Comprehensive molecular profiling of lung adenocarcinoma

Abstract: Lung adenocarcinoma, a major cause of cancer-related deaths globally, was examined through a comprehensive analysis of 230 resected tumors. This study integrated various sequencing techniques to profile messenger RNA, microRNA, and DNA, along with evaluating copy number variations, methylation patterns, and proteomic data. The findings revealed a notable rate of somatic mutations (average of 8.9 mutations per megabase). Among the 18 significantly mutated genes were RIT1 activating mutations and newly identified MGA loss-of-function mutations, which were mutually exclusive with MYC amplification. Gender-based differences were observed, with EGFR mutations being more common in females and RBM10 mutations in males. Genetic abnormalities in NF1, MET, ERBB2, and RIT1 were detected in 13% of cases, often in tumors lacking other activated oncogenes, suggesting their potential driver roles. Splicing alterations were driven by somatic genomic changes, as evidenced by DNA and mRNA sequencing from the same tumor, including MET mRNA exon 14 skipping in 4% of cases. While MAPK and PI(3)K pathway activity was explained by known mutations in some cases, unexplained mechanisms appeared to activate the pathways in others. These findings lay the groundwork for understanding lung adenocarcinoma’s molecular basis and offer insights for classification and further investigations. Molecular profiling is crucial for identifying actionable mutations, guiding treatment choices in advanced adenocarcinoma and acquired resistance to tyrosine kinase inhibitors. Circulating tumor DNA sequencing gains importance in NSCLC diagnostics due to its accessibility, allowing longitudinal disease monitoring. Notably, the overall cancer death rate dropped by 27% between 1991 and 2016, resulting in around 2,629,200 fewer expected cancer deaths compared to peak death rates.

Investigation of RBM10 mutation and its associations with clinical and molecular characteristics in EGFR-mutant and EGFR-wildtype lung adenocarcinoma

Tobacco smoke produces both mutagenic and physiological effects, altering the mutation rate of cells and the selection acting on them in the damaged lung environment, and facilitating its role in driving cancer progression. In addition to these gene-by-environment interactions, gene-by-gene epistatic interactions also shape the adaptive landscape, influencing the evolutionary trajectories of cancer. Understanding the influence of tobacco smoke on the epistatic trajectories of lung cancer progression would help guide the development of targeted therapies that are more effective for smoker or never-smoker populations. To address this need, we constructed a continuous-time Markov chain model for the evolutionary trajectories of lung adenocarcinoma (LUAD), the most common subtype of lung cancer and the most frequent subtype among never-smokers. Using thousands of tumor sample sequences aggregated across studies, we profiled the trajectories of LUAD in smokers and never-smokers and estimated the rates at which mutations are gained from each possible set of pre-existing mutations, or genetic states. We then accounted for differences in baseline mutation rates to quantify the selective benefit of mutations. We find that epistasis is prevalent in LUAD, with several strong synergistic interactions—such as between RB1 and EGFR mutations- and antagonistic interactions-such as between EGFR and KEAP1 or KRAS mutations. Additionally, we identify non-additive epistatic effects: STK11 mutations are synergistic with KEAP1 and KRAS mutations but do not experience additional selection when both are mutated. In contrast, GNAS mutations are not synergistic with KEAP1 or RBM10 mutations alone but are synergistic with their co-mutation. Smoking has a large influence on the adaptive landscape, with several common mutations being preferentially selected in never-smoker cancers, including EGFR, SMAD4, GNAS, and PIK3CA mutations. KEAP1, STK11, and KRAS mutations are preferentially selected in smoker cancers. Smoking’s physiological influence also affects the strength of certain epistatic interactions, such as between STK11 and KEAP1 mutations. Overall, we find that smoking not only increases the mutation rate of lung cells but also substantially alters the adaptive landscape of lung adenocarcinoma, leading to clinically relevant differences in selection on mutations between smoker and never-smoker cancers. We additionally detect frequent pairwise and higher-order epistatic effects in LUAD that may inform the personalized application of targeted therapies. Citation Format: Krishna Dasari, Jorge Alfaro-Murillo, Jeffrey Townsend. Tobacco smoke alters the adaptive landscape of lung adenocarcinoma and influences the strength of epistatic interactions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1251.

