SMARCA4 alterations in non-small cell lung cancer: a systematic review and meta-analysis.

AIMS: A mutation in the SMARCA4 gene which encodes BRG1, a common catalytic subunit of switch/sucrose non-fermentable chromatin-remodelling complexes, plays a vital role in carcinogenesis. SMARCA4 mutations are present in approximately 10% of non-small cell lung cancers (NSCLC), making it a crucial gene in NSCLC, but with varying prognostic associations. To explore this, we conducted a systematic review and meta-analysis on the prognostic significance of SMARCA4 mutations in NSCLC. METHODS: Electronic database search was performed from inception to December 2022. Study characteristics and prognostic data were extracted from each eligible study. Depending on heterogeneity, pooled HR and 95% CI were derived using the random-effects or fixed-effects models. RESULTS: 8 studies (11 cohorts) enrolling 8371 patients were eligible for inclusion. Data on overall survival (OS) and progression-free survival (PFS) were available from 8 (10 cohorts) and 1 (3 cohorts) studies, respectively. Comparing SMARCA4-mutated NSCLC patients with SMARCA4-wild-type NSCLC patients, the summary HRs for OS and PFS were 1.49 (95% CI 1.18 to 1.87; I2=84%) and 3.97 (95% CI 1.32 to 11.92; I2=79%), respectively. The results from the trim-and-fill method for publication bias and sensitivity analysis were inconsistent with the primary analyses. Three studies reported NSCLC prognosis for category I and II mutations separately; category I was significantly associated with OS. CONCLUSION: Our findings suggest that SMARCA4 mutation negatively affects NSCLC OS and PFS. The prognostic effects of SMARCA4-co-occurring mutations and the predictive role of SMARCA4 mutation status in immunotherapy require further exploration.

WhARIO: whole-slide-image-based survival analysis for patients treated with immunotherapy.

Purpose: Immune checkpoint inhibitors (ICIs) are now one of the standards of care for patients with lung cancer and have greatly improved both progression-free and overall survival, although <20% of the patients respond to the treatment, and some face acute adverse events. Although a few predictive biomarkers have integrated the clinical workflow, they require additional modalities on top of whole-slide images and lack efficiency or robustness. In this work, we propose a biomarker of immunotherapy outcome derived solely from the analysis of histology slides. Approach: We develop a three-step framework, combining contrastive learning and nonparametric clustering to distinguish tissue patterns within the slides, before exploiting the adjacencies of previously defined regions to derive features and train a proportional hazards model for survival analysis. We test our approach on an in-house dataset of 193 patients from 5 medical centers and compare it with the gold standard tumor proportion score (TPS) biomarker. Results: On a fivefold cross-validation (CV) of the entire dataset, the whole-slide image-based survival analysis for patients treated with immunotherapy (WhARIO) features are able to separate a low- and a high-risk group of patients with a hazard ratio (HR) of 2.29 (CI95=1.48 to 3.56), whereas the TPS 1% reference threshold only reaches a HR of 1.81 (CI95=1.21 to 2.69). Combining the two yields a higher HR of 2.60 (CI95=1.72 to 3.94). Additional experiments on the same dataset, where one out of five centers is excluded from the CV and used as a test set, confirm these trends. Conclusions: Our uniquely designed WhARIO features are an efficient predictor of survival for lung cancer patients who received ICI treatment. We achieve similar performance to the current gold standard biomarker, without the need to access other imaging modalities, and show that both can be used together to reach even better results.

Demographic Analysis of Cancer Research Priorities and Treatment Correlations.

