Genetic Determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

Effect of EGFR-TKIs combined with craniocerebral radiotherapy on the prognosis of EGFR-mutant lung adenocarcinoma patients with brain metastasis: A propensity-score matched analysis

Background and Purpose

Epidermal growth factor receptor (EGFR)-mutant lung cancers are associated with a high risk of developing brain metastases (BM). Craniocerebral radiotherapy is a cornerstone for the treatment of BM, and EGFR-TKIs act on craniocerebral metastases". However, whether EGFR-TKIs combined with craniocerebral radiotherapy can further increase the efficacy and improve the prognosis of patients is unclear. This study aimed to evaluate the difference in efficacy between targeted-therapy alone and targeted-therapy combined with radiotherapy in EGFR-mutant lung adenocarcinoma patients with BM.

Materials and Methods

A total of 291 patients with advanced non-small cell lung cancer (NSCLC) and EGFR mutations were enrolled in this retrospective cohort study. Propensity score matching (PSM) was conducted using a nearest-neighbor algorithm (1:1) to adjust for demographic and clinical covariates. Patients were divided into two groups: EGFR-TKIs alone and EGFR-TKIs combined with craniocerebral radiotherapy. Intracranial progression-free survival (iPFS) and overall survival (OS) were calculated. Kaplan-Meier analysis was used to compare iPFS and OS between the two groups. Brain radiotherapy included WBRT, local radiotherapy, and WBRT+Boost.

Results

The median age at diagnosis was 54 years (range: 28-81 years). Most patients were female (55.9%) and non-smokers (75.5%). Fifty-one pairs of patients were matched using PSM. The median iPFS for EGFR-TKIs alone (n=37) and EGFR-TKIs+craniocerebral radiotherapy (n=24) was 8.9 and 14.7 months, respectively. The median OS for EGFR-TKIs alone (n=52) and EGFR-TKIs+craniocerebral radiotherapy (n=52) was 32.1 and 45.3 months, respectively.

Conclusion

In EGFR-mutant lung adenocarcinoma patients with BM, targeted therapy combined with craniocerebral radiotherapy is an optimal treatment.

Fully accessible fitness landscape of oncogene-negative lung adenocarcinoma

Cancer genomes are almost invariably complex with genomic alterations cooperating during each step of carcinogenesis. In cancers that lack a single dominant oncogene mutation, cooperation between the inactivation of multiple tumor suppressor genes can drive tumor initiation and growth. Here, we shed light on how the sequential acquisition of genomic alterations generates oncogene-negative lung tumors. We couple tumor barcoding with combinatorial and multiplexed somatic genome editing to characterize the fitness landscapes of three tumor suppressor genes NF1, RASA1, and PTEN, the inactivation of which jointly drives oncogene-negative lung adenocarcinoma initiation and growth. The fitness landscape was surprisingly accessible, with each additional mutation leading to growth advantage. Furthermore, the fitness landscapes remained fully accessible across backgrounds with additional tumor suppressor mutations. These results suggest that while predicting cancer evolution will be challenging, acquiring the multiple alterations required for the growth of oncogene-negative tumors can be facilitated by the lack of constraints on mutational order.

Brain metastatic outgrowth and osimertinib resistance are potentiated by RhoA in EGFR-mutant lung cancer

The brain is a major sanctuary site for metastatic cancer cells that evade systemic therapies. Through pre-clinical pharmacological, biological, and molecular studies, we characterize the functional link between drug resistance and central nervous system (CNS) relapse in Epidermal Growth Factor Receptor- (EGFR-) mutant non-small cell lung cancer, which can progress in the brain when treated with the CNS-penetrant EGFR inhibitor osimertinib. Despite widespread osimertinib distribution in vivo, the brain microvascular tumor microenvironment (TME) is associated with the persistence of malignant cell sub-populations, which are poised to proliferate in the brain as osimertinib-resistant lesions over time. Cellular and molecular features of this poised state are regulated through a Ras homolog family member A (RhoA) and Serum Responsive Factor (SRF) gene expression program. RhoA potentiates the outgrowth of disseminated tumor cells on osimertinib treatment, preferentially in response to extracellular laminin and in the brain. Thus, we identify pre-existing and adaptive features of metastatic and drug-resistant cancer cells, which are enhanced by RhoA/SRF signaling and the brain TME during the evolution of osimertinib-resistant disease.