Background RBM10 is frequently mutated in lung adenocarcinoma (LUAD). Several studies identified RBM10 could regulate proliferation and apoptosis, but how can RBM10 mutations affect tumor microenvironment (TME) is elusive. We aimed to explore the effect of RBM10 mutations on TME. Methods Whole-exome sequencing (WES) was performed on 39 treatment-naïve early-stage LUADs presenting as ground-glass nodules (GGN). Data from TCGA database (n=562) and WES and RNA-sequencing (RNA-seq) data of another Chinese LUAD cohort (n=128, CHOICE_ADC cohort) were obtained. GSEA was performed to determine immune related pathways. Single-sample GSEA (ssGSEA), CIBERSORT and TIMER were used to evaluate immune infiltration. TIDE was used to calculate the predictive immunotherapy response. Results RBM10 mutational frequency in TCGA and CHOICE_ADC cohort were 7% and 8%, but reached 28% in GGN cohort. Because there were more early-stage LUADs in our cohort, RBM10 more likely mutated in early-stage LUAD. Additionally, majority of RBM10 mutations were protein-truncating variants, including nonsense and frameshift mutation. Survival analysis revealed RBM10 deficiency was related to shorter overall survival. GSEA was performed using RNA-seq data from TCGA and CHIOCE_ADC cohort and revealed immune related pathways were enriched in RBM10 deficient population. In TCGA cohort, the inflammatory response and TGF-β signaling were two of the representative enriched pathways. Similarly, the interferon-γ response and TNF-α signaling via NF-κB were two of the most enriched pathways in CHOICE_ADC cohort. The number of neoantigen and tumor mutation burden were higher in patients with RBM10 mutations. We further compared HLA expression between patients with RBM 10 mutations and wild-type population and found numerous HLAs showed higher expression in RBM10 deficient population, such as HLA.DRB6, HLA.DRB5 and HLA.DQA1. By using ssGSEA, we found diverse immune signatures (Th1 cells, macrophages, DC and CD8+T cells) showed higher enrichment levels in population with low RBM10 expression in both TCGA and CHOICE_ADC cohort. Similarly, RBM10 expression had a positive correlation with the levels of myeloid dendritic cell, macrophage, neutrophil, CD8+T cell and CD4+T cell according to the results of TIMMER and CIBERSORT. Finally, we found PD-L1 and TIM3 exhibited higher expression in population with RBM10 deficiency. Additionally, the predicted immunotherapy response was calculated through TIDE algorithm. Expression of IFNG was upregulated and immune evasion level was lower in population with RBM10 deficiency. Conclusion RBM10 mutations were more common in early-stage LUADs. Immune activity in patients with RBM10 mutations was elevated and there were more neoantigens in these patients. Our results demonstrated that LUAD patients with RBM10 mutations could more likely benefit from immunotherapy. Citation Format: Bing Liu, Yang Chen, Nan Wu. RBM10 mutations remodel tumor microenvironment of lung adenocarcinoma and contribute to its progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2822.

