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Tumor Discovery PTMAP5–hsa-miR-22-3p–KIF2C axis in HCC development

Table 3. Correlation analysis between KIF2C and immune In our investigation, we identified DEGs common
cell biomarkers in hepatocellular carcinoma as determined to two datasets through Venn analysis. Subsequently,
by the GEPIA database we constructed PPI networks for these DEGs using the
STRING database and Cytoscape software. To identify key
Immune cell Biomarker R‑value P‑value genes, we employed the MCODE plugin within Cytoscape.
B cell CD19 0.11 a 0.026* a The prognostic value of 29 genes (P < 0.05) associated with
CD79A 0.048 0.33 the identified hub genes was evaluated using Kaplan–Meier
CD8 T cell CD8A 0.33 a 5.5E – 12*** a survival analysis, and their expression levels were further
+
CD8B 0.38 a 1.1E – 15*** a validated through the GEPIA platform. Ultimately, 24 key
+
CD4 T cell CD4 0.099 a 0.043* a genes were identified.
M1 macrophage NOS2 0.023 0.64 The MCODE algorithm was used to score each gene,
IRF5 0.34 a 7.5E – 13*** a and hub genes were identified through comprehensive
PTGS2 −0.017 0.72 cross-validation of 13 different algorithms, increasing the
M2 macrophage CD163 0.25 a 2E – 07*** a accuracy of the results. Data from gene microarrays and
VSIG4 0.3 a 3.1E – 10*** a RNA sequencing, sourced from public repositories such as
MS4A4A 0.29 a 1.1E – 09*** a the GEO and TCGA, were utilized to evaluate the impact
of 54,675 genes on survival outcomes across 21 distinct
Neutrophil CEACAM8 0.066 a 0.17 cancer types. The meta-analysis involved integrating gene
ITGAM 0.39 a 0*** a expression data with clinical prognostic significance,
CCR7 0.021 0.66 enabling the assessment, discovery, and validation of
Dendritic cell HLA-DPB1 0.31 a 4.6E – 11*** a molecular markers related to survival.
HLA-DQB1 0.21 a 2.2E – 05*** a An analysis was carried out to explore the link
HLA-DRA 0.32 a 1.6E – 11*** a between the expression levels of the 24 identified genes
HLA-DPA1 0.27 a 1.2E – 08*** a and the prognosis of patients with HCC using Kaplan‒
CD1C 0.12 a 0.011* a Meier survival analysis. The results were subsequently
NRP1 0.23 a 2.3E – 09*** a validated using the GEPIA tool, and the cross-validation
of prognostic results between the two databases further
ITGAX 0.28 a 1E--08*** a enhanced the reliability of the findings. In addition, the
Notes: These results are statistically significant.*P<0.05; **P<0.01; GEPIA database was utilized to examine differences in gene
a
***P<0.001.
expression between normal and HCC tissues. Genes that
KIF2C expression across these immune subtypes was did not meet the threshold of P < 0.05 were systematically
statistically significant in 20 different cancers (P < 0.05). excluded from the study. Finally, 24 genes were identified
Moreover, KIF2C expression showed significant variation as crucial and potentially associated with the progression
across various molecular subtypes in 13 types of cancers of HCC.
(P < 0.05). These findings indicate that KIF2C expression Numerous research studies have provided evidence
levels differ based on the immune and molecular subtypes suggesting that these key genes could function as oncogenes
in diverse human cancers. Detailed observations are or serve as valuable cancer biomarkers. Zhou et al.
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provided in Figures S4 and S5. demonstrated that overexpression of ASPM is associated
with low survival rates and unfavorable prognosis in
4. Discussion endometrial carcinoma tissues. Li et al. ’s highlighted
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HCC, a prevalent form of primary liver cancer, stands the role of the hsa_cirC_0003732 molecule in enhancing
out due to its high mortality rate and poor prognosis. the proliferation of osteosarcoma cells by modulating the
Despite notable strides in the realms of diagnosis and miR-545/CCNA2 axis. Their findings indicate that hsa_
treatment concerning HCC, this malignancy remains a cirC_0003732 holds promise as both a valuable diagnostic
highly aggressive malignancy, characterized by its dismal and prognostic biomarker, as well as a potential therapeutic
overall survival rate and notably low 5-year survival target in osteosarcoma.
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rates. Consequently, unraveling the intricate molecular i. Similarly, Li et al. reported that during the activation
mechanisms governing HCC development and identifying of the CCND1/PI3K/Akt signaling pathway, driving
potential diagnostic and prognostic biomarkers holds the expansion of HCC cells in both in vitro and
significant promise in delineating effective therapeutic in vivo. Liao et al. suggested that the overexpression
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targets and ultimately enhancing patient outcomes. of FAM83D in HCC tissues is correlated with the

Volume 3 Issue 3 (2024) 16 doi: 10.36922/td.2846