An in silico comparative transcriptome analysis identifying hub lncRNAs and mRNAs in brain metastatic small cell lung cancer (SCLC)

Small cell lung cancer (SCLC) is a particularly lethal subtype of lung cancer. Metastatic lung tumours lead to most deaths from lung cancer. Predicting and preventing tumour metastasis is crucially essential for patient survivability. Hence, in the current study, we focused on a comprehensive analysis of lung cancer patients' differentially expressed genes (DEGs) on brain metastasis cell lines. DEGs are analysed through KEGG and GO databases for the most critical biological processes and pathways for enriched DEGs. Additionally, we performed protein-protein interaction (PPI), GeneMANIA, and Kaplan-Meier survival analyses on our DEGs. This article focused on mRNA and lncRNA DEGs for LC patients with brain metastasis and underlying molecular mechanisms. The expression data was gathered from the Gene Expression Omnibus database (GSE161968). We demonstrate that 30 distinct genes are up-expressed in brain metastatic SCLC patients, and 31 genes are down-expressed. All our analyses show that these genes are involved in metastatic SCLC. PPI analysis revealed two hub genes (CAT and APP). The results of this article present three lncRNAs, Including XLOC_l2_000941, LOC100507481, and XLOC_l2_007062, also notable mRNAs, have a close relation with brain metastasis in lung cancer and may have a role in the epithelial-mesenchymal transition (EMT) in tumour cells.

Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Background: Immunotherapy has been a promising approach option for lung cancer.

Method: All the open-accessed data was obtained from the Cancer Genome Atlas (TCGA) database. All the analysis was conducted using the R software analysis.

Results: Firstly, the genes differentially expressed in lung cancer immunotherapy responders and non-responders were identified. Then, the lung adenocarcinoma immunotherapy-related genes were determined by LASSO logistic regression and SVM-RFE, respectively. A total of 18 immunotherapy response-related genes were included in our investigation. Subsequently, we constructed the logistics score model. Patients with high logistics score had a better clinical effect on immunotherapy, with 63.2% of patients responding to immunotherapy, while only 12.1% of patients in the low logistics score group responded to immunotherapy. Moreover, we found that pathways related to immunotherapy were mainly enriched in metabolic pathways such as fatty acid metabolism, bile acid metabolism, oxidative phosphorylation, and carcinogenic pathways such as KRAS signaling. Logistics score was positively correlated with NK cells activated, Mast cells resting, Monocytes, Macrophages M2, dendritic cells resting, dendritic cells activated and eosinophils, while was negatively related to Tregs, macrophages M0, macrophages M1, and mast cells activated. In addition, ERVH48-1 was screened for single-cell exploration. The expression of ERVH48-1 increased in patients with distant metastasis, and ERVH48-1 was associated with pathways such as pancreas beta cells, spermatogenesis, G2M checkpoints and KRAS signaling. The result of quantitative real-time PCR showed that ERVH48-1 was upregulated in lung cancer cells.

Conclusion: Our study developed an effective signature to predict the immunotherapy response of lung cancer patients.

The CRISPR Revolution in the Drug Discovery Workflow: An Industry Perspective

In a relatively short time, the pharmaceutical industry has witnessed a rapid integration of the CRISPR technology in multiple areas of research, development, therapy, and diagnostics. A unique feature to this system compared with other technologies is the exceptional versatility in adapting to the broad range of needs across the drug discovery pipeline, such as target identification, cell engineering, and in vivo modeling. As a consequence, the CRISPR toolbox has been evolving to address key questions around preclinical and clinical drug development. In this review, we provide a high-level perspective of how CRISPR has impacted several aspects of the drug discovery workflow and the future ahead for this exciting technology.

Genetic, Metabolic and Immunological Features of Cancers with NRF2 Addiction

Nuclear factor erythroid-derived 2-like 2 (NRF2) is a master transcription factor that coordinately regulates the expression of many cytoprotective genes and plays a central role in defense mechanisms against oxidative and electrophilic insults. Although increased NRF2 activity is principally beneficial for our health, NRF2 activation in cancer cells is detrimental. Many human cancers exhibit persistent NRF2 activation and such cancer cells rely on NRF2 for most of their malignant characteristics, such as therapeutic resistance and aggressive tumorigenesis, and thus fall into NRF2 addiction. The persistent activation of NRF2 confers great advantages on cancer cells, whereas it is not tolerated by normal cells, suggesting that certain requirements are necessary for a cell to exploit NRF2 and evolve into malignant a cancer cell. In this review, recent reports and data on the genetic, metabolic and immunological features of NRF2-activated cancer cells are summarized, and prerequisites for NRF2 addiction in cancer cells and their therapeutic applications are discussed.

Patient-Derived Lung Tumoroids—An Emerging Technology in Drug Development and Precision Medicine

Synthetic 3D multicellular systems derived from patient tumors, or tumoroids, have been developed to complete the cancer research arsenal and overcome the limits of current preclinical models. They aim to represent the molecular and structural heterogeneity of the tumor micro-environment, and its complex network of interactions, with greater accuracy. They are more predictive of clinical outcomes, of adverse events, and of resistance mechanisms. Thus, they increase the success rate of drug development, and help clinicians in their decision-making process. Lung cancer remains amongst the deadliest of diseases, and still requires intensive research. In this review, we analyze the merits and drawbacks of the current preclinical models used in lung cancer research, and the position of tumoroids. The introduction of immune cells and healthy regulatory cells in autologous tumoroid models has enabled their application to most recent therapeutic concepts. The possibility of deriving tumoroids from primary tumors within reasonable time has opened a direct approach to patient-specific features, supporting their future role in precision medicine.

Concurrent TP53 Mutations Facilitate Resistance Evolution in EGFR-Mutant Lung Adenocarcinoma

INTRODUCTION

Patients with EGFR-mutant NSCLC experience variable duration of benefit on EGFR tyrosine kinase inhibitors. The effect of concurrent genomic alterations on outcome has been incompletely described.

METHODS

In this retrospective study, targeted next-generation sequencing data were collected from patients with EGFR-mutant lung cancer treated at the Dana-Farber Cancer Institute. Clinical data were collected and correlated with somatic mutation data. Associations between TP53 mutation status, genomic features, and mutational processes were analyzed.

RESULTS

A total of 269 patients were identified for inclusion in the cohort. Among 185 response-assessable patients with pretreatment specimens, TP53 alterations were the most common event associated with decreased first-line progression-free survival and decreased overall survival, along with DNMT3A, KEAP1, and ASXL1 alterations. Reduced progression-free survival on later-line osimertinib in 33 patients was associated with MET, APC, and ERBB4 alterations. Further investigation of the effect of TP53 alterations revealed an association with worse outcomes even in patients with good initial radiographic response, and faster acquisition of T790M and other resistance mechanisms. TP53-mutated tumors had higher mutational burdens and increased mutagenesis with exposure to therapy and tobacco. Cell cycle alterations were not independently predictive, but portended worse OS in conjunction with TP53 alterations.

CONCLUSIONS

TP53 alterations associate with faster resistance evolution independent of mechanism in EGFR-mutant NSCLC and may cooperate with other genomic events to mediate acquisition of resistance mutations to EGFR tyrosine kinase inhibitors.

Deficiency of the splicing factor RBM10 limits EGFR inhibitor response in EGFR mutant lung cancer

Molecularly targeted cancer therapy has improved outcomes for patients with cancer with targetable oncoproteins, such as mutant EGFR in lung cancer. Yet, the long-term survival of these patients remains limited, because treatment responses are typically incomplete. One potential explanation for the lack of complete and durable responses is that oncogene-driven cancers with activating mutations of EGFR often harbor additional co-occurring genetic alterations. This hypothesis remains untested for most genetic alterations that co-occur with mutant EGFR. Here, we report the functional impact of inactivating genetic alterations of the mRNA splicing factor RNA-binding motif 10 (RBM10) that co-occur with mutant EGFR. RBM10 deficiency decreased EGFR inhibitor efficacy in patient-derived EGFR-mutant tumor models. RBM10 modulated mRNA alternative splicing of the mitochondrial apoptotic regulator Bcl-x to regulate tumor cell apoptosis during treatment. Genetic inactivation of RBM10 diminished EGFR inhibitor–mediated apoptosis by decreasing the ratio of (proapoptotic) Bcl-xS to (antiapoptotic) Bcl-xL isoforms of Bcl-x. RBM10 deficiency was a biomarker of poor response to EGFR inhibitor treatment in clinical samples. Coinhibition of Bcl-xL and mutant EGFR overcame the resistance induced by RBM10 deficiency. This study sheds light on the role of co-occurring genetic alterations and on the effect of splicing factor deficiency on the modulation of sensitivity to targeted kinase inhibitor cancer therapy.

Retinoblastoma Protein Paralogs and Tumor Suppression

The retinoblastoma susceptibility gene (RB1) is the first tumor suppressor gene discovered and a prototype for understanding regulatory networks that function in opposition to oncogenic stimuli. More than 3 decades of research has firmly established a widespread and prominent role for RB1 in human cancer. Yet, this gene encodes but one of three structurally and functionally related proteins that comprise the pocket protein family. A central question in the field is whether the additional genes in this family, RBL1 and RBL2, are important tumor suppressor genes. If so, how does their tumor suppressor activity overlap or differ from RB1. Here we revisit these questions by reviewing relevant data from human cancer genome sequencing studies that have been rapidly accumulating in recent years as well as pertinent functional studies in genetically engineered mice. We conclude that RBL1 and RBL2 do have important tumor suppressor activity in some contexts, but RB1 remains the dominant tumor suppressor in the family. Given their similarities, we speculate on why RB1 tumor suppressor activity is unique.

Premetastatic shifts of endogenous and exogenous mutational processes support consolidative therapy in EGFR-driven lung adenocarcinoma

The progression of cancer is an evolutionary process that is challenging to assess between sampling timepoints. However, investigation of cancer evolution over specific time periods is crucial to the elucidation of key events such as the acquisition of therapeutic resistance and subsequent fatal metastatic spread of therapy-resistant cell populations. Here we apply mutational signature analyses within clinically annotated cancer chronograms to detect and describe the shifting mutational processes caused by both endogenous (e.g. mutator gene mutation) and exogenous (e.g. mutagenic therapeutics) factors between tumor sampling timepoints. In one patient, we find that cisplatin therapy can introduce mutations that confer genetic resistance to subsequent targeted therapy with Erlotinib. In another patient, we trace detection of defective mismatch-repair associated mutational signature SBS3 to the emergence of known driver mutation CTNNB1 S37C. In both of these patients, metastatic lineages emerged from a single ancestral lineage that arose during therapy-a finding that argues for the consideration of local consolidative therapy over other therapeutic approaches in EGFR-positive non-small cell lung cancer. Broadly, these results demonstrate the utility of phylogenetic analysis that incorporates clinical time course and mutational signature deconvolution to inform therapeutic decision making and retrospective assessment of disease etiology.

Tumor suppressor pathways shape EGFR-driven lung tumor progression and response to treatment

In vivo modeling combined with CRISPR/Cas9-mediated somatic genome editing has contributed to elucidating the functional importance of specific genetic alterations in human tumors. Our recent work uncovered tumor suppressor pathways that affect EGFR-driven lung tumor growth and sensitivity to tyrosine kinase inhibitors and reflect the mutational landscape and treatment outcomes in the human disease.

Observation on the clinical efficacy and side effects of EGFR-TKI ± chemotherapy in the treatment of EGFR mutation-positive advanced lung adenocarcinoma

Objective

To assess the clinical efficacy and side effects of EGFR-TKI with or without chemotherapy in the treatment of EGFR mutation-positive advanced lung adenocarcinoma.

Methods

A total of 103 IIIB or IV EGFR mutation-positive lung adenocarcinoma patients admitted to the oncology department of Fujian Provincial Hospital from January 2017 to October 2020 were selected. According to genetic mutation status, patients were divided into the following groups: 19del alone, 19del combined with TP53 or other co-mutations, L858R mutation alone, and L858R mutation combined with TP53 or other co-mutations. Targeted drugs or targeted drugs combined with chemotherapy were respectively administered in the four groups. In patients with simple 19 deletion, only targeted drugs with no combined therapy were applied, resulting in seven total groups. The difference between short-term treatment and long-term treatment effects and the occurrence of adverse reactions was calculated and compared.

Results

There was no statistical significance of difference in the incidence of adverse reactions in seven groups ( p > 0.05). The short-term disease control rate of the combination group was higher than the targeted drug group with the difference yielding statistical significance ( p < 0.001). The short-term objective response rate of the combination group was higher than the targeted drug group, also yielding statistical significance ( p < 0.001). By October 2020, the median progression-free survival (PFS) was 16 months in the EGFR-TKI-targeted combined with chemotherapy group and 10 months in the single-drug EGFR-TKI group, and the PFS time was longer in the combination group than in the single targeted drug group, the difference being statistically significant ( p = 0.001).

Conclusions

In the treatment of advanced lung adenocarcinoma patients with EGFR-gene sensitive mutations, compared with single EGFR-TKI-targeted therapy, EGFR-TKI-targeted drug combined chemotherapy can control the disease progression more effectively, and does not increase adverse reactions.

Preclinical Models for the Study of Lung Cancer Pathogenesis and Therapy Development

Experimental preclinical models have been a cornerstone of lung cancer translational research. Work in these model systems has provided insights into the biology of lung cancer subtypes and their origins, contributed to our understanding of the mechanisms that underlie tumor progression, and revealed new therapeutic vulnerabilities. Initially patient-derived lung cancer cell lines were the main preclinical models available. The landscape is very different now with numerous preclinical models for research each with unique characteristics. These include genetically engineered mouse models (GEMMs), patient-derived xenografts (PDXs) and three-dimensional culture systems ("organoid" cultures). Here we review the development and applications of these models and describe their contributions to lung cancer research.

Capturing cancer evolution using genetically engineered mouse models (GEMMs)

Initiating from a single cell, cancer undergoes clonal evolution, leading to a high degree of intratumor heterogeneity (ITH). The arising genetic heterogeneity between cancer cells is influenced by exogenous and endogenous forces that shape the composition of clones within tumors. Preclinical mouse models have provided a valuable tool for understanding cancer, helping to build a fundamental understanding of tumor initiation, progression, and metastasis. Until recently, genetically engineered mouse models (GEMMS) of cancer had lacked the genetic diversity found in human tumors, in which evolution may be driven by long-term carcinogen exposure and DNA damage. However, advances in sequencing technology and in our understanding of the drivers of genetic instability have given us the knowledge to generate new mouse models, offering an approach to functionally explore mechanisms of tumor evolution.

Context Matters-Why We Need to Change From a One Size Fits all Approach to Made-to-Measure Therapies for Individual Patients With Pancreatic Cancer

Pancreatic cancer is one of the deadliest cancers and remains a major unsolved health problem. While pancreatic ductal adenocarcinoma (PDAC) is associated with driver mutations in only four major genes (KRAS, TP53, SMAD4, and CDKN2A), every tumor differs in its molecular landscape, histology, and prognosis. It is crucial to understand and consider these differences to be able to tailor treatment regimens specific to the vulnerabilities of the individual tumor to enhance patient outcome. This review focuses on the heterogeneity of pancreatic tumor cells and how in addition to genetic alterations, the subsequent dysregulation of multiple signaling cascades at various levels, epigenetic and metabolic factors contribute to the oncogenesis of PDAC and compensate for each other in driving cancer progression if one is tackled by a therapeutic approach. This implicates that besides the need for new combinatorial therapies for PDAC, a personalized approach for treating this highly complex cancer is required. A strategy that combines both a target-based and phenotypic approach to identify an effective treatment, like Reverse Clinical Engineering® using patient-derived organoids, is discussed as a promising way forward in the field of personalized medicine to tackle this deadly disease.

RNA-binding proteins of COSMIC importance in cancer

Herculean efforts by the Wellcome Sanger Institute, the National Cancer Institute, and the National Human Genome Research Institute to sequence thousands of tumors representing all major cancer types have yielded more than 700 genes that contribute to neoplastic growth when mutated, amplified, or deleted. While some of these genes (now included in the COSMIC Cancer Gene Census) encode proteins previously identified in hypothesis-driven experiments (oncogenic transcription factors, protein kinases, etc.), additional classes of cancer drivers have emerged, perhaps none more surprisingly than RNA-binding proteins (RBPs). Over 40 RBPs responsible for virtually all aspects of RNA metabolism, from synthesis to degradation, are recurrently mutated in cancer, and just over a dozen are considered major cancer drivers. This Review investigates whether and how their RNA-binding activities pertain to their oncogenic functions. Focusing on several well-characterized steps in RNA metabolism, we demonstrate that for virtually all cancer-driving RBPs, RNA processing activities are either abolished (the loss-of-function phenotype) or carried out with low fidelity (the LoFi phenotype). Conceptually, this suggests that in normal cells, RBPs act as gatekeepers maintaining proper RNA metabolism and the "balanced" proteome. From the practical standpoint, at least some LoFi phenotypes create therapeutic vulnerabilities, which are beginning to be exploited in the clinic.

EGFR Status Assessment for Better Care of Early Stage Non-Small Cell Lung Carcinoma: What Is Changing in the Daily Practice of Pathologists?

The recent emergence of novel neoadjuvant and/or adjuvant therapies for early stage (I-IIIA) non-small cell lung carcinoma (NSCLC), mainly tyrosine kinase inhibitors (TKIs) targeting EGFR mutations and immunotherapy or chemo-immunotherapy, has suddenly required the evaluation of biomarkers predictive of the efficacy of different treatments in these patients. Currently, the choice of one or another of these treatments mainly depends on the results of immunohistochemistry for PD-L1 and of the status of EGFR and ALK. This new development has led to the setup of different analyses for clinical and molecular pathology laboratories, which have had to rapidly integrate a number of new challenges into daily practice and to establish new organization for decision making. This review outlines the impact of the management of biological samples in laboratories and discusses perspectives for pathologists within the framework of EGFR TKIs in early stage NSCLC.

Cycling cancer persister cells arise from lineages with distinct programs

Non-genetic mechanisms have recently emerged as important drivers of cancer therapy failure¹, where some cancer cells can enter a reversible drug-tolerant persister state in response to treatment². Although most cancer persisters remain arrested in the presence of the drug, a rare subset can re-enter the cell cycle under constitutive drug treatment. Little is known about the non-genetic mechanisms that enable cancer persisters to maintain proliferative capacity in the presence of drugs. To study this rare, transiently resistant, proliferative persister population, we developed Watermelon, a high-complexity expressed barcode lentiviral library for simultaneous tracing of each cell's clonal origin and proliferative and transcriptional states. Here we show that cycling and non-cycling persisters arise from different cell lineages with distinct transcriptional and metabolic programs. Upregulation of antioxidant gene programs and a metabolic shift to fatty acid oxidation are associated with persister proliferative capacity across multiple cancer types. Impeding oxidative stress or metabolic reprogramming alters the fraction of cycling persisters. In human tumours, programs associated with cycling persisters are induced in minimal residual disease in response to multiple targeted therapies. The Watermelon system enabled the identification of rare persister lineages that are preferentially poised to proliferate under drug pressure, thus exposing new vulnerabilities that can be targeted to delay or even prevent disease recurrence.

Quantitative In Vivo Analyses Reveal a Complex Pharmacogenomic Landscape in Lung Adenocarcinoma

The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most critical gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative experimental platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. The complex map of genotype-specific treatment responses uncovered that over 20% of possible interactions show significant resistance or sensitivity. Known and novel interactions were identified, and one of these interactions, the resistance of KEAP1-mutant lung tumors to platinum therapy, was validated using a large patient response data set. These results highlight the broad impact of tumor suppressor genotype on treatment responses and define a strategy to identify the determinants of precision therapies. SIGNIFICANCE: An experimental and analytical framework to generate in vivo pharmacogenomic maps that relate tumor genotypes to therapeutic responses reveals a surprisingly complex map of genotype-specific resistance and sensitivity.

A Functional Taxonomy of Tumor Suppression in Oncogenic KRAS-Driven Lung Cancer

Cancer genotyping has identified a large number of putative tumor suppressor genes. Carcinogenesis is a multistep process, but the importance and specific roles of many of these genes during tumor initiation, growth, and progression remain unknown. Here we use a multiplexed mouse model of oncogenic KRAS-driven lung cancer to quantify the impact of 48 known and putative tumor suppressor genes on diverse aspects of carcinogenesis at an unprecedented scale and resolution. We uncover many previously understudied functional tumor suppressors that constrain cancer in vivo. Inactivation of some genes substantially increased growth, whereas the inactivation of others increases tumor initiation and/or the emergence of exceptionally large tumors. These functional in vivo analyses revealed an unexpectedly complex landscape of tumor suppression that has implications for understanding cancer evolution, interpreting clinical cancer genome sequencing data, and directing approaches to limit tumor initiation and progression. SIGNIFICANCE: Our high-throughput and high-resolution analysis of tumor suppression uncovered novel genetic determinants of oncogenic KRAS-driven lung cancer initiation, overall growth, and exceptional growth. This taxonomy is consistent with changing constraints during the life history of cancer and highlights the value of quantitative in vivo genetic analyses in autochthonous cancer models.This article is highlighted in the In This Issue feature, p. 1601.

What Is New in Biomarker Testing at Diagnosis of Advanced Non-Squamous Non-Small Cell Lung Carcinoma? Implications for Cytology and Liquid Biopsy

The discovery and clinical validation of biomarkers predictive of the response of non-squamous non-small-cell lung carcinomas (NS-NSCLC) to therapeutic strategies continue to provide new data. The evaluation of novel treatments is based on molecular analyses aimed at determining their efficacy. These tests are increasing in number, but the tissue specimens are smaller and smaller and/or can have few tumor cells. Indeed, in addition to tissue samples, complementary cytological and/or blood samples can also give access to these biomarkers. To date, it is recommended and necessary to look for the status of five genomic molecular biomarkers (EGFR, ALK, ROS1, BRAFV600, NTRK) and of a protein biomarker (PD-L1). However, the short- and more or less long-term emergence of new targeted treatments of genomic alterations on RET and MET, but also on others’ genomic alteration, notably on KRAS, HER2, NRG1, SMARCA4, and NUT, have made cellular and blood samples essential for molecular testing. The aim of this review is to present the interest in using cytological and/or liquid biopsies as complementary biological material, or as an alternative to tissue specimens, for detection at diagnosis of new predictive biomarkers of NS-NSCLC.