e20544 Background: According to WHO, lung cancer is the leading cause of cancer-related death worldwide, but treatment has advanced in the last decade. The widespread use of Next Generation Sequencing has led to the discovery of several pathogenic mutations including RNA binding motif 10 [RBM10], a part of the spliceosome complex that regulates splicing of pre-mRNA [Pan Q, Nat Genet. 2008]. The knock down of RBM10 increases the growth of mouse tumor xenografts [Hernández J, RNA Biol. 2016]. Mutated RBM10increased spliceosome inhibition in EGFR mutated lung cancer cells thereby contributing to EGFR TKI resistance [Bao Y, Cancer Res. 2023]. Methods: Electronic medical records were utilized to create a database of patients [50 patients] seen from 2018-2023 with NSCLC and RBM10 mutations, with appropriate IRB approval. For sub-group analysis, we separated into groups by rapid progression vs stable disease defined as progression free survival earlier than respective clinical trials. Fisher’s exact tests were used to assess the association between mutation and clinical outcomes. Results: From analysis of treatment response, 71% [20 patients out of 28] of the patients with complete treatment data had rapid progression of disease. In our patient dataset, 20 out of the 50 RBM10 mutated patients had EGFR mutations while 18 had KRAS mutations. RBM10 mutations did not seem to correlate with alterations in MSI stability as all patients had MSI stable disease and there was no relationship between the tumor mutation burden and the clinical response in the RBM10 mutated patients (odds ratio (OR) = 1.33, 95% CI 0.24-7.35, p = 0.741). In comparing the mutated RBM10 population to wild type RBM10 population, controlled for driver mutations, median PFS was 6.7 (95% CI [4.5, 17.]) compared to 13.9 (95% CI [10.4, 24.2]). RBM10 mutations in EGFR mutated patients often developed later in the course of disease, commonly at progression leading to late EGFR TKI resistance. The most common non driver concurrent mutation with RBM10 was TP53, while the most common VUS were SPTA1 and ZFHX3. TP53 mutation had a higher representation in the RBM10 mutated rapid progression group, OR (odds ratio) 8.081, 95% CI [0.773, 431/717], P-value = 0. 00838). The ZFHX3 mutation had a higher representation in the RBM10 mutated stable disease group OR 0.0430, 95% CI [0.0007, 0.5506]. Conclusions: From this single institution investigation, RBM10 mutations were associated with aggressive disease with treatment progression faster than median durations of response. RBM10 mutations with concurrent ZFHX3 and EGFR mutations were associated with more stable disease, while concurrent KRAS and TP53 predicted even more aggressive disease. However, once the RBM10 mutation developed in the EGFR population, rapid progression was observed, indicating a mechanism of late resistance. More investigation is warranted into RBM10 to further certify its use as a biomarker.

<b>Introduction:</b> genetic alterations have implications for prognosis/treatment are frequently detected in pulmonary adenocarcinomas (PA). Molecular testing is performed in patients with locally advanced or metastatic disease but not in patients undergoing curative surgery, so this could be a bias of selection when considering the prevalence of such changes <b>Objective:</b> to describe the prevalence of molecular changes in patients with surgically resected PA and compare it with advanced disease patients <b>Methods:</b> we selected patients with PA diagnosed between 2009-15, who underwent genomic testing for <i>EGFR</i>, <i>KRAS</i> and <i>BRAS</i> mutations, <i>ALK</i> rearrangements, <i>MET</i> amplification and <i>RET</i> fusions. Patients were classified in: a. inoperable PA; and b. candidates for resection <b>Results:</b> 625 patients with PA were identified and 253 (40.5%) had at least one molecular change. We did not found differences in the prevalence of molecular changes between both groups (41.3% group a–37.9% in group b; p=0.40). The prevalence of the molecular changes is shown in <b>Conclusions:</b> patients undergoing curative surgery for PA had similar genomic changes when compared with inoperable PA. The prevalence of <i>KRAS-</i><i>EGFR</i> mutation is similar to what is found in literature, but our prevalence of <i>MET</i> amplification is particularly higher than that reported for other populations (Cardarella et al.AJRCCM 2013 &lt;1%). Moreover, this is the third most frequent alteration in our patients undergoing surgery.

