Novel Immunohistochemical Profiling of Small-Cell Lung Cancer: Correlations Between Tumor Subtypes and Immune Microenvironment

Background/Objectives: Small-cell lung cancer (SCLC) is a highly aggressive malignancy with an emerging molecular classification based on the expression of the transcription factors ASCL1, NEUROD1, and POU2F3. This study aimed to explore the relationship between these novel subtypes and the tumor im...

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Vydáno v:Diagnostics (Basel) Ročník 14; číslo 23; s. 2660
Hlavní autoři: Vigdorovits, Alon, Olteanu, Gheorghe-Emilian, Pascalau, Andrei-Vasile, Pirlog, Radu, Berindan-Neagoe, Ioana, Pop, Ovidiu-Laurean
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland MDPI AG 01.12.2024
Témata:
Biopsy
Cancer therapies
Chemotherapy
Cloning
Development and progression
Gene expression
Genetic aspects
Health aspects
Histology
Kinases
Ligands
Lung cancer
Lung cancer, Small cell
Lymphocytes
Medical prognosis
Metastasis
molecular classification
Mortality
Mutation
Patients
Physiological aspects
Prognosis
SCLC
TILs
Transcription factors
tumor immune microenvironment
Tumors
Romania
United States > US
SCLC
TILs
tumor immune microenvironment
molecular classification
ISSN:2075-4418, 2075-4418
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Shrnutí:Background/Objectives: Small-cell lung cancer (SCLC) is a highly aggressive malignancy with an emerging molecular classification based on the expression of the transcription factors ASCL1, NEUROD1, and POU2F3. This study aimed to explore the relationship between these novel subtypes and the tumor immune microenvironment (TIME), particularly CD8+ and CD4+ tumor-infiltrating lymphocytes (TILs). Methods: In 51 cases of patients with SCLC, immunohistochemical (IHC) stains for ASCL1, NEUROD1, POU2F3, CD56, Ki67, CD8, and CD4 were performed. H-scores for the novel transcription factors were calculated to determine tumor subtype. CD8+ and CD4+ TIL counts were averaged across 10 high-power fields. The Kruskal–Wallis test and subsequent post hoc Dunn tests were used to determine the differences in transcription factor expression and TILs across subtypes. Results: In our cohort, 68.62% of our cases were SCLC-A, 9.80% were SCLC-N, 7.84% were SCLC-P, and 13.72% were SCLC-I. Significant differences were observed in the expression of ASCL1, NEUROD1, and POU2F3 across subtypes. CD8+ TILs were more abundant in SCLC-P and SCLC-I. CD8+ TILs were negatively correlated with ASCL1 expression (p < 0.05) and positively correlated with POU2F3 expression (p < 0.005). Conclusions: This study highlights the need to integrate the novel SCLC classification with data regarding the TIME to better inform patient prognosis and treatment.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2075-4418
2075-4418
DOI:10.3390/diagnostics14232660