Subtyping of advanced lung cancer based on PD-L1 expression, tumor histopathology and mutation burden (EGFR and KRAS): a study from North India.

Immune checkpoint inhibitor (PD-L1) therapy of advanced non-small-cell lung cancer (NSCLC) has variable outcomes. Tumor subtypes based on PD-L1 expression, histopathology, mutation burden is required for patient stratification and formulation of treatment guidelines. Lung cancers (n=57) diagnosed at Pathology department, VPCI (2018-2021) were retrospectively analyzed. PD-L1(SP263) expressed by tumor cells [low (<1%), medium (1-49%), high (≥50%)] was correlated with histopathology, microenvironment, EGFR, KRAS expression. Patients were categorized into high and low risk based on their: i) gender: males (n=47, 30-89 years), females (n=10, 45-80 years); ii) smoking history: males 26/47 (45.61%), females 1/10 (10%); iii) tumor subtyping: squamous cell carcinoma 15/57 (26.32%), adenocarcinoma 6/57 (17.54%), NSCLC-undifferentiated 24/57 (42.10%), adenosquamous carcinoma 5/57 (8.77 %), carcinosarcoma 4/57 (7.02%), small cell carcinoma 1/57 (1.75%); iv) inflammatory tumor microenvironment/TILs 44/57 (77.1%); iv) PD-L1 positivity-31/57 (54.3%); v) concomitant EGFR/KRAS positivity. PD-L1positive cases showed squamous/undifferentiated histopathology, concomitant EGFR+ (9/20, 45%) and KRAS+ (8/15, 53.3%), smoking+ (21/31,67.74%).PD-L1 negative cases (26/57, 45.6%), were EGFR+ (2/14, 14.28%) and KRAS+ (6/19, 31.5%). The high-risk lung cancer subtypes show squamous/undifferentiated histopathology, inflammatory microenvironment, male preponderance, smoking history, higher concomitant PD-L1, KRAS and EGFR positivity. Lung cancer subtyping can predict clinical response/resistance of patients prior to initiation of PD-L1 inhibitor therapies and can be used to guide therapy.

Distribution of airborne microbes and antibiotic susceptibility pattern of bacteria during Gwalior trade fair, Central India.

BACKGROUND/PURPOSE: Research into the distribution of bioaerosols during events associated with huge groups of people is lacking, especially in developing countries. The purpose of this study was to understand the distribution pattern of bioaerosols during an annual trade fair in the historical city of Gwalior, central India, a very important historical fair that was started by the King of Gwalior Maharaja Madho Rao in 1905. METHODS: Air samples were collected from six different sites at the fair ground and three different sites in a residential area before/during/after the fair using an impactor sampler on microbial content test agar and rose bengal agar for total bacteria and fungi, respectively. The representative strains of bacteria and fungi were further identified and selected bacterial strains were subjected to antibiotic susceptibility testing according to US Clinical and Laboratory Standards Institute (CLSI) guidelines. RESULTS: The bacterial bioaerosol count [colony-forming units (CFU)/m(3)] at fair sites was found to be 9.0 × 10(3), 4.0 × 10(4), and 1.0 × 10(4) before the start of the fair, during the fair, and after the fair, respectively. The fungal bioaerosol count at fair sites was 2.6 × 10(3) CFU/m(3), 6.3 × 10(3) CFU/m(3), and 1.7 × 10(3) CFU/m(3) before the fair, during the fair, and after the fair, respectively. Bacterial/fungal bioaerosols during-fair were increased significantly from the bacterial/fungal bioaerosols of the before-fair period (p < 0.05); they were also significantly higher than the bacterial/fungal bioaerosols at non-fair sites during the event (p < 0.0001). The proportion of antibiotic-resistant bacteria over the fair ground was significantly increased during-fair and was still higher in the after-fair period. Methicillin-resistant staphylococci (MRS) were also reported at the fair ground. CONCLUSION: The study indicates significantly higher bacterial and fungal bioaerosols during the fair event. Therefore, further research is needed to explore the health aspects and guidelines to control microbial load during such types of events.