Adeno-to-squamous transition drives resistance to KRAS inhibition in LKB1 mutant lung cancer.

KRASG12C inhibitors (adagrasib and sotorasib) have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients eventually develop resistance. In lung patients with adenocarcinoma with KRASG12C and STK11/LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids treated with KRAS inhibitors reveal tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. Transcriptomic and epigenomic analyses reveal ΔNp63 drives AST and modulates response to KRAS inhibition. We identify an intermediate high-plastic cell state marked by expression of an AST plasticity signature and Krt6a. Notably, expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

EML4-ALK fusions drive lung adeno-to-squamous transition through JAK-STAT activation.

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, exhibits strong cancer plasticity. We find that ALK rearrangement is detectable in 5.1-7.5% of human LUAS, and transgenic expression of EML4-ALK drives lung adenocarcinoma (LUAD) formation initially and squamous transition at late stage. We identify club cells as the main cell-of-origin for squamous transition. Through recapitulating lineage transition in organoid system, we identify JAK-STAT signaling, activated by EML4-ALK phase separation, significantly promotes squamous transition. Integrative study with scRNA-seq and immunostaining identify a plastic cell subpopulation in ALK-rearranged human LUAD showing squamous biomarker expression. Moreover, those relapsed ALK-rearranged LUAD show notable upregulation of squamous biomarkers. Consistently, mouse squamous tumors or LUAD with squamous signature display certain resistance to ALK inhibitor, which can be overcome by combined JAK1/2 inhibitor treatment. This study uncovers strong plasticity of ALK-rearranged tumors in orchestrating phenotypic transition and drug resistance and proposes a potentially effective therapeutic strategy.

Counteracting lineage-specific transcription factor network finely tunes lung adeno-to-squamous transdifferentiation through remodeling tumor immune microenvironment.

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, harbors strong plasticity and is significantly associated with poor prognosis. We established an up-to-date comprehensive genomic and transcriptomic landscape of LUAS in 109 Chinese specimens and demonstrated LUAS development via adeno-to-squamous transdifferentiation. Unsupervised transcriptomic clustering and dynamic network biomarker analysis identified an inflammatory subtype as the critical transition stage during LUAS development. Dynamic dysregulation of the counteracting lineage-specific transcription factors (TFs), containing adenomatous TFs NKX2-1 and FOXA2, and squamous TFs TP63 and SOX2, finely tuned the lineage transition via promoting CXCL3/5-mediated neutrophil infiltration. Genomic clustering identified the most malignant subtype featured with STK11-inactivation, and targeting LSD1 through genetic deletion or pharmacological inhibition almost eradicated STK11-deficient lung tumors. These data collectively uncover the comprehensive molecular landscape, oncogenic driver spectrum and therapeutic vulnerability of Chinese LUAS.

Oxidative stress-triggered Wnt signaling perturbation characterizes the tipping point of lung adeno-to-squamous transdifferentiation.

Lkb1 deficiency confers the Kras-mutant lung cancer with strong plasticity and the potential for adeno-to-squamous transdifferentiation (AST). However, it remains largely unknown how Lkb1 deficiency dynamically regulates AST. Using the classical AST mouse model (Kras LSL-G12D/+;Lkb1flox/flox, KL), we here comprehensively analyze the temporal transcriptomic dynamics of lung tumors at different stages by dynamic network biomarker (DNB) and identify the tipping point at which the Wnt signaling is abruptly suppressed by the excessive accumulation of reactive oxygen species (ROS) through its downstream effector FOXO3A. Bidirectional genetic perturbation of the Wnt pathway using two different Ctnnb1 conditional knockout mouse strains confirms its essential role in the negative regulation of AST. Importantly, pharmacological activation of the Wnt pathway before but not after the tipping point inhibits squamous transdifferentiation, highlighting the irreversibility of AST after crossing the tipping point. Through comparative transcriptomic analyses of mouse and human tumors, we find that the lineage-specific transcription factors (TFs) of adenocarcinoma and squamous cell carcinoma form a "Yin-Yang" counteracting network. Interestingly, inactivation of the Wnt pathway preferentially suppresses the adenomatous lineage TF network and thus disrupts the "Yin-Yang" homeostasis to lean towards the squamous lineage, whereas ectopic expression of NKX2-1, an adenomatous lineage TF, significantly dampens such phenotypic transition accelerated by the Wnt pathway inactivation. The negative correlation between the Wnt pathway and AST is further observed in a large cohort of human lung adenosquamous carcinoma. Collectively, our study identifies the tipping point of AST and highlights an essential role of the ROS-Wnt axis in dynamically orchestrating the homeostasis between adeno- and squamous-specific TF networks at the AST tipping point.