Understanding the diversity in cancer research priorities and the correlations among different treatment modalities is essential to address the evolving landscape of oncology. This study, conducted in collaboration with the European Cancer Patient Coalition (ECPC) and Childhood Cancer International-Europe (CCI-E) as part of the "UNCAN.eu" initiative, analyzed data from a comprehensive survey to explore the complex interplay of demographics, time since cancer diagnosis, and types of treatments received. Demographic analysis revealed intriguing trends, highlighting the importance of tailoring cancer research efforts to specific age groups and genders. Individuals aged 45-69 exhibited highly aligned research priorities, emphasizing the need to address the unique concerns of middle-aged and older populations. In contrast, patients over 70 years demonstrated a divergence in research priorities, underscoring the importance of recognising the distinct needs of older individuals in cancer research. The analysis of correlations among different types of cancer treatments underscored the multidisciplinary approach to cancer care, with surgery, radiotherapy, chemotherapy, precision therapy, and biological therapies playing integral roles. These findings support the need for personalized and combined treatment strategies to achieve optimal outcomes. In conclusion, this study provides valuable insights into the complexity of cancer research priorities and treatment correlations in a European context. It emphasizes the importance of a multifaceted, patient-centred approach to cancer research and treatment, highlighting the need for ongoing support, adaptation, and collaboration to address the ever-changing landscape of oncology.

Multicenter evaluation of an automated, multiplex, RNA-based molecular assay for detection of ALK, ROS1, RET fusions and MET exon 14 skipping in NSCLC.

The current study assessed the performance of the fully automated RT-PCR-based Idylla™ GeneFusion Assay, which simultaneously covers the advanced non-small cell lung carcinoma (aNSCLC) actionable ALK, ROS1, RET, and MET exon 14 rearrangements, in a routine clinical setting involving 12 European clinical centers. The Idylla™ GeneFusion Assay detects fusions using fusion-specific as well as expression imbalance detection, the latter enabling detection of uncommon fusions not covered by fusion-specific assays. In total, 326 archival aNSCLC formalin-fixed paraffin-embedded (FFPE) samples were included of which 44% were resected specimen, 46% tissue biopsies, and 9% cytological specimen. With a total of 179 biomarker-positive cases (i.e., 85 ALK, 33 ROS1, 20 RET fusions and 41 MET exon 14 skipping), this is one of the largest fusion-positive datasets ever tested. The results of the Idylla™ GeneFusion Assay were compared with earlier results of routine reference technologies including fluorescence in situ hybridization, immunohistochemistry, reverse-transcription polymerase chain reaction, and next-generation sequencing, establishing a high sensitivity/specificity of 96.1%/99.6% for ALK, 96.7%/99.0% for ROS1, 100%/99.3% for RET fusion, and 92.5%/99.6% for MET exon 14 skipping, and a low failure rate (0.9%). The Idylla™ GeneFusion Assay was found to be a reliable, sensitive, and specific tool for routine detection of ALK, ROS1, RET fusions and MET exon 14 skipping. Given its short turnaround time of about 3 h, it is a time-efficient upfront screening tool in FFPE samples, supporting rapid clinical decision making. Moreover, expression-imbalance-based detection of potentially novel fusions may be easily verified with other routine technologies without delaying treatment initiation.

Developments in predictive biomarker testing and targeted therapy in advanced stage non-small cell lung cancer and their application across European countries.

In the past two decades, the treatment of metastatic non-small cell lung cancer (NSCLC), has undergone significant changes due to the introduction of targeted therapies and immunotherapy. These advancements have led to the need for predictive molecular tests to identify patients eligible for targeted therapy. This review provides an overview of the development and current application of targeted therapies and predictive biomarker testing in European patients with advanced stage NSCLC. Using data from eleven European countries, we conclude that recommendations for predictive testing are incorporated in national guidelines across Europe, although there are differences in their comprehensiveness. Moreover, the availability of recently EMA-approved targeted therapies varies between European countries. Unfortunately, routine assessment of national/regional molecular testing rates is limited. As a result, it remains uncertain which proportion of patients with metastatic NSCLC in Europe receive adequate predictive biomarker testing. Lastly, Molecular Tumor Boards (MTBs) for discussion of molecular test results are widely implemented, but national guidelines for their composition and functioning are lacking. The establishment of MTB guidelines can provide a framework for interpreting rare or complex mutations, facilitating appropriate treatment decision-making, and ensuring quality control.

Future perspective for the application of predictive biomarker testing in advanced stage non-small cell lung cancer.

For patients with advanced stage non-small cell lung cancer (NSCLC), treatment strategies have changed significantly due to the introduction of targeted therapies and immunotherapy. In the last few years, we have seen an explosive growth of newly introduced targeted therapies in oncology and this development is expected to continue in the future. Besides primary targetable aberrations, emerging diagnostic biomarkers also include relevant co-occurring mutations and resistance mechanisms involved in disease progression, that have impact on optimal treatment management. To accommodate testing of pending biomarkers, it is necessary to establish routine large-panel next-generation sequencing (NGS) for all patients with advanced stage NSCLC. For cost-effectiveness and accessibility, it is recommended to implement predictive molecular testing using large-panel NGS in a dedicated, centralized expert laboratory within a regional oncology network. The central molecular testing center should host a regional Molecular Tumor Board and function as a hub for interpretation of rare and complex testing results and clinical decision-making.

Real-world incidence and risk factors of pneumonitis in chemoradiation plus immune checkpoint inhibitors compared with chemoradiation alone in lung cancer: a retrospective cohort study.

Background: Immune checkpoint inhibitors (ICIs) have shown high efficacy in lung cancer. Adding ICIs to chemoradiation might increase the treatment efficacy, while the application of ICIs or chemoradiation alone can induce treatment-related pneumonitis, so whether combination therapy would increase the risk of pneumonitis needs careful evaluation. This study aimed to retrospectively analyze the incidence of pneumonitis in patients who underwent chemoradiation combined with ICIs compared with chemoradiation alone and explore the risk factors of pneumonitis in combination therapy. Methods: This was a retrospective cohort study. Patients who received conventional thoracic radiation with a minimum total dose of 50 Gy for lung cancer between January 2020 and December 2021 at West China Hospital were retrospectively reviewed and followed up for at least 6 months after radiation. Patients were divided into two groups according to whether chemoradiation was administered with or without ICIs. Pneumonitis was evaluated by chest computed tomography (CT) at least every 2 months in outpatient department. The clinical characteristics, including sex, age, smoking history, pathological diagnosis, baseline pulmonary disease [including chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD)], treatment strategy, location of primary tumor and radiological dosimetric parameters were recorded. Chi-squared tests or Fisher's exact tests were performed to analyze the difference between the combination group and control group for categorical variables and Mann-Whitney U test for continuous variables. Univariate and multivariate analyses were performed by logistic regression. Results: A total of 152 patients who received chemoradiation were enrolled. The median age was 59 years. A total of 115 (75.7%) patients were non-small cell lung cancer (NSCLC), 22 (14.5%) were small cell lung cancer (SCLC), and 15 (9.9%) were other pathological types. Among them, 58 received chemoradiation combined with ICIs and 94 received chemoradiation alone. The rate of grade ≥2 pneumonitis was significantly higher in the combination therapy group (39.7% vs. 22.3%, P=0.028) and was associated with the use of ICIs [odds ratio (OR): 2.641, 95% confidence interval (CI): 1.244-5.608, P=0.011] and percent volume of the lung receiving ≥30 Gy (V30) (OR: 1.728, 95% CI: 1.214-2.460, P=0.002). The history of chronic lung disease was the independent risk factor (OR: 6.359, 95% CI: 1.953-20.705, P=0.002) of grade ≥3 pneumonitis. In the combination group, univariate and multivariate analyses revealed that V5, V20, V30, and mean lung dose (MLD) were not associated with pneumonitis, whereas the history of chronic lung disease was an independent risk factor of grade ≥3 pneumonitis (OR: 8.351, 95% CI: 1.469-47.484, P=0.017). Conclusions: The incidence of pneumonitis of ICIs combined with chemoradiation was higher than chemoradiation alone, but manageable. The combination therapy should be applied with caution especially in patients with history of chronic lung disease.

Integrating artificial intelligence into lung cancer screening: a randomised controlled trial protocol.

INTRODUCTION: Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%-25%.Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects.Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting. METHODS AND ANALYSIS: This open-label randomised controlled study focuses on LCS for patients aged 50-80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant. ETHICS AND DISSEMINATION: The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations. TRIAL REGISTRATION NUMBER: NCT05704920.

Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes.

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.

Tackling the implementation gap for the uptake of NGS and advanced molecular diagnostics into healthcare systems.

Next-generation sequencing (NGS) and liquid biopsy (LB) showed positive results in the fight against different cancer types. This paper aims to assess the uptake of advanced molecular diagnostics/NGS for quick and efficient genetic profiles of tumour cells. For that purpose, the European Alliance for Personalised Medicine conducted a series of expert interviews to ascertain the current status across member states. One stakeholder meeting was additionally conducted to prioritize relevant factors by stakeholders. Seven common pillars were identified, and twenty-five measures were defined based on these pillars. Results showed that a multi-faceted approach is necessary for successful NGS implementation and that regional differences may be influenced by healthcare policies, resources, and infrastructure. It is important to consider different correlations when interpreting the results and to use them as a starting point for further discussion.

Aligning Cancer Research Priorities in Europe with Recommendations for Conquering Cancer: A Comprehensive Analysis.

Improvements in cancer care require a new degree of collaboration beyond the purely medical sphere, extending deeply into the world of other stakeholders-preeminently patients but also the other stakeholders in the hardware and software of care. Cancer remains a global health challenge, necessitating collaborative efforts to understand, prevent, and treat this complex disease. To achieve this goal, a comprehensive analysis was conducted, aligning the prioritization of cancer research measures in 13 European countries with 13 key recommendations for conquering cancer in the region. The study utilized a survey involving both patients and citizens, alongside data from IQVIA, a global healthcare data provider, to assess the availability and access to single-biomarker tests in multiple European countries. The results revealed a focused approach toward understanding, preventing, and treating cancer, with each country emphasizing specific research measures tailored to its strengths and healthcare objectives. This analysis highlights the intricate relationship between research priorities, access to biomarker tests, and financial support. Timely access to tests and increased availability positively influence research areas such as cancer prevention, early detection, ageing, and data utilization. The alignment of these country-specific measures with 13 recommendations for conquering cancer in Europe underscores the importance of tailored strategies for understanding, preventing, and treating cancer.

An in-silico analysis reveals further evidence of an aggressive subset of lung carcinoids sharing molecular features of high-grade neuroendocrine neoplasms.

Little is known as to whether there may be any pathogenetic link between pulmonary carcinoids and neuroendocrine carcinomas (NECs). A gene signature we previously found to cluster pulmonary carcinoids, large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC), and which encompassed MEN1, MYC, MYCL1, RICTOR, RB1, SDHA, SRC and TP53 mutations or copy number variations (CNVs), was used to reclassify an independent cohort of 54 neuroendocrine neoplasms (NENs) [31 typical carcinoids (TC), 11 atypical carcinoids (AC) and 12 SCLC], by means of transcriptome and mutation data. Unsupervised clustering analysis identified two histology-independent clusters, namely CL1 and CL2, where 17/42 (40.5%) carcinoids and all the SCLC samples fell into the latter. CL2 carcinoids affected survival adversely, were enriched in T to G transversions or T > C/C > T transitions in the context of specific mutational signatures, presented with at least 1.5-fold change (FC) increase of gene mutations including TSC2, SMARCA2, SMARCA4, ERBB4 and PTPRZ1, differed for gene expression and showed epigenetic changes in charge of MYC and MTORC1 pathways, cellular senescence, inflammation, high-plasticity cell state and immune system exhaustion. Similar results were also found in two other independent validation sets comprising 101 lung NENs (24 carcinoids, 21 SCLC and 56 LCNEC) and 30 carcinoids, respectively. We herein confirmed an unexpected sharing of molecular traits along the spectrum of lung NENs, with a subset of genomically distinct aggressive carcinoids sharing molecular features of high-grade neuroendocrine neoplasms.

Optimizing tissue stewardship in non-small cell lung cancer to support molecular characterization and treatment selection: statement from a working group of thoracic pathologists.

