Abstract 165P
Background
Lung cancer is the most common cancer in men (14.3%) and 3rd most common cancer in female (8.4%) but account for overall highest cancer related mortality (18%). In India, lung cancer is 4th most common cancer both in incidence and cancer related death. NSCLC is the most common type accounting about 80-85% cases and among these adenocarcinoma accounts for more than half and is further defined according to different molecular subtypes by the identification of oncogenic drivers. With recent advances in the knowledge of NSCLC biology, various oncogenic driver mutations are identified which causes aberrant activation of intracellular signaling pathways associated with the sustained growth of lung cancer cells. Research objectives: Evaluation the mutational profile of NSCLC with broad panel-based next-generation sequencing.
Methods
The study was a hospital based prospective, cross sectional descriptive study conducted at a tertiary care center in Northeast India done during the period from 1st january,2022 to 31st December,2022. Ninteen cases of histologically proven meatstatic NSCLC in core biopsy were included in this study.
Results
The age of patients with NSCLC in our study ranged from 48 to 80 years with mean age of 64.36(+/-9.82) years. Majority of the patients in our study were from the age category 71-80 years (37%) Male to female ratio was 19:1 (95% vs 5%). 73.3% of cases were chronic smokers while 26.3% were nonsmokers with smoker non-smoker ratio of 2.79:1.100% of cases presented in late stage (Stages IV). Regarding biomarker profile of NSCLC in our study, EGFR mutation positivity was seen in 10.5%.ALK rearrangement was positive in 5.3% of patients. In our study PD-L1 expression positivity was57.9% and among these patients,18.2% has TPS>50% whereas 81.8% showed TPS<50%.
Conclusions
Adenocarcinoma is the predominant histological subtype of NSCLC in the region of NE India, with a high proportion of cases harboring EGFR mutation. Moreover, NSCLC is characterized with unique mutations and cannot be generalized in larger context. So, study with larger sample size should be encouraged for evaluation of molecular profile of NSCLC in this region.
Editorial acknowledgement
Clinical trial identification
Legal entity responsible for the study
Assam Medical College, Dibrugarh.
Funding
Has not received any funding.
Disclosure
The author has declared no conflicts of interest.
Resources from the same session
145P - Identification of next generation sequencing (NGS)-based genomic signature predicting resistance to immunotherapy (IO) in patients (pts) with metastatic non-small cell lung cancer (mNSCLC): A single-center cohort study
Presenter: Antonio Vitale
Session: Cocktail & Poster Display session
Resources:
Abstract
146P - The prognosis value of heat-shock proteins in esophagogastric cancer: A systematic review and meta-analysis
Presenter: Eric Nakamura
Session: Cocktail & Poster Display session
Resources:
Abstract
148P - Identification of potential predictive biomarkers for ovarian cancer chemotherapy response
Presenter: Alsina Nurgalieva
Session: Cocktail & Poster Display session
Resources:
Abstract
149P - Rare RAS mutations are associated with recurrence patterns and recurrence-free survival in colon cancer: First results from Morocco
Presenter: Fatima Agy
Session: Cocktail & Poster Display session
Resources:
Abstract
151P - Development of a predictive model for response to neoadjuvant chemoradiation therapy of rectal cancer using the immunologic profile
Presenter: Eun Shin
Session: Cocktail & Poster Display session
Resources:
Abstract
152P - Biomarkers of neoadjuvant chemoradiotherapy response in locally advanced rectal cancer
Presenter: Cibele Masotti
Session: Cocktail & Poster Display session
Resources:
Abstract
153P - BRAF variants and therapy outcomes in melanoma
Presenter: Eftychia Chatziioannou
Session: Cocktail & Poster Display session
Resources:
Abstract
154P - The impact of proton pump inhibitors in the prognosis of patients with non-metastatic nasopharyngeal carcinoma
Presenter: João Barbosa Martins
Session: Cocktail & Poster Display session
Resources:
Abstract
155P - Use of machine learning for the identification of molecular biomarkers to predict response to neoadjuvant chemotherapy in locally advanced breast cancer patients
Presenter: María Del Río Pisula
Session: Cocktail & Poster Display session
Resources:
Abstract
156P - Molecularly driven therapy recommended by a molecular tumor board: Accessible option or privilege for a minority of patients? A single-center experience from the Czech Republic
Presenter: Michal Eid
Session: Cocktail & Poster Display session
Resources:
Abstract