RBM10 is the RNA-binding protein often absent or mutated in lung adenocarcinoma, rendering it as a potential biomarker or even therapeutic target to prolongate survival time. In this study, we investigated the involvement of RBM10 mutation in the pathogenesis and tumorigenesis of lung adenocarcinoma and identified the differentials in relative signal pathways, aiming to provide the new therapeutic approaches. By performing the systematic TCGA analysis, our results demonstrated that RBM10 mutation was identified in 6% lung adenocarcinoma patients, meanwhile 113 functional genes were identified as significant expression among these patients. Further gene ontology and KEGG analysis were employed to identify the most relative 10 genes and signal pathways. Moreover, four members of the 5-acyl-6, 7-dihydrothiophene [3, 2-c] pyridine (known as “ru-ski”)-ru-ski 43 were identified as the potential drugs for RBM10 mutation lung adenocarcinoma therapy, investigated by the GDSC database. Meanwhile there were 157 genes that were more frequently mutated in the RBM10 mutation group than the wild-type group (p value<0.05). KEGG analysis showed that these genes were enriched in various cancer development pathways and cell proliferation. Finally, our investigations provided the glance at the differential genes and cellular signaling pathways related to RBM10 mutation and identified series of potential drugs for personalized RBM10 mutation lung adenocarcinoma therapy.

RBM10 is an RNA splicing regulator that is frequently mutated in lung adenocarcinoma (LUAD) and has recently been proposed to be a cancer gene. How RBM10 mutations observed in LUAD affect its normal functions, however, remains largely unknown. Here integrative analysis of RBM10 mutation and RNA expression data revealed that LUAD-associated RBM10 mutations exhibit a mutational spectrum similar to that of tumor suppressor genes. In addition, this analysis showed that RBM10 mutations identified in LUAD patients lacking canonical oncogenes are associated with significantly reduced RBM10 expression. To systematically investigate RBM10 mutations, we developed an experimental pipeline for elucidating their functional effects. Among six representative LUAD-associated RBM10 mutations, one nonsense and one frameshift mutation caused loss-of-function as expected, whereas four missense mutations differentially affected RBM10-mediated splicing. Importantly, changes in proliferation rates of LUAD-derived cells caused by these RBM10 missense mutants correlated with alterations in RNA splicing of RBM10 target genes. Together, our data implies that RBM10 mutations contribute to LUAD pathogenesis, at least in large part, by deregulating splicing. The methods described in this study should be useful for analyzing mutations in additional cancer-associated RNA splicing regulators.

EGFR and KRAS mutations are frequently detected in lung adenocarcinoma (LUAD). Tumor mutational signature (TMS) determination is an approach to identify somatic mutational patterns associated with pathogenic factors. In this study, through the analysis of TMS, the underlying pathogenic factors of LUAD with EGFR and KRAS mutations were traced. This was a retrospective study. TMS of LUAD with KRAS and EGFR mutations from the TCGA, OncoSG, and MSK datasets was determined by two bioinformatics tools, namely the "MutationalPatterns" and "FitMS" packages. Elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) of LUAD clinical specimens was analyzed using capillary electrophoresis. In LUAD with KRAS mutations, TMS analysis indicated that the smoking-related SBS4 signature was enriched. For LUAD with EGFR L858R mutation, the smoking-related SBS4 signature was enriched in the Western population from the TCGA database; however, the smoking-related SBS4 signature was not obvious in Asian LUAD patients. LUAD with EGFR exon19 deletion (19Del) exhibited stronger SBS15 signature, which was related to defective DNA mismatch repair. Capillary electrophoresis analysis showed that an EMAST locus was frequently instable in LUAD with EGFR 19Del. Different from the Western population, Asian LUAD patients with EGFR mutations exhibited the enrichment of SBS1, SBS2, and SBS13 signatures, which were associated with the endogenous mutation process of cytidine deamination. TMS analysis reveals that smoking is associated with LUAD with KRAS mutations. Defective DNA mismatch repair and endogenous cytidine deamination are associated with LUAD with EGFR mutations, especially for the EGFR 19Del. The endogenous mutational process is stronger in Asian LUAD patients than Western LUAD patients.

Patterns of DNA Mutations and ALK Rearrangement in Resected Node Negative Lung Adenocarcinoma

Single-Cell Analysis Reveals Transcriptomic Features of Drug-Tolerant Persisters and Stromal Adaptation in a Patient-Derived EGFR-Mutated Lung Adenocarcinoma Xenograft Model.

