diverse cancer cell functional phenotypes is the main obstacle hindering e cient anticancer treatment. Recently, achievements have been attained in single-cell sequencing (scRNA-seq) to understandcancer cell functional status at the cell level. As revealed by cancerSEA functional correlation analysis, PLAC8 functional phenotypes within BRCA cells showed a negative correlation with invasion, metastasis, apoptosis, DNA damage, and DNA repair (Fig. 3).

Modulation of immune molecules by PLAC8
TISIDB database was employed to analyze Spearman's correlation of PLAC8 expression with lymphocytes and immunomodulators. The classi cation of immunomodulators included major histocompatibility complex (MHC) molecules, immuno-inhibitors as well as immuno-stimulators. The resulting heatmap showed that in most malignancies, PLAC8 was signi cantly correlated with TILs and immunomodulators (MHC, immuno-inhibitors, immuno-stimulators) (Fig. 4). Therefore, PLAC8 could likely modulate these immune molecules.

PLAC8 correlates with immune in ltration level in BRCA
The survival and LNM(lymph node metastasis) in tumor patients can be predicted independently by TIL (tumor-in ltrating lymphocytes) frequency [37][38][39]. Thus, the TIMER database was utilized to examine the relationship of PLAC8expression with the degrees of immune in ltrationamong 39 types of malignancies ( Figure S2). Consequently, the PLAC8 level was markedly associated with tumor purity among 31 cancers related tothe in ltration of B cells within 31 cancers. Moreover, the PLAC8 level was also related to CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and DC in ltration levels in 31, 31, 21, 29, and 30 types of malignancies, respectively. PLAC8 level was not statistically associated with B cell, CD4 + T cell, neutrophil, DC, CD8 + T cell, and macrophage in ltration in mesothelioma (UVM) ( Figure  S2AL). However, PLAC8 level had a signi cant association with purity level (R = − 0.525, P = 1.76e-71), B cell (R = 0.42, P = 5.76e-43), CD8 + T cell (R = 0.442, P = 5.87e-48), CD4 + T cell (R = 0.56, P = 1.60e-80), neutrophil (R = 0.499, P = 5.19e-61) and DC (R = 0.521, P = 1.94e-67) in BRCA (Fig. 5A). KM plots based on the TIMER database were used to investigate the PLAC8 level relationship with immune cell in ltration in BRCA. Consequently, B cell in ltration was signi cantly related to BRCA prognosis (P = 0.046) (Fig. 5B). In addition, deletions or normal copy number of PLAC8 gene locus was related to elevated immune cell in ltration, except B cell, neutrophil, and DC. Although SCNA was not related to immune in ltration in B cell, neutrophil, and DC (Fig. 5C), our present ndings indicated the essential effect of PLAC8 on immune in ltration degree, particularly DC, in BRCA.
3.6 Relationship of PLAC8 with immune cell gene markers GEPIA2 and TIMER were utilized for correlation analysis between PLAC8 and TIIC gene makers in BRCA to exploit the correlation of PLAC8 with tumor immune in ltration.
The selection of gene markers of diverse functional T cells and common immune cell populations was consistent with the literature. The correlation analysis after tumor purity adjustment in BRCA is shown in Table 3. PLAC8 had a signi cant relationship with gene markers of B cells, monocytes, TAMs, T cells, CD8 + T cells, neutrophils, macrophages, DCs, NK cells, mast cells, and most functional T cells. Intriguingly, the above ndings demonstrated the robust association of PLAC8 with B cells, T cells, and functional T cells, consistent with previous studies, and revealed a correlation of PLAC8 with mast cells.  [40]. In-depth research could con rm the vital role of PLAC8 in modulating tumor metastasis and DC in ltration. In our study, PLAC8 signi cantly interacted with various vital genes of exhausted T cell comprising PD-1 (Cor = 0.61, P < .0001), TIM-3 (Cor = 0.3, P < 0.0001), TIGIT (Cor = 0.75, P < .0001), LAG3 (Cor = 0.38, P < 0.0001), and GZMB (Cor = 0.53, P < 0.0001), involved in cancer immunotherapy.  , and C6 (TGF-b dominant type), manifested the expression of PLAC8. PLAC8 was found highest and lowest in the C2 and C3 types, respectively (Fig. 6A). PLAC8 expression was further investigated in different molecular subtypes of BRCA using TISIDB. Five different molecular subtypes (basal, Her2, lumA, lumB, and normal) were identi ed in BRCA. PLAC8 expression was highest and lowest in the basal and lumB subtypes, respectively (Fig. 6B), indicating its potent relationship with the tumor immune microenvironment. However, the comparison of different BRCA stages (I-IV, X) was signi cantly based on the GEPIA2 database (P = 0.00436) (Fig. 6C). Furthermore, MEXPRESS analysis indicated that PLAC8 mRNA expression correlated with the BRCA estrogen receptor status, BRCA progesterone receptor status, histological type, menopause status, gender, tumor stage simpli ed, sample type, and subtype (Fig. 6D).

PLAC8 co-expression networks in BRCA
For an in-depth understanding of the biological signi cance of PLAC8 in BRCA, the co-expression pattern of PLAC8 was examined using the "LinkFinder" module in LinkedOmics (Fig. 7A). Heatmaps showed the top 50 genes showing positive and negativecorrelation with PLAC8 ( Fig. 7B and 7C).
GSEA-based annotation of signi cant GO term demonstrated PLAC8 co-expressed genes participation in positive modulation of the adaptive immune response, T cell activation, leukocyte cell-cell adhesion, leukocyte proliferation, cellular defense response as well as response to chemokine signaling pathway (Fig. 7D). KEGG analysis revealed primary gene enrichment in cytotoxicity mediated by natural killer cells, infection with Staphylococcus aureus, NF-kappa B signal transduction pathway, cell adhesion molecules (CAMs), chemokine signal transduction pathway, hematopoietic cell lineage, the interaction between cytokine and cytokine receptor (Fig. 7E).

