Tuğrul Burak Genç

Dr. Tuğrul Burak Genç

orcid

Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 May 2026 in Preprints.org
Verified
Preprint
Open access
PDF file
AÇAlperen Akansel Çağlar
Alperen Akansel Çağlar
AÖAykut Özmen
Aykut Özmen
TGTuğrul Burak Genç
Tuğrul Burak Genç
AYAnıl Yıldız
Anıl Yıldız
OCOzde Melisa Celayir
Ozde Melisa Celayir
NBNilufer Bulut
Nilufer Bulut
Background: Non–small cell lung cancer (NSCLC) is one of the most commonly diagnosed malignancies and a leading cause of cancer-related mortality worldwide. Although immune checkpoint inhibitors such as nivolumab have become a standard option in the second-line and later-line settings, identifying patients who derive meaningful benefit remains challenging. Established biomarkers, including PD-L1 expression, have shown limited predictive performance. The Lung Immune Prognostic Index (LIPI), a simple score reflecting systemic inflammation and tumor burden, has emerged as a potential prognostic tool. However, its real-world prognostic value in patients receiving nivolumab after first-line therapy remains insufficiently defined. Methods: This retrospective, single-center study included 109 patients with advanced NSCLC who received nivolumab following disease progression after first-line therapy. LIPI was calculated based on derived neutrophil-to-lymphocyte ratio (dNLR ≥3) and lactate dehydrogenase (LDH) levels above the upper limit of normal. Patients were stratified into three groups (LIPI 0-1-2). Progression-free survival (PFS) and overall survival (OS) were analyzed using the Kaplan–Meier method and compared with the log-rank test. Multivariable Cox proportional hazards models were used to identify independent prognostic factors. Results: Patients were categorized as LIPI 0 (n=32), LIPI 1 (n=45), and LIPI 2 (n=32). A clear stepwise deterioration in outcomes was observed across increasing LIPI categories. Median PFS was not reached in the LIPI 0 group, and was 340 days and 109 days in the LIPI 1 and LIPI 2 groups, respectively (p < 0.001). Similarly, median OS was not reached in the LIPI 0 group, while it was 820 days and 201 days in the LIPI 1 and LIPI 2 groups, respectively (p < 0.001). In multivariable analysis, LIPI remained independently associated with both PFS and OS. In contrast, PD-L1 expression and other clinicopathological variables were not independently associated with survival outcomes, suggesting that the prognostic impact of LIPI is independent of PD-L1. Conclusions: LIPI appears to be a robust, readily available prognostic marker in patients with advanced NSCLC treated with nivolumab beyond the first-line setting. Its independent association with survival outcomes, irrespective of PD-L1 expression, suggests that it captures distinct biological processes related to systemic inflammation. Incorporation of LIPI into routine clinical practice may improve risk stratification and support more individualized treatment decisions. Notably, LIPI may provide complementary prognostic information beyond tumor-specific biomarkers such as PD-L1.

8 September 2026 in Diagnostics
Verified
Journal Article
Open access
PDF file
AÇAlperen Akansel Çağlar
Alperen Akansel Çağlar
AÖAykut Özmen
Aykut Özmen
TGTuğrul Burak Genç
Tuğrul Burak Genç
AYAnıl Yıldız
Anıl Yıldız
OCOzde Melisa Celayir
Ozde Melisa Celayir
NBNilufer Bulut
Nilufer Bulut
Background: The Lung Immune Prognostic Index (LIPI), based on the derived neutrophil-to-lymphocyte ratio and lactate dehydrogenase, may reflect systemic inflammation and tumor-related metabolic burden. This study evaluated the prognostic value of pretreatment LIPI and its relationship with programmed death-ligand 1 (PD-L1) expression in patients with advanced non-small cell lung cancer (NSCLC) receiving nivolumab after first-line therapy. Methods: A total of 158 patients were included in this retrospective, single-center study. Patients were classified into LIPI 0, LIPI 1, or LIPI 2 groups according to their pretreatment LIPI scores. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan–Meier analysis and multivariable Cox regression. The prognostic value of LIPI was also evaluated within PD-L1-negative and PD-L1-positive subgroups, and LIPI × PD-L1 interactions were explored. Harrell’s concordance index was used to examine whether adding LIPI improved model discrimination beyond clinical variables and PD-L1 expression. PD-L1 data were available for 145 patients. Results: Median PFS was 566, 340, and 109 days for the LIPI 0, LIPI 1, and LIPI 2 groups, respectively, while median OS was 841, 760, and 201 days, respectively; the differences were statistically significant for both outcomes (both p < 0.001). The objective response rate (ORR) was 55.6%, 36.5%, and 4.9%, whereas the disease control rate (DCR) was 75.9%, 65.1%, and 14.6% in the LIPI 0, LIPI 1, and LIPI 2 groups, respectively (both p < 0.001). In multivariable analyses, higher LIPI remained independently associated with shorter PFS and OS, with the strongest association observed in the LIPI 2 group. LIPI also differentiated survival outcomes within both PD-L1-negative and PD-L1-positive subgroups, although no significant LIPI × PD-L1 interaction was identified for PFS or OS. The addition of LIPI increased the C-index from 0.583 to 0.698 for PFS (ΔC-index, 0.115; p < 0.001) and from 0.588 to 0.697 for OS (ΔC-index, 0.109; p = 0.003). Conclusions: Pretreatment LIPI was independently associated with PFS and OS in patients with advanced NSCLC receiving nivolumab after first-line therapy. Its association remained after adjustment for available PD-L1 expression data, and its addition improved model discrimination. These findings suggest that LIPI may provide prognostic information complementary to PD-L1 expression and routinely available clinical factors.

1 January 2026 in Eurasian Journal of Medical Investigation
Verified
Journal Article
Closed access
PDF file
NDNazan Demir
Nazan Demir
CKCevat İlTeriş Kıkılı
Cevat İlTeriş Kıkılı
BKBahadır Köylü
Bahadır Köylü
FKFatih Kemik
Fatih Kemik
TGTuğrul Burak Genç
Tuğrul Burak Genç
FSFatih Selçukbiricik
Fatih Selçukbiricik
Ejmi Eurasian Journal of Medical Investigation