Introduction: EGFR mutations holds the major targets for drug in lung adenocarcinoma (LUAD). Despite the tremendous study of EGFR mutant (MT) LUAD, the comprehensive interpretation of the heterogeneous character of LUAD harboring EGFR MT remains a key challenge. Here, we investigated the heterogeneity of EGFR MT LUAD and explored the tumor microenvironment (TME) in EGFR MT LUAD. Method: We performed single-cell RNA sequencing (scRNA-seq) from 135 LUAD patients which consist of normal(n=24), EGFR wild (WT)(n=18), and MT(n=93). Also, we used whole genome sequencing and bulk-RNA sequencing to validate with scRNA-seq results. From 898,648 cells, main cell types were classified. To explore the various characteristics of MT LUAD tumor cells, we used two ways: i) We re-clustered epithelial cells populating the normal, WT, and MT. ii) We re-clustered only MT epithelial cells. In each analysis, we identified the tumor character in the clusters using differential expressed genes analysis, lineage tracing, clinical information, mutation, and trajectory analysis. Also, we extracted each main cell type except epithelial cells, and identified subtypes of main cell types. Finally, we revealed the interaction of cellular components in TME. Results: In the analysis of epithelial cells, we identified characteristics of specific EGFR MT by comparing of EGFR WT and MT tumors in clusters with similar biological features. The cluster represented by alveolar type 2 (AT2) known as initiation of LUAD was populating normal, WT, and MT. In this cluster, MT- and WT-associated pathway shared but differently significant between MT and WT in the pathway analysis. The cluster represented by proliferative is mostly comprised tumor cells and we found significantly increased the expression of MDK, CD24 in the MT of the cluster. In the analysis of only MT epithelial cells, 2 of clusters were stage-specific cluster: i) The cluster annotated as early stage cluster, ii) The cluster annotated as advanced stage cluster. Trajectory showed that there is a pseudotemporal continuum, following the stage from early stage cluster to advanced stage cluster. Also, based on the lineage tracing, 2 of clusters revealed lineage-specific clusters: i) The cluster annotated as AT2 was enriched from early stage cells, ii) The cluster annotated as basal cell known as origin of lung squamous cell carcinoma(LUSC) was enriched from advanced stage cells. Psedotemporal ordering of these cluster revealed AT2 cluster transdifferentiate into basal cell cluster which implied the possibility of LUAD to LUSC transition by drug resistance. In the interaction of MT and WT TME, the number of signaling received epithelial cells from myeloid cells, endothelial cells, and fibroblasts as sender increased compared with the interaction of normal. Conclusion: We shed light on the ecosystem of TME according to clinical and biological feature of tumor in EGFR mutant LUAD. Citation Format: You Won Lee, Eun Ji Lee, Seung Yeon Oh, Kyoung-Ho Pyo, Seong Gu Heo, YoungJoon Park, Su-Jin Choi, Kyumin Lim, Ju-hyeon Lee, Jae Hwan Kim, Jii Bum Lee, Ji Yoon Lee, Sun Min Lim, Chang Gon Kim, Min Hee Hong, Mi Ran Yun, Byoung Chul Cho. Phenotype profiling of tumor microenvironment in EGFR mutant lung adenocarcinoma with multi-omics data. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5935.

