Cytomorphological features as predictors of epidermal growth factor receptor mutation status in lung adenocarcinoma

An emerging era of computational cytology

BACKGROUND

The significant advancement in digital imaging, data management, advanced computational power, and artificial neural network have an immense impact on the field of cytology. The amalgamation of these areas has generated a newer discipline known as computational cytology.

AIMS AND OBJECTIVE

In To discuss the various important aspects of computational cytology.

MATERIALS AND METHODS

We reviewed the different studies published in English during the last few years on computational cytology.

RESULT

Computational cytology is a newer and emerging discipline in pathology that deals with the patient's meta-data and digital image data to make a mathematical model to produce diagnostic interpretations and predictions. The role of the cytologist is now changing from a simple observational scientist and slide interpreter to a dynamic and integrated multi-parametric prediction-based scientist.

CONCLUSION

In the current stage, the cytologist must understand the situation and should have a vision of the complete scenario on computational cytology.

Differential expression of PD-L1 and IDO1 in association with the immune microenvironment in resected lung adenocarcinomas

Like programmed cell death ligand 1 (PD-L1), indoleamine 2,3-dioxygenase 1 (IDO1) is known to exert immunosuppressive effects and be variably expressed in human lung cancer. However, IDO1 expression has not been well studied in lung adenocarcinoma. PD-L1 and IDO1 expression was evaluated in 261 resected lung adenocarcinomas using tissue microarrays and H-scores (cutoff: 5). We compared IDO1 and PD-L1 expression with clinical features, tumor-infiltrating lymphocytes, HLA class I molecule expression, molecular alterations, and patient outcomes. There was expression of PD-L1 in 89 (34%) and IDO1 in 74 (29%) cases, with co-expression in 49 (19%). Both PD-L1 and IDO1 were significantly associated with smoking, aggressive pathologic features, and abundant CD8+ and T-bet+ (Th1 marker) tumor-infiltrating lymphocytes. PD-L1 expression was also associated with preserved HLA class I molecule expression (p = 0.002). Compared to PD-L1+/IDO1+ and PD-L1+ only cases, significantly fewer IDO1+ only cases had abundant CD8+ and T-bet+ tumor-infiltrating lymphocytes (p < 0.001, respectively). PD-L1 expression was significantly associated with EGFR wild-type (p < 0.001) and KRAS mutants (p = 0.021), whereas isolated IDO1 expression was significantly associated with EGFR mutations (p = 0.007). As for survival, PD-L1 was a significant predictor of decreased progression-free and overall survival by univariate but not multivariate analysis, while IDO1 was not associated with progression-free or overall survival. Interestingly, there was a significant difference in the 5-year progression-free and overall survival (p = 0.004 and 0.038, respectively), where cases without PD-L1 or IDO1 expression had the longest survival, and those with PD-L1 alone had the shortest survival. While PD-L1+/-IDO1 expression is observed in association with HLA class I expression, cytotoxic T lymphocyte/Th1 microenvironments, EGFR wild-type, and KRAS mutations, isolated IDO1 expression does not demonstrate these associations, suggesting that IDO1 may serve a distinct immunosuppressive role in lung adenocarcinomas. Thus, further investigation of IDO1 may demonstrate its role as a potential biomarker for patients who undergo anti-PD-1/PD-L1 therapy.