Background

India presents a diverse genetic pool with varying cancer incidence patterns. Common cancers in the Indian population include head and neck, lung, breast, colorectal, prostate, ovarian, and gastrointestinal cancers. Understanding the distribution of circulating tumor cells (CTCs) across these cancers may help account for cellular minimal residual disease (MRD) and early recurrence in solid tumors. Surgery with curative intent can be further evaluated for residual disease using dual biomarkers such as ctDNA and CTCs.

Methods

In this retrospective analysis, peripheral blood samples from 5,935 patients across various cancer types—including head and neck, lung, breast, colorectal, prostate, ovarian, and gastrointestinal cancers—were evaluated for the presence of CTCs, with and without PD-L1 overexpression and CTC clusters. CTCs were detected using the OncoDiscover platform approved by CDSCO in 1.5 mL of peripheral blood. The platform utilizes a multifunctional magneto-nanosystem mediated by anti-epithelial cell adhesion molecule (EpCAM) antibodies. CTCs were confirmed as EpCAM⁺, CK18⁺, DAPI⁺, and CD45⁻ cells. PD-L1 expression on CTCs was analyzed using linear fluorescence intensity gradients acquired through an automated Zeiss microscope. Additionally, a computational model was developed to evaluate CTC frequency, mean distribution, regression analysis, and normal probability plots to assess predictability across cancer types, age groups, stages, and genders.

Results

The study included 5,935 patient blood samples, comprising 90.07% baseline and 9.92% follow-up samples. CTC counts ranged from 1 to 10 per 1.5 mL of blood, with a mean value of 1.12. Among the patients, 69.87% (n = 2,854) demonstrated PD-L1 expression on their CTCs, with a mean value of 0.99. The 51–60-year age group exhibited the highest proportion of both total CTCs (19.16%, n = 1,137) and PD-L1–positive CTCs (19.71%, n = 805). Most CTC clusters were identified in breast, colorectal, and endometrial cancers. Pancreatic cancer patients showed the highest mean CTC count (1.4), whereas laryngeal cancer samples had the lowest mean count (0.78). The computational model indicated that the 51–60-year age group had the highest impact on cancer prevalence and mean CTC distribution. The model also demonstrated a strong correlation between blood-based outcomes and normal probability scores.

Conclusions

Higher CTC counts were strongly associated with advanced disease stages, particularly in cancers prone to hematogenous spread, such as breast, lung, and prostate cancers. Incorporating CTC profiling from baseline into diagnostic and surveillance strategies may enhance personalized cancer management. The presence of CTCs in disease-free survival (DFS) settings suggests potential links to poor therapeutic response, disease progression, and minimal residual disease.