Lung adenocarcinoma (LUAD) is one of the major histopathological types of non-small cell lung cancer (NSCLC), including solid, acinar, lepidic, papillary and micropapillary subtypes. Increasing evidence has shown that micropapillary LUAD is positively associated with a higher percentage of driver gene mutations, a higher incidence of metastasis and a poorer prognosis, while lepidic LUAD has a relatively better prognosis. However, the novel genetic change and its underlying mechanism in the progression of micropapillary LUAD have not been exactly determined. A total of 181 patients with LUAD who underwent surgery at the First Affiliated Hospital of Huzhou University from January 2020 to December 2022 were enrolled. Three predominant lepidic and three predominant micropapillary LUAD tissue samples were carried out using whole-exome sequencing. Comprehensive analysis of genomic variations and the difference between lepidic and micropapillary LUAD was performed. In addition, the TMEM229A Q200del mutation was verified using our cohort and TCGA-LUAD datasets. The correlations between the TMEM229A Q200del mutation and the clinicopathological characteristics of patients with LUAD were further analyzed. The functions and mechanisms of TMEM229A Q200del on NSCLC cell proliferation and migration were also determined. The frequency of genomic changes in patients with micropapillary LUAD was higher than that in patients with lepidic LUAD. Mutations in EGFR, ATXN2, C14orf180, MUC12, NOTCH1, and PKD1L2 were concomitantly detected in three predominant micropapillary and three predominant lepidic LUAD cases. The TMEM229A Q200del mutation was only mutated in lepidic LUAD. Additionally, the TMEM229A Q200del mutation had occurred in 16 (8.8%) patients, and not found TMEM229A R76H and M346T mutations in our cohort, while TMEM229A mutations (R76H, M346T, and Q200del) occurred only in 1.0% of the TCGA-LUAD cohort. Further correlation analysis between the TMEM229A Q200del mutation and clinicopathological characteristics suggested that a lower frequency of the Q200del mutation was significantly associated with positive lymph node metastasis, advanced TNM stage, positive cancer thrombus, and pathological features. Finally, overexpression of TMEM229A Q200del suppressed NSCLC cell proliferation and migration invitro. Mechanistically, overexpression of TMEM229A and TMEM229A Q200del both reduced the expression level of phosphorylated (p)-ERK and p-AKT (Ser473), and the reduced protein level of p-ERK in the TMEM229A Q200del group was more pronounced compared to the TMEM229A group. Our results demonstrated that the TMEM229A Q200del mutant may play a protective role in the progression of LUAD via inactivating ERK pathway, providing a potential therapeutic target in LUAD.

Cancer is the second leading cause of death worldwide, accounting for an estimated 9.96 million deaths in 2020 [1]. The global cancer burden is dominated by China, which has the largest population size worldwide [2, 3]. Cancer is a group of genetic diseases driven by a series of structural genomic changes [4]. Therefore, extensive analysis of somatic changes in cancer genomes can help us develop treatments that target changes in genomic drivers, thereby improving the life expectancy of cancer patients [5]. At present, a small number of cancer type-specific genomic targets are used as molecular biomarkers to guide the treatment of this particular cancer type in clinical practice [6, 7]. With the arrival of precision medicine era, a variety of biomarkers based on somatic genomic changes have been developed. Based on these new biomarkers, cancer patients are divided into more and more subgroups. In other words, these somatic genomic changes are present in increasingly smaller patient subgroups. Moreover, the list of indications for tumor agnostic treatment is expected to expand rapidly because some anti-cancer drugs have been found to be active in tumor-agnostic manner [8]. Therefore, treatment guidance strategies that group patients into specific tumor subtypes may limit their treatment opportunities, and it may be difficult for patients to benefit from new developments in precision medicine. Comprehensive genomic profiling techniques such as whole-genome sequencing, whole-exome sequencing and large panel sequencing, could solve the issue mentioned above [9, 10] because they can help clinicians to identify a full set of actionable genomic changes for each metastatic cancer patient. Additionally, systematic collection of a full actionable genomic alteration data set from cancer patients can be used to better understand the genomic-related molecular mechanisms of drug resistance and monitor the treatment response. All of these have greatly promoted the development of precision medicine. However, if comprehensive genomic analysis is widely implemented in clinical practice, we could pay a high price for it as we still don't know how often this procedure should be repeated. By analyzing the metastatic cancer genomes, some studies found that individual metastasis is dominated by a single clone with characteristic clone-driven mutations, therefore, the heterogeneity is much lower than that of the primary tumor [11]. This is consistent with the clinical observation that the driver gene heterogeneity between untreated metastases is very small [12], indicating that a single biopsy at diagnosis could be sufficient to guide first-line treatment option. Unfortunately, systemic therapy can stimulate tumor evolution by promoting genetic diversification [13, 14]. In a study recently published in Nature Medicine, titled “Limited evolution of the actionable metastatic cancer genome under therapeutic pressure”, Prof. Joris van de Haar and colleagues analyzed the whole-genome sequencing data of metastatic cancer patients to explore how the actionable cancer genome evolves over the therapeutic course [15]. A total of 250 biopsy pairs longitudinally obtained from 231 patients with metastatic solid tumors over the treatment course were analyzed. Most of the enrolled patients received multiple lines of standard-of-care treatment. The authors reported that the biomarkers for clinical trial enrollment and standard-of-care treatment were identified in 72% and 23% of biopsies, respectively. Approximately 99% of patients had the same standard-of-care genomic biomarkers in the first and second biopsy. Moreover, 219 clinical trial enrollment biomarkers were identified in the first biopsies. Among them, 205 (94%) biomarkers were recovered in the follow-up biopsies. Second whole-genome sequencing did not identify additional clinical trial enrollment biomarkers in 91% of patients. When the authors considered specific genes targeted by hormonal therapies (22% of cases) or small-molecule inhibitors (21% of cases) over the therapeutic course, they observed more frequent genome evolution. The data from this study indicated that the actionable metastatic cancer genome has not changed much during disease progression. This finding is consistent with a study that analyzed sequencing data from 76 untreated metastases from 20 cancer patients [12]. However, the paired biopsies analyzed in this study were all longitudinally sampled from patients receiving systemic anti-cancer therapy, which provides researchers with more important information. Furthermore, this study showed that whole-genome sequencing could be performed in the early stages of metastatic disease and only a single test was sufficient. If this strategy is finally validated for clinical application, it can overcome most of the difficulties caused by the continuous need to validate and implement new sequencing panels. This study also identified two situations in which a single genome analysis was not sufficient to achieve optimal patient care. The first one was when the patients received hormonal therapies or small molecule inhibitors. These patients usually have on-target genomic evolutions, so repeated genome analysis may be required. Second, single genome analysis was found limited in lung cancer patients who harbored standard-of-care genomic targets and were treated with small molecule inhibitors. It should be noted that these on-target genomic alterations only determine the response to the treatment that induced these alterations but do not alter the standard-of-care or investigational treatment indications for other anti-cancer drugs. However, for cases in which on-target evolution may affect clinical decision-making, repeating genomic analysis is necessary. This study had several limitations. First, the median biopsy interval was short (6.4 months), so the findings of this study would not be applicable to cancer patients with long-term survival. Second, this study only analyzed biopsy pairs collected from metastases. Therefore, whether the findings of this study are applicable to the biopsy of the primary tumor still needs further investigations. Third, due to the dataset heterogeneity and the small total numbers of gained/lost biomarkers in this study, the power of subgroup analysis was limited. Last but not least, due to the depth of whole-genome sequencing and the limited sampling range of core needle biopsy, this study had very limited detection capabilities for uncommon sub-clonal mutations. To more comprehensively study the evolution of sub-clonal mutations in the future, we can try to supplement whole-genome sequencing data with the deep sequencing of liquid biopsy. Overall, this study analyzed a large representative group of metastatic cancer patients and demonstrated that the evolution of the actionable genome in treated metastases was limited. Additionally, the first whole-genome sequencing analysis of a metastatic biopsy is sufficient to identify the genomic biomarkers of standard-of-care and the opportunities for investigational treatment. These findings promote the optimization of cancer diagnostic strategies in the precision medicine era. Not applicable. All the authors made contributions to the conception and drafting. All authors read and approved the final manuscript The study was supported by the National Natural Science Foundation of China (81970115 and 32100656). The author declares no competing interests. Not applicable. Not applicable. Not applicable. Not applicable.

P76.33 Concurrent EGFR and KRAS Mutations in Lung Adenocarcinoma: A Single Institution Case Series