Background: Cancer marker expression analysis through immunohistochemistry (IHC) plays a crucial role in diagnosis, prognosis, and treatment selection. This study aimed to evaluate the expression patterns of specific cancer markers using IHC in tumor samples and correlate these findings with clinicopathological parameters in a tertiary care setting. Methods: A prospective observational study was conducted over 6 months, analyzing 96 tumor samples through automated immunohistochemistry. Five key cancer markers (Ki-67, p53, HER2/neu, PD-L1, and EGFR) were evaluated for expression patterns and intensity. The correlations between marker expression and clinicopathological parameters were assessed using standardized scoring systems and statistical analysis. Results: Ki-67 showed the highest positivity rate (75.0%), followed by p53 (64.6%), while HER2/neu expression was observed in 41.7% of cases. Moderate staining intensity predominated across all markers (39.8-43.5%). Significant correlations were observed between marker expression and tumor grade (p<0.001), particularly for Ki-67 and p53. Lymph node positivity showed strong associations with marker expression, notably in Ki-67 (68.1%) and p53 (63.5%) positive cases. Multivariate analysis revealed significant associations between marker expression and tumor size (OR: 2.31, 95% CI: 1.52-3.48) and lymph node status (OR: 2.95, 95% CI: 1.84-4.72). Conclusion: The study demonstrates significant correlations between cancer marker expression and clinicopathological parameters, highlighting their potential in predicting disease outcomes and guiding therapeutic decisions. The findings support the utility of immunohistochemical markers in cancer diagnostics and prognostication.