Discussion
PLAC8 is a protein containing 115amino acids with abundant cysteine [9], rstdiscovered to show high expression within mouse placenta [10]. According to our results, PLAC8 inhibits the apoptosis of BRCA through the activation of the PI3K/AKT/NF-κB signal transduction pathway. PLAC8 plays a vital role as an oncogene or tumor suppressor gene during cancer development [41]. Nevertheless, comprehensive study on the association between PLAC8 level and immune in ltration, T cell activity, andthe pan-cancer prognosis is limited. Our study revealed that PLAC8 level was associated withthe prognostic outcome of various malignancies, especially BRCA, by analyzing massive tumor specimens derived from a series of large public databases. Besides, PLAC8 expression was positively related to the degree of immune in ltration within BRCA. The analysis on gene expression correlations for T cells robustly validated that PLAC8 signi cantly interactedwith numerous functional T cells within BRCA, particularly the exhausted T cells. Therefore, PLAC8 provides new directions as a possible prognostic biomarker for BRCA for exploiting the association of PLAC8 with T cell function and immune in ltration.
Our study comprehensively investigated PLAC8 expression and systematic prognostic signature in pancancers based on several public datasets in TIMER and 33 malignancies from TCGA-based GEPIA2, which revealed differential PLAC8 expression between cancerous and normal tissue in various malignancies. PLAC8 expression increased in HNSC-HPVpos, KIRC, and KIRP compared to normal tissue in the TIMER database. However, several datasets revealed lower PLAC8 expression in BRCA, CHOL, COAD, HNSC, KICH, LIHC, LUAD, LUSC, PRAD, READ, SKCM. The varied PLAC8 level in various malignancies in different databases might be due to variations in the data collection and intrinsic biological properties. However, a robust, consistent prognostic association of PLAC8 expression was found in these databases in BRCA. In PrognoScan, the PLAC8 level was signi cantly related to survival inAML, skin cancer, and, particularly, breast cancer. Further analysis using GEPIA2 and KM Plotter suggested that down-regulation of PLAC8 predicted the dismal prognostic outcome of BRCA, LUSC, OV, STAD, CESC, SARC, SKCM, CHOL, LIHC, and LUSC. Moreover, PLAC8 expression signi cantly correlated with patient ER status -array, PR status -IHC, HER2 status -array, Intrinsic subtype, Grade, and Pietenpol subtype. Collectively, these outcomes indicated PLAC8 as a prognostic biomarker for BRCA.
Similarly, CancerSEA analysis indicated the involvement of PLAC8 in cancer metastasis and invasion.
Further, PLAC8 was veri ed to inhibit BRCA apoptosis by activatingPI3K/AKT/NF-κB signal transduction pathway. PLAC8 may play a role as an oncogene or a tumor suppressor gene during cancer development [41]. We, therefore, propose that PLAC8 could be a potential BRCA biomarker.
TISIDB-based assessment of the relationship of PLAC8 with the immune system revealed that it was signi cantly correlated with lymphocytes, immuno-inhibitors, immuno-stimulators, and MHC molecules. The T1-type chemokine epigenetic silencing was demonstrated as a new immune evasion mechanism within cancers, whereas epigenetic reprogramming facilitated theselective increase in the therapeutic e cacy in BRCA [42]. Therefore, PLAC8 associated with the above immune molecules might be a novel target to investigate immune evasion in BRCA, likely to function as an immunotherapeutic target. BRCA is classi ed into various molecular subtypes. TISIDB database analysis revealed that PLAC8 expression was the highest in basal subtype, followed by the normal type, Her2, lumA, and lumB types. Varied PLAC8 levels were detected in distinct immune subtypes in BRCA, with the highest in the C2 type. The in-depth and comprehensive study on PLAC8 gene expression in diverse databases of BRCA and subtypes indicated the potent correlation of PLAC8 with immunological properties in the tumor microenvironment (TME).
Due to the strong impact of PLAC8 on the immune system and the remarkable prognostic signi cance in BRCA, we analyzed the association between PLAC8 and the degree of immune in ltration within BRCA. Intriguingly, we revealed the dual roles of PLAC8. High PLAC8 level positively correlated with superior prognosis in various types of malignancies, including BRCA, and simultaneously triggered T cell exhaustion, leading to inadequate anti-tumor immunity. The underlying mechanism has been explained recently by several researchers. PLAC8 showeda positive effect on regulating the migration and invasion of trophoblasts by promoting Cdc42 and Rac1 activation [11]. Therefore, PLAC8 plays a diverse role in normal immunity development and modulating TME, which requires identi cation in a speci c stage.
To summarize, the present outcomes implicated PLAC8 as a prognostic biomarker in pan-cancers, particularly BRCA. Elevated PLAC8 expression is associated with a high immune in ltration degree in B cells, CD4 + T cells, Macrophages, DCs, neutrophils, CD8 + T cells, and most functional T cells. Despite its vital function in immunity development, PLAC8 is signi cantly related to T cell exhaustion and might promote T cell exhaustion in BRCA. Therefore, PLAC8 expression determination might assist in prognostic prediction. Besides, its modulation within exhausted T cells possibly could serve as the new approach for optimizingthe therapeutic effect of immunotherapy among BRCA cases.

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Data supporting our ndings are already included in the manuscript.

Competing interests
The authors declare that they have no competing interests.

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Authors' contributions LP, WY and YHP conducted statistical analysis and drafted the manuscript. SLX conceived the research, participated in the research design and coordination, and provided suggestions on the writing of the manuscript. All authors read and approved the nal manuscript.