ITM2A (Integral Membrane Protein 2A)

This integrated framework successfully identified has-miR-6756-5p as both a diagnostic biomarker and therapeutic target, demonstrating how traditional experimental validation coupled with computational prediction enhances translational potential. The multi-scale approach spanning bulk transcriptomics, AI-driven biomarker selection, single-cell characterization, and functional validation represents an effective paradigm for developing clinically relevant cancer biomarkers and therapeutic targets.

Its overexpression inhibited cancer cell proliferation, migration, and invasion while reducing tumor growth in xenografts. Oe-circITFG2 competitively bound miR-526b-5p, upregulating ITM2A to activate autophagy-mediated PD-L1 degradation and enhance antitumor immunity.

MSR1+macrophages promote tumor-infiltrating ITM2A+CD4T exhaustion differentiation by regulating the ITM2A-ZAP70 axis. ZEA-αCD4 specifically targeted MSR1-ITM2A interaction to activate antitumor immunity and improve the efficacy of αPDL1 immunotherapy.

Pharmacogenomic analysis further confirmed that the expression level of ITM2A was negatively correlated with the sensitivity of etoposide. By establishing the 'immunometabolism-therapeutic response' regulatory axis of ITM2A, this study hopes to provide an innovative theoretical basis for the targeted treatment of TNBC and the precise stratification of immunotherapy.

Subsequently, we utilized four machine learning algorithms to identify four key genes: ITM2A, FOXP3, WIPF1, and RSPO1 from DEGs...Furthermore, we showed that ITM2A overexpression inhibited the growth of HNSC cells. Our results suggest that ITM2A may be a novel prognostic marker associated with TIME.

Furthermore, we elucidated that ITM2A could suppress malignant phenotypes of bladder cancer cells via inhibiting activation of the STAT3 induced by IL-6. In conclusion, our research unveiled the mechanistic role of ITM2A in inhibiting tumor progression, shedding light on its potential as a prognostic predictor and therapeutic target in bladder cancer management.

The integration of this single-cell level model with clinicopathological features enabled accurate overall survival prediction and effective risk stratification in HCC patients. Our findings illuminate the potential of ferroptosis-related genes in tailoring therapy and prognosis prediction for HCC, offering novel insights into the intricate interplay among ferroptosis, immune response, and HCC progression.

T cell proliferation-based molecular subtypes and predictive signatures can be utilized to anticipate patient results, immunological landscape, and treatment response in CRC. Novel biomarker candidates and potential therapeutic drugs for CRC were identified and verified using in vitro and in vivo tests.

The ML approach helped construct novel diagnostic and prognostic models based on the expression profiling of BC. The identified nine-gene signature and eight-gene signatures showed excellent potential in BC diagnosis and prognosis, respectively.

The expression of ITM2A was low in patients with drug resistance of CML, and the low expression of ITM2A may be the key factor of imatinib resistance in CML.

In this study, the hypothesis that mutation-associated transcriptional profiles drive different outcomes in pediatric AML was investigated at the single cell level. We found genetic subtype-specific transcriptome differences in AML-blasts as well as differences in T cells might be contributing toward diverse clinical outcomes.

Mechanically, ITM2A upregulation mediates the sensitivity of cervical cancer cell through Notch signaling pathway. Our study suggests that ITM2A may serve as a target in mediating cisplatin-resistant cervical cancer.