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Gene & Protein in Disease Significance of MXRA7 in bladder cancer

Table 1. Multivariate Cox regression analysis of clinical 4. Discussion
and molecular factors in bladder cancer (n=325, all
muscle‑invasive tumors) In cancer biology, the identification of biomarkers for
diagnosis, treatment selection, and prognosis remains
Term Regression p‑value HR HR 95% CI a significant challenge, and BLCA is no exception. 40,41
coefficient This study adds MXRA7 to the growing list of potential
Age 0.03 0.01 1.03 1.01~1.04 biomarkers for BLCA, potentially through its involvement
MXRA7 0.26 0.05 1.30 0.97~1.74 in pathways related to cell adhesion, proliferation, and
Risk score 0.76 0.00 2.20 1.61~2.83 anti-apoptotic mechanisms. These include the PI3K-Akt
MXRA7 expression - - - - signaling pathway, ECM-receptor interaction, and focal
level-high adhesion pathways (Figure 2), all of which contribute to
Low 0.73 0.04 1.80 1.03~3.15 cancer progression by fostering an environment conducive
Cancer status-tumor free - - - - to tumor cell survival, growth, invasion, and metastasis.
Notably, MXRA7 expression was found to be upregulated
With tumor 0.80 0.00 2.22 1.50~3.06
more than twofold in high-risk BLCA patients (Figure 1),
Tumor grade-high grade - - - - consistent with findings from previous studies. Furthermore,
20
Low grade 0.74 0.05 1.80 0.98~3.48 preliminary KM prognostic analysis revealed that high
Clinical_N-N0 - - - - MXRA7 expression was associated with poor PFS but not
N1 0.13 0.62 1.20 0.74~1.96 DFI in BLCA patients. In addition, the LASSO regression
N2 0.37 0.01 1.57 1.05~2.37 model demonstrated that MXRA7 expression levels could
N3 1.23 0.03 3.42 1.33~10.83 effectively stratify patients into low- and high-risk groups
NX 0.65 0.06 1.91 1.01~3.59 (Figure 5). Collectively, these findings suggest that MXRA7 is
closely linked to BLCA biology and may serve as a promising
Notes: C-index=0.60, 95% CI=0.60~0.60. target for clinical management of the disease.
Abbreviations: CI: Confidence interval; HR: Hazard ratio.
As the first study to explore the role of MXRA7
for 1 year, 3 years, or 5 years (Figure 5A). Using this model, in BLCA – and indeed in any solid tumor – this
doctors can estimate a patient’s chance of survival based on research provides novel insights but also has certain
their total score. For instance, assuming that a 30-year-old obvious limitations. The primary limitation is the
BLCA patient with the following characteristics – risk score lack of experimental validation for the bioinformatic
of -0.50, MXRA7 of 8.50 (high expression), tumor grade findings using independent datasets or laboratory-
high, N0 stage, and cancer status with tumor – would have a based approaches. Future research should address these
total score around 134 by adding the points corresponding limitations in three key areas. First, rigorous analysis of
to each feature based on the nomogram, predicting the external, independent BLCA datasets are needed to confirm
patient having a 50% chance of survival at the 5 year. This the observations derived from the TCGA dataset. Datasets
th
model’s accuracy was tested and showed strong reliability. generated using advanced techniques, such as single-cell
The validity of the model was supported by C-index of 0.75 RNA sequencing (scRNA-seq), which can differentiate
42
with 95% CI between 0.71 and 0.79 and a significant p-value cell populations within tumor tissues, would provide more
(1.43e-35). The calibration plots showed that the model’s robust and convincing evidence. Second, experimental
predictions closely matched actual patient outcomes over validation should be conducted to confirm MXRA7’s
5 years (Figure 5B). Finally, the model was evaluated role in BLCA biology and its potential as a therapeutic
using ROC curves, which test prediction reliability over target. In vitro studies using siRNA-mediated knockdown,
different time periods. Here, the model’s AUC (a measure of CRISPR/Cas9-mediated knockout, or cDNA transfection-
accuracy) was above 0.80 for predictions at 1, 3, and 5 years, mediated overexpression could evaluate MXRA7’s effects
with the best accuracy at 3 years (AUC of 0.83) (Figure 5C). on cell proliferation, migration, invasion, and response to
This means that the model is effective at identifying patients therapeutic agents, similar to previous studies conducted
at higher risk, making it a valuable tool in personalized on leukemic cell lines in our lab. In vivo validation using
7-9
patient care. In summary, this model incorporates key xenograft and metastasis models would further elucidate
factors such as age, MXRA7 expression, and cancer stage MXRA7’s role in tumor growth and progression. Third,
to offer an accurate and reliable way for doctors to assess mechanistic investigations are needed to dissect the
survival chances in BLCA patients. With its AUC above detailed pathways mediating MXRA7’s functions. One
80%, the model can be a useful tool for treatment planning critical question to be answered is whether MXRA7 acts
and providing personalized patient prognoses. as a driver of BLCA progression or merely as a phenotypic

Volume 4 Issue 2 (2025) 7 doi: 10.36922/gpd.6256