Loss of TSC1/TSC2 sensitizes immune checkpoint blockade in non-small cell lung cancer.

Tuberous sclerosis complex subunit 1 (TSC1) and 2 (TSC2) are frequently mutated in non-small cell lung cancer (NSCLC), however, their effects on antitumor immunity remained unexplored. A CRISPR screening in murine KrasG12D/Trp53-/- (KP) model identified Tsc1 and Tsc2 as potent regulators of programmed cell death ligand 1 (Pd-l1) expression in vitro and sensitivity to anti-programmed cell death receptor 1 (PD-1) treatment in vivo. TSC1 or TSC2 knockout (KO) promoted the transcriptional and membrane expression of PD-L1 in cell lines. TSC2-deficient tumors manifested an inflamed microenvironment in patient samples and The Cancer Genome Atlas dataset. In syngeneic murine models, KP-Tsc2-KO tumors showed notable response to anti-PD-1 antibody treatment, but Tsc2-wild-type tumors did not. Patients with TSC1/TSC2-mutant NSCLC receiving immune checkpoint blockade (ICB) had increased durable clinical benefit and survival. Collectively, TSC1/TSC2 loss defines a distinct subtype of NSCLC characterized as inflamed tumor microenvironment and superior sensitivity to ICB.

Targeting HSPA1A in ARID2-deficient lung adenocarcinoma.

Somatic mutations of the chromatin remodeling gene ARID2 are observed in ∼7% of human lung adenocarcinomas (LUADs). However, the role of ARID2 in the pathogenesis of LUADs remains largely unknown. Here we find that ARID2 expression is decreased during the malignant progression of both human and mice LUADs. Using two KrasG12D -based genetically engineered murine models, we demonstrate that ARID2 knockout significantly promotes lung cancer malignant progression and shortens overall survival. Consistently, ARID2 knockdown significantly promotes cell proliferation in human and mice lung cancer cells. Through integrative analyses of ChIP-Seq and RNA-Seq data, we find that Hspa1a is up-regulated by Arid2 loss. Knockdown of Hspa1a specifically inhibits malignant progression of Arid2-deficient but not Arid2-wt lung cancers in both cell lines as well as animal models. Treatment with an HSPA1A inhibitor could significantly inhibit the malignant progression of lung cancer with ARID2 deficiency. Together, our findings establish ARID2 as an important tumor suppressor in LUADs with novel mechanistic insights, and further identify HSPA1A as a potential therapeutic target in ARID2-deficient LUADs.

Recognizing Pattern and Rule of Mutation Signatures Corresponding to Cancer Types.

Cancer has been generally defined as a cluster of systematic malignant pathogenesis involving abnormal cell growth. Genetic mutations derived from environmental factors and inherited genetics trigger the initiation and progression of cancers. Although several well-known factors affect cancer, mutation features and rules that affect cancers are relatively unknown due to limited related studies. In this study, a computational investigation on mutation profiles of cancer samples in 27 types was given. These profiles were first analyzed by the Monte Carlo Feature Selection (MCFS) method. A feature list was thus obtained. Then, the incremental feature selection (IFS) method adopted such list to extract essential mutation features related to 27 cancer types, find out 207 mutation rules and construct efficient classifiers. The top 37 mutation features corresponding to different cancer types were discussed. All the qualitatively analyzed gene mutation features contribute to the distinction of different types of cancers, and most of such mutation rules are supported by recent literature. Therefore, our computational investigation could identify potential biomarkers and prediction rules for cancers in the mutation signature level.

TransRef enables accurate transcriptome assembly by redefining accurate neo-splicing graphs.

RNA-seq technology is widely employed in various research areas related to transcriptome analyses, and the identification of all the expressed transcripts from short sequencing reads presents a considerable computational challenge. In this study, we introduce TransRef, a new computational algorithm for accurate transcriptome assembly by redefining a novel graph model, the neo-splicing graph, and then iteratively applying a constrained dynamic programming to reconstruct all the expressed transcripts for each graph. When TransRef is utilized to analyze both real and simulated datasets, its performance is notably better than those of several state-of-the-art assemblers, including StringTie2, Cufflinks and Scallop. In particular, the performance of TransRef is notably strong in identifying novel transcripts and transcripts with low-expression levels, while the other assemblers are less effective.

c-CSN: Single-cell RNA Sequencing Data Analysis by Conditional Cell-specific Network.

The rapid advancement of single-cell technologies has shed new light on the complex mechanisms of cellular heterogeneity. However, compared to bulk RNA sequencing (RNA-seq), single-cell RNA-seq (scRNA-seq) suffers from higher noise and lower coverage, which brings new computational difficulties. