Cancer Driver Mutations Research Articles

STEM-05. SHARED ONCOGENIC MUTATIONS IN THE SUBVENTRICULAR ZONE AND GLIOBLASTOMA: GENETIC AND CLINICAL IMPLICATIONS

Abstract The subventricular zone (SVZ), a neurogenic niche in the adult brain, is suspected to harbor neural stem cells (NSCs) that can acquire cancer-driving mutations and give rise to glioblastoma (GBM). Nevertheless, the corroborating genetic data are restricted to a small patient cohort. This study aimed to validate the presence of low-level oncogenic mutations in the SVZ of GBM patients and assess their clinical implications.. We performed deep hybrid capture sequencing of 15 GBM-associated genes and TERT promoter amplicon sequencing on triple-matched samples from the SVZ, primary tumor, and blood of 60 GBM patients. Approximately 62% of patients (40 of 61 patients) showed shared oncogenic mutations between the tumor and tumor-free SVZ, including TERT promoter, PTEN, and TP53. While shared mutations did not affect overall clinical profiles, TERT promoter mutations were significantly enriched in the shared group (94.9% of patients, p ≤ 0.001). RNA sequencing revealed upregulation of proliferation-related genes in tumors with shared SVZ mutations, and these patients had worse progression-free and overall survival (p = 0.038 and 0.031, respectively). This study provides the largest-scale genetic validation of the SVZ as a potential cellular origin of GBM, highlighting the distinct genetic and clinical features associated with shared oncogenic mutations. These findings warrant further investigation into the role of SVZ mutations in GBM genesis and their potential as therapeutic targets.

In vitro effectiveness of CB469, a MET tyrosine kinase inhibitor in MET-activated cancer cells

Gene alterations in receptor tyrosine kinases can result in oncogenic driver mutation in non-small cell lung cancer (NSCLC) including in genes like EGFR, ALK and MET. MET amplifications and MET exon14 skipping are the primary genetic changes in MET-altered cancers. Acquired MET mutations mediate resistance to clinical MET-targeted therapy in NSCLC. MET kinase domain secondary mutations (D1228X, Y1230X) confer resistance to type I MET tyrosine kinase inhibitors (TKIs) in METexon14-altered or MET amplified NSCLC. Here, we investigated the preclinical activity of a novel MET inhibitor, CB469, with cell growth, signaling pathway and colony formation. We confirmed that CB469 inhibited the activity of MET wild and secondary mutant kinases, D1228N and Y1230H, as a type II inhibitor. CB469 also inhibited cell growth and cell signaling proteins in MET-activated or MET exon14 skipping-mutated cancer cell lines and NIH/3T3 cells expressing an engineered MET mutant. CB469 exhibited the inhibitory efficacy comparable with that of capmatinib in migration of EBC-1(METwt) and Hs746T(METΔex14) cells. Finally, CB469 showed selective and potent inhibition in MET-activated cancer cells among MET TKIs leading to enhanced selectivity for MET-mutant versus wild type MET with inhibition of cell growth in NIH/3T3 cells expressing an engineered MET mutant variant.

RAS-mutant leukaemia stem cells drive clinical resistance to venetoclax.

Cancer driver mutations often show distinct temporal acquisition patterns, but the biological basis for this, if any, remains unknown. RAS mutations occur invariably late in the course of acute myeloid leukaemia, upon progression or relapsed/refractory disease1-6. Here, by using human leukaemogenesis models, we first show that RAS mutations are obligatory late events that need to succeed earlier cooperating mutations. We provide the mechanistic explanation for this in a requirement for mutant RAS to specifically transform committed progenitors of the myelomonocytic lineage (granulocyte-monocyte progenitors) harbouring previously acquired driver mutations, showing that advanced leukaemic clones can originate from a different cell type in the haematopoietic hierarchy than ancestral clones. Furthermore, we demonstrate that RAS-mutant leukaemia stem cells (LSCs) give rise to monocytic disease, as observed frequently in patients with poor responses to treatment with the BCL2 inhibitor venetoclax. We show that this is because RAS-mutant LSCs, in contrast to RAS-wild-type LSCs, have altered BCL2 family gene expression and are resistant to venetoclax, driving clinical resistance and relapse with monocytic features. Our findings demonstrate that a specific genetic driver shapes the non-genetic cellular hierarchy of acute myeloid leukaemia by imposing a specific LSC target cell restriction and critically affects therapeutic outcomes in patients.

Obesity-dependent selection of driver mutations in cancer

Obesity is a risk factor for cancer, but whether obesity is linked to specific genomic subtypes of cancer is unknown. We examined the relationship between obesity and tumor genotype in two clinicogenomic corpora. Obesity was associated with specific driver mutations in lung adenocarcinoma, endometrial carcinoma and cancers of unknown primaries, independent of clinical covariates, demographic factors and genetic ancestry. Obesity is therefore a driver of etiological heterogeneity in some cancers.

Sodium arsenite-induced DNA methylation alterations exacerbated by p53 knockout in MCF7 cells

Epigenetic alterations are ubiquitous across human malignancies. Thus, functional characterization of epigenetic events deregulated by environmental pollutants should enhance our understanding of the mechanisms of carcinogenesis and inform preventive strategies. Recent reports showing the presence of known cancer-driving mutations in normal tissues have sparked debate on the importance of non-mutational stressors potentially acting as cancer promoters. Here, we aimed to test the hypothesis that the presence of mutations in p53, a commonly mutated gene in human malignancies, may influence cellular response to an environmental non-mutagenic agent, potentially involving epigenetic mechanism. We used the CRISPR-Cas9 system to generate knockouts of p53 in MCF7 and T47D breast cancer cell lines and characterized DNA methylome changes by targeted pyrosequencing and methylome-wide Infinium MethylationEPIC BeadChip arrays after exposure to sodium arsenite, a well-established human carcinogen with documented effects on the epigenome. We found that the knockout of p53 alone was associated with extensive alterations in DNA methylation content, with predominant CpG hypermethylation concurrent with global demethylation, as determined by LINE-1 repetitive element pyrosequencing. While exposure to sodium arsenite induced little to no effects in parental cell lines, mutant cells, upon treatment with sodium arsenite, exhibited a markedly altered response in comparison to their wild-type counterparts. We further performed genome regional analyses and found that differentially methylated regions (DMRs) associated with exposure to sodium arsenite map to genes involved in chromatin remodeling and cancer development. Reconstitution of wild-type p53 only partially restored p53-mutant-specific differential methylation states in response to sodium arsenite exposure, which may be due to the insufficient reconstitution of p53 function, or suggestive of a potential exposure-specific epigenetic memory. Together, our results revealed wide-spread epigenetic alterations associated with p53 mutation that influence cellular response to sodium arsenite exposure, which may constate an important epigenetic mechanism by which tumour promoting agents synergize with driver mutations in cancer promotion.

Usefulness of multigene liquid biopsy of bile for identifying driver genes of biliary duct cancers.

Liquid biopsy (LB) is an essential tool for obtaining tumor-derived materials with minimum invasion. Bile has been shown to contain much higher free nucleic acid levels than blood plasma and can be collected through endoscopic procedures. Therefore, bile possesses high potential as a source of tumor derived cell-free DNA (cfDNA) for bile duct cancers. In this study, we show that a multigene panel for plasma LB can also be applied to bile cfDNA for comparing driver gene mutation detection in other sources (plasma and tumor tissues of the corresponding patients). We collected cfDNA samples from the bile of 24 biliary tract cancer cases. These included 17 cholangiocarcinomas, three ampullary carcinoma, two pancreatic cancers, one intraductal papillary mucinous carcinoma, and one insulinoma. Seventeen plasma samples were obtained from the corresponding patients before surgical resection and subjected to the LiquidPlex multigene panel LB system. We applied a machine learning approach to classify possible tumor-derived variants among the prefiltered variant calls by a LiquidPlex analytical package with high fidelity. Among the 17 cholangiocarcinomas, we could detect cancer driver mutations in the bile of 10 cases using the LiquidPlex system. Of the biliary tract cancer cases examined with this method, 13 (54%) and 4 (17%) resulted in positive cancer driver mutation detection in the bile and plasma cfDNAs, respectively. These results suggest that bile is a more reliable source for LB than plasma for multigene panel analyses of biliary tract cancers.

Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations

Elucidating the molecular dependencies behind the cancer-type specificity of driver mutations may reveal new therapeutic opportunities. We hypothesized that developmental programs would impact the transduction of oncogenic signaling activated by a driver mutation and shape its cancer-type specificity. Therefore, we designed a computational analysis framework by combining single-cell gene expression profiles during fetal organ development, latent factor discovery, and information theory-based differential network analysis to systematically identify transcription factors that selectively respond to driver mutations under the influence of organ-specific developmental programs. After applying this approach to VHL mutations, which are highly specific to clear cell renal cell carcinoma (ccRCC), we revealed important regulators downstream of VHL mutations in ccRCC and used their activities to cluster patients with ccRCC into three subtypes. This classification revealed a more significant difference in prognosis than the previous mRNA profile-based method and was validated in an independent cohort. Moreover, we found that EP300, a key epigenetic factor maintaining the regulatory network of the subtype with the worst prognosis, can be targeted by a small inhibitor, suggesting a potential treatment option for a subset of patients with ccRCC. This work demonstrated an intimate relationship between organ development and oncogenesis from the perspective of systems biology, and the method can be generalized to study the influence of other biological processes on cancer driver mutations.

EP.02A.01 Gender-Specific Onset Age Distribution Among Different Driver Mutations in Lung Cancer

EP.02A.01 Gender-Specific Onset Age Distribution Among Different Driver Mutations in Lung Cancer

Machine learning optimized DriverDetect software for high precision prediction of deleterious mutations in human cancers.

The detection of cancer-driving mutations is important for understanding cancer pathology and therapeutics development. Prediction tools have been created to streamline the computation process. However, most tools available have heterogeneous sensitivity or specificity. We built a machine learning-derived algorithm, DriverDetect that combines the outputs of seven pre-existing tools to improve the prediction of candidate driver cancer mutations. The algorithm was trained with cancer gene-specific mutation datasets of cancer patients to identify cancer drivers. DriverDetect performed better than the individual tools or their combinations in the validation test. It has the potential to incorporate future novel prediction algorithms and can be retrained with new datasets, offering an expanded application to pan-cancer analysis for cross-cancer study. (115 words).

Functional profiling of serine, threonine and tyrosine sites.

Systematic perturbation of amino acids at endogenous loci provides diverse insights into protein function. Here, we performed a genome-wide screen to globally assess the cell fitness dependency of serine, threonine and tyrosine residues. Using an adenine base editor, we designed a whole-genome library comprising 817,089 single guide RNAs to perturb 584,337 S, T and Y sites. We identified 3,467 functional substitutions affecting cell fitness and 677 of them involving phosphorylation, including numerous phosphorylation-mediated gain-of-function substitutions that regulate phosphorylation levels of itself or downstream factors. Furthermore, our findings highlight that specific substitution types, notably serine to proline, are crucial for maintaining domain structure broadly. Lastly, we demonstrate that 309 enriched hits capable of initiating cell overproliferation might be potential cancer driver mutations. This study represents an extensive functional profiling of S, T and Y residues and provides insights into the distinctive roles of these amino acids in biological mechanisms and tumor progression.

Abstract C171: Identifying cancer driver mutation signatures in lung adenocarcinoma from Black/African American individuals: Addressing cancer health disparities

Abstract Lung cancer remains the leading cause of cancer-related mortality globally and continues to contribute significantly to cancer health disparities. Black/African American (B/AA) men exhibit a higher risk of lung cancer compared to White men; B/AA individuals also exhibit lower 5-year survival and stage-specific survival rates than White subjects. Biological factors, including genetic differences in cancer driver mutation, may influence this disparity. Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer across all ethnic groups, including B/AA individuals. Our study aims to characterize the main driver and co-mutation signatures of LUAD in B/AA individuals, who are significantly underrepresented in current mutational studies. We hypothesize that B/AA individuals will have a unique repertoire of cancer driver genes, which could contribute to genetic differences and response to targeted therapies compared to LUAD of White subjects. We are obtaining 100 de-identified archival formalin-fixed, paraffin-embedded (FFPE) LUAD samples from B/AA subjects from cancer registries in Florida and California. Extraction of DNA from the FFPE samples is in progress, and samples have been sent for whole exome sequencing (WES) and ancestry determination. This data will then be analyzed and compared with known LUAD mutation profiles from other ethnicities. Identification of cancer driver mutations will then inform the development of in vitro models for therapeutic testing. To date, the limited information on cancer driver genes in LUAD from B/AA subjects suggests that KRAS is the most common cancer driver gene, just like in LUAD from White subjects, and is found in ∼34% of cases. Therefore, we anticipate identifying KRAS mutations similar to this proportion based on the collection of previously published literature analyses. One key goal of this study is to obtain more information about the exact spectrum of KRAS mutations in LUAD from B/AA subjects. In addition, our work may unveil new variants of known cancer driver mutations such as KRAS, EGFR, BRAF, etc., and finally, “new” driver genes. Our efforts will address critical gaps in the understanding of lung cancer driver genes, a key step to developing personalized treatment of lung cancer and mitigating cancer health disparities between B/AA and White individuals. Supported by grants U54CA233396, U54CA233444, and U54CA233465 from the National Institutes of Health (NIH)/National Cancer Institute (NCI), the Norris Comprehensive Cancer Center core grant, award number P30CA014089 from the NIH/NCI, and by the Undergraduate Research Associates Program supported by the USC Provost. Citation Format: Davin Pan, Daniel J. Mullen, Colton Stensrud, Jose Aparicio, Christina M. Gobin, Sofia Lugo, Kweku Ofosu-Asante, Justin K. Mensah-Mamfo, Kyle R Phillips, Yong Huang, Nazarius S. Lamango, William D Wallace, Suhn K Rhie, Kristinanna M. Fredenburg, Ite A. Offringa. Identifying cancer driver mutation signatures in lung adenocarcinoma from Black/African American individuals: Addressing cancer health disparities [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C171.

Pervasive Induction of Regulatory Mutation Microclones in Sun-exposed Skin.

Carcinogen-induced mutations are thought near-random, with rare cancer-driver mutations underlying clonal expansion. Using high-fidelity Duplex Sequencing to reach a mutation frequency sensitivity of 4×10 -9 per nt, we report that sun exposure creates pervasive mutations at sites with ∼100-fold UV-sensitivity in RNA-processing gene promoters - cyclobutane pyrimidine dimer (CPD) hyperhotspots - and these mutations have a mini-driver clonal expansion phenotype. Numerically, human skin harbored 10-fold more genuine mutations than previously reported, with neonatal skin containing 90,000 per cell; UV signature mutations increased 8,000-fold in sun-exposed skin, averaging 3×10 -5 per nt. Clonal expansion by neutral drift or passenger formation was nil. Tumor suppressor gene hotspots reached variant allele frequency 0.1-10% via 30-3,000 fold clonal expansion, in occasional biopsies. CPD hyperhotspots reached those frequencies in every biopsy, with modest clonal expansion. In vitro, tumor hotspot mutations arose occasionally over weeks of chronic low-dose exposure, whereas CPD hyperhotspot mutations arose in days at 1000-fold higher frequencies, growing exponentially. UV targeted mini-drivers in every skin cell.

Characterization of driver mutations identifies gene signatures predictive of prognosis and treatment sensitivity in multiple myeloma.

In multiple myeloma (MM), while frequent mutations in driver genes are crucial for disease progression, they traditionally offer limited insights into patient prognosis. This study aims to enhance prognostic understanding in MM by analyzing pathway dysregulations in key cancer driver genes, thereby identifying actionable gene signatures. We conducted a detailed quantification of mutations and pathway dysregulations in 10 frequently mutated cancer driver genes in MM to characterize their comprehensive mutational impacts on the whole transcriptome. This was followed by a systematic survival analysis to identify significant gene signatures with enhanced prognostic value. Our systematic analysis highlighted 2 significant signatures, TP53 and LRP1B, which notably outperformed mere mutation status in prognostic predictions. These gene signatures remained prognostically valuable even when accounting for clinical factors, including cytogenetic abnormalities, the International Staging System (ISS), and its revised version (R-ISS). The LRP1B signature effectively distinguished high-risk patients within low/intermediate-risk categories and correlated with significant changes in the tumor immune microenvironment. Additionally, the LRP1B signature showed a strong association with proteasome inhibitor pathways, notably predicting patient responses to bortezomib and the progression from monoclonal gammopathy of unknown significance to MM. Through a rigorous analysis, this study underscores the potential of specific gene signatures in revolutionizing the prognostic landscape of MM, providing novel clinical insights that could influence future translational oncology research.

Whole-Exome Sequencing Reveals Novel Candidate Driver Mutations and Potential Druggable Mutations in Patients with High-Risk Neuroblastoma.

Neuroblastoma is the most prevalent solid tumor in early childhood, with a 5-year overall survival rate of 40-60% in high-risk cases. Therefore, the identification of novel biomarkers for the diagnosis, prognosis, and therapy of neuroblastoma is crucial for improving the clinical outcomes of these patients. In this study, we conducted the whole-exome sequencing of 48 freshly frozen tumor samples obtained from the Biobank. Somatic variants were identified and selected using a bioinformatics analysis pipeline. The mutational signatures were determined using the Mutalisk online tool. Cancer driver genes and druggable mutations were predicted using the Cancer Genome Interpreter. The most common mutational signature was single base substitution 5. MUC4, MUC16, and FLG were identified as the most frequently mutated genes. Using the Cancer Genome Interpreter, we identified five recurrent cancer driver mutations spanning MUC16, MUC4, ALK, and CTNND1, with the latter being novel and containing a missense mutation, R439C. We also identified 11 putative actionable mutations including NF1 Q1798*, Q2616*, and S636X, ALK F1174L and R1275Q, SETD2 P10L and Q1829E, BRCA1 R612S, NOTCH1 D1670V, ATR S1372L, and FGFR1 N577K. Our findings provide a comprehensive overview of the novel information relevant to the underlying molecular pathogenesis and therapeutic targets of neuroblastoma.

Half of oncologists fail to use ordered NGS results to guide their first-line treatment decision in advanced NSCLC: A retrospective study in a community-based integrated healthcare system

PurposeNext generation sequencing (NGS) testing is used to identify driver mutation(s) in non-small cell lung cancer (NSCLC) that are amenable to targeted therapy, resulting in superior outcomes and improved tolerability. We characterized how clinicians in a large integrated healthcare system utilized NGS testing to inform first line treatment decisions in patients with stage IV NSCLC shortly after diagnosis. MethodsWe conducted a cross-sectional study of 964 patients within an integrated healthcare system, Kaiser Permanente Southern California (KPSC), who were diagnosed with stage IV NSCLC and completed NGS testing (Strata Oncology) between May 2019 to June 2021. Treatment start dates were used to divide patients into those who started treatment before or after NGS results, or those who did not receive treatment after NGS results. Patients harboring alterations in seven genes (EGFR, ALK, ROS-1, BRAF, KRAS, RET, and MET) were considered candidates for targeted first line therapy. ResultsFirst line treatment was initiated in half (52 %; n = 284) of all treated patients prior to NGS results. Just under half (48 %; n = 137) of these patients were found to have a targetable mutation by NGS, of whom 59 % received first line chemotherapy and/or immunotherapy, rather than targeted therapy. Nearly 27 % of the sample never received treatment, of which 31 % had a targetable mutation, and may have been candidates for targeted therapy. Not undergoing first line treatment was correlated with older age, higher comorbidity index, smoking history, and the lack of an identifiable driver mutation. ConclusionNGS tests results were not exclusively used to inform first line treatment decisions in most patients with stage IV NSCLC, and most patients with a targetable mutation were not treated with targeted therapy. Possible explanations include lengthy turnaround times for NGS testing and the availability of timelier but less accurate single gene testing.

Personalized therapy in oncology: melanoma as a paradigm for molecular-targeted treatment approaches.

In recent decades, the field of systemic cancer treatment has seen remarkable changes due to advancements in the understanding of cancer's biology, immunology, and genetic makeup. As a result, individuals with late-stage cancers are now achieving survival rates that were previously unattainable. The goal of personalized cancer therapy is to enhance clinical outcomes by customizing drug treatments to suit the unique genetic and/or epigenetic profiles of each patient's tumor. This approach aims to reduce the side effects commonly associated with ineffective treatments. Advances in genetic sequencing and molecular cytogenetics have been instrumental in identifying cancer-driving mutations and epigenetic irregularities, leading to the development of specific molecular therapies. This review article highlights the progress and success of targeted molecular therapies in treating malignant melanoma, illustrating the concept of personalized cancer treatment.

Bioinformatics tools and resources for cancer and application.

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Next-generation sequencing technology in cancer

Next-generation sequencing (NGS) technology has revolutionized cancer research and treatment by enabling comprehensive analysis of genetic mutations, alterations, and expression profiles. It allows for the identification of cancer-driving mutations, helping in the development of targeted therapies. NGS provides detailed insights into tumor heterogeneity, resistance mechanisms, and clonal evolution. Its high-throughput capacity facilitates large-scale studies, improving our understanding of cancer genomics. By enabling personalized treatment plans based on individual genetic profiles, NGS holds promise for more effective and tailored cancer therapies. Early reviews on cancer genomics often lacked comprehensive coverage of emerging technologies. They missed in-depth analysis of NGS advancements, their impact on cancer research, and clinical applications. The review addresses this gap by reviving a thorough examination of NGS methods, their role in identifying genetic mutations, and their potential in personalized cancer treatment, thus providing essential insights into the evolving landscape of cancer genomics. The article covers the advancements in technology and bioinformatic approaches for NGS data analysis. It delves into NGS applications in research and diagnostics, particularly for solid cancer diagnosis. The review highlights specific cancer types, including hereditary breast cancer, melanoma, prostate cancer, thyroid cancer, lung cancer, and colorectal cancer. It explores NGS contribution in understanding the genetic basis of these cancers and its potential for enhancing personalized diagnosis and treatment strategies. This review rectifies early lacunas by providing a comprehensive and updated examination of NGS technology, addressing gaps in previous analyses and emphasizes bioinformatic approaches for NGS data analysis, crucial for interpreting vast genomic data accurately. The review meets the current need for a thorough understanding of NGS’s role in personalized cancer treatment and research.

Pathogenesis of Endometriosis and Endometriosis-Associated Cancers.

Endometriosis is a hormone-dependent, chronic inflammatory condition that affects 5-10% of reproductive-aged women. It is a complex disorder characterized by the growth of endometrial-like tissue outside the uterus, which can cause chronic pelvic pain and infertility. Despite its prevalence, the underlying molecular mechanisms of this disease remain poorly understood. Current treatment options are limited and focus mainly on suppressing lesion activity rather than eliminating it entirely. Although endometriosis is generally considered a benign condition, substantial evidence suggests that it increases the risk of developing specific subtypes of ovarian cancer. The discovery of cancer driver mutations in endometriotic lesions indicates that endometriosis may share molecular pathways with cancer. Moreover, the application of single-cell and spatial genomics, along with the development of organoid models, has started to illuminate the molecular mechanisms underlying disease etiology. This review aims to summarize the key genetic mutations and alterations that drive the development and progression of endometriosis to malignancy. We also review the significant recent advances in the understanding of the molecular basis of the disorder, as well as novel approaches and in vitro models that offer new avenues for improving our understanding of disease pathology and for developing new targeted therapies.

Efficacy of immunotherapy in RET fusion-positive NSCLC: A meta-analysis

BackgroundThe Rearranged during Transfection (RET) gene represents a rare driver mutation in non-small cell lung cancer (NSCLC) occurring in only 1 %–2 % of cases, with implications in targeted carcinogenesis. Despite the significant efficacy demonstrated by immunotherapy in advanced NSCLC with wild-type driver genes, its validation in RET fusion-positive patients is yet to be established. ObjectivesThis meta-analysis aims to systematically evaluate the effectiveness of immunotherapy in patients with RET fusion-positive NSCLC. Data sourcesand Methods: PubMed and Web of Science databases were systematically searched for relevant studies. Outcomes including objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were extracted for further analysis. ResultsTen real-world evidence (RWE) studies involving 7145 patients were enrolled in this meta-analysis. In terms of tumor response, the pooled ORR and DCR were 24.0 % and 61.0 %, respectively. Regarding survival analysis, the pooled median PFS and median OS were 4.17 months [95 % confidence interval (CI): 3.40–5.02) and 17.22 months (95 % CI: 11.58–23.91)], respectively. Subgroup analyses showed that immunotherapies plus chemotherapy were superior to single-immunotherapy in terms of ORR, DCR, and median PFS, which were 43 % (95 % CI: 31%–55 %) vs. 17 % (95 % CI: 11%–25 %), 74 % (95 % CI: 60%–84 %) vs. 45 % (95 % CI: 31%–59 %) and 6.69 months (95 % CI: 4.91–8.93) vs. 2.96 months (95 % CI: 2.25–3.78), respectively. ConclusionsTo date, RET fusions appear to be associated with poor response to immunotherapy in NSCLC patients, and immunotherapy combined with chemotherapy seems to offer greater clinical benefits than mono-immunotherapy.