Many patients with non-small cell lung cancer do not receive guideline-recommended, biomarker-directed therapy, despite the potential for improved clinical outcomes. Access to timely, accurate, and comprehensive molecular profiling, including targetable protein overexpression, is essential to allow fully informed treatment decisions to be taken. In turn, this requires optimal tissue management to protect and maximize the use of this precious finite resource. Here, a group of leading thoracic pathologists recommend factors to consider for optimal tissue management. Starting from when lung cancer is first suspected, keeping predictive biomarker testing in the front of the mind should drive the development of practices and procedures that conserve tissue appropriately to support molecular characterization and treatment selection.

Molecular profiling in cholangiocarcinoma: A practical guide to next-generation sequencing.

Cholangiocarcinomas (CCA) are a heterogeneous group of tumors that are classified as intrahepatic, perihilar, or distal according to the anatomic location within the biliary tract. Each CCA subtype is associated with distinct genomic alterations, including single nucleotide variants, copy number variants, and chromosomal rearrangements or gene fusions, each of which can influence disease prognosis and/or treatment outcomes. Molecular profiling using next-generation sequencing (NGS) is a powerful technique for identifying unique gene variants carried by an individual tumor, which can facilitate their accurate diagnosis as well as promote the optimal selection of gene variant-matched targeted treatments. NGS is particularly useful in patients with CCA because between one-third and one-half of these patients have genomic alterations that can be targeted by drugs that are either approved or in clinical development. NGS can also provide information about disease evolution and secondary resistance alterations that can develop during targeted therapy, and thus facilitate assessment of prognosis and choice of alternative targeted treatments. Pathologists play a critical role in assessing the viability of biopsy samples for NGS, and advising treating clinicians whether NGS can be performed and which of the available platforms should be used to optimize testing outcomes. This review aims to provide clinical pathologists and other healthcare professionals with practical step-by-step guidance on the use of NGS for molecular profiling of patients with CCA, with respect to tumor biopsy techniques, pre-analytic sample preparation, selecting the appropriate NGS panel, and understanding and interpreting results of the NGS test.

Current challenges and practical aspects of molecular pathology for non-small cell lung cancers.

The continuing evolution of treatment options in thoracic oncology requires the pathologist to regularly update diagnostic algorithms for management of tumor samples. It is essential to decide on the best way to use tissue biopsies, cytological samples, as well as liquid biopsies to identify the different mandatory predictive biomarkers of lung cancers in a short turnaround time. However, biological resources and laboratory member workforce are limited and may be not sufficient for the increased complexity of molecular pathological analyses and for complementary translational research development. In this context, the surgical pathologist is the only one who makes the decisions whether or not to send specimens to immunohistochemical and molecular pathology platforms. Moreover, the pathologist can rapidly contact the oncologist to obtain a new tissue biopsy and/or a liquid biopsy if he/she considers that the biological material is not sufficient in quantity or quality for assessment of predictive biomarkers. Inadequate control of algorithms and sampling workflow may lead to false negative, inconclusive, and incomplete findings, resulting in inappropriate choice of therapeutic strategy and potentially poor outcome for patients. International guidelines for lung cancer treatment are based on the results of the expression of different proteins and on genomic alterations. These guidelines have been established taking into consideration the best practices to be set up in clinical and molecular pathology laboratories. This review addresses the current predictive biomarkers and algorithms for use in thoracic oncology molecular pathology as well as the central role of the pathologist, notably in the molecular tumor board and her/his participation in the treatment decision-making. The perspectives in this setting will be discussed.

The use of minimal residual disease in thoracic oncology: Gaps between promises and the on-the-ground reality of daily practice.

The assessment of minimal residual disease (MRD) from blood samples of patients with resected non-small cell lung carcinoma (NSCLC) is promising and opens up many opportunities for the optimisation of patient care in daily practice. Notably, this includes the potential for escalation or de-escalation of adjuvant therapies. Thus, the evaluation of MRD status can directly contribute to an increase in the overall survival of early stage NSCLC patients and/or limit therapeutic but also "financial" toxicity. Therefore, several clinical trials recently evaluated MRD in early stage NSCLC by integrating and retrospectively comparing the results of MRD assessments. In this context, there is an urgent need to close the gap between clinical research and the use of the evaluation of MRD in routine daily practice. Further action needs to be taken, particularly in evaluating the pertinence of the detection of MRD in prospective interventional clinical studies. This may be done in part by comparing different parameters, such as the techniques used, the different time points and the cutoffs of MRD assessments. This article investigates the assessment of MRD in non-small cell lung cancers, with a special focus on the issues associated with the various assays and the limitations of using circulating free DNA analyses for MRD assessment in early stage lung cancer. Recommendations and tips for the optimisation of MRD evaluation in non-small cell lung cancers are provided.

c-Met immunohistochemistry as reflex test at diagnosis for non-small cell lung cancer: a real-world experience from a monocentric case series.

AIMS: Recent clinical trials have shown promising results with drugs targeting the hepatocyte growth factor receptor (c-Met) for advanced non-small cell lung cancers overexpressing c-Met. We assessed reflex testing of c-Met immunohistochemistry (IHC) at diagnosis for NSCLC in the real-world. METHODS: We retrospectively collected clinical, pathological and molecular data of cases diagnosed with NSCLC in our institution from January 2021 to June 2023. We performed c-Met IHC (SP44 clone) and scored the expression using a H-score and a three-tier classification. RESULTS: 391 cases with interpretable c-Met IHC staining were included. The median age at diagnosis was 70 years (range 25-89 years) including 234 males (male/female ratio 1:5). 58% of the samples came from surgical resections, 35% from biopsies and 8% from cytological procedures. 52% of cases were classified as c-Met-positive (H-score≥150) and 19% were classified as c-Methigh (≥50%, 3+). 43% of the c-Metneg presented with lymph node and/or visceral metastases at diagnosis vs 55% for c-Methigh (p=0.042). 23% of the adenocarcinomas showed c-Methigh expression vs 3% for squamous cell carcinomas (p=0.004). 27% of the c-Metneg cases had a high PD-L1 expression vs 58% of c-Methigh cases (p<0.001). MET ex14 skipping was present in 8% of the c-Methigh cases. CONCLUSIONS: Systematic c-Met testing in daily routine for NSCLC patients is feasible, highlighting a potential correlation with clinicopathological and molecular features.

Prognostic Role of KRAS G12C Mutation in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.

KRAS G12C mutation (mKRAS G12C) is the most frequent KRAS point mutation in non-small cell lung cancer (NSCLC) and has been proven to be a predictive biomarker for direct KRAS G12C inhibitors in advanced solid cancers. We sought to determine the prognostic significance of mKRAS G12C in patients with NSCLC using the meta-analytic approach. A protocol is registered at the International Prospective Register for systematic reviews (CRD42022345868). PubMed, EMBASE, The Cochrane Library, and Clinicaltrials.gov.in were searched for prospective or retrospective studies reporting survival data for tumors with mKRAS G12C compared with either other KRAS mutations or wild-type KRAS (KRAS-WT). The hazard ratios (HRs) for overall survival (OS) or Disease-free survival (DFS) of tumors were pooled according to fixed or random-effects models. Sixteen studies enrolling 10,153 participants were included in the final analysis. mKRAS G12C tumors had poor OS [HR, 1.42; 95% CI, 1.10-1.84, p = 0.007] but similar DFS [HR 2.36, 95% CI 0.64-8.16] compared to KRAS-WT tumors. Compared to other KRAS mutations, mKRAS G12C tumors had poor DFS [HR, 1.49; 95% CI, 1.07-2.09, p < 0.0001] but similar OS [HR, 1.03; 95% CI, 0.84-1.26]. Compared to other KRAS mutations, high PD-L1 expression (>50%) [OR 1.37 95% CI 1.11-1.70, p = 0.004] was associated with mKRAS G12C tumors. mKRAS G12C is a promising prognostic factor for patients with NSCLC, negatively impacting survival. Prevailing significant heterogeneity and selection bias might reduce the validity of these findings. Concomitant high PD-L1 expression in these tumors opens doors for exciting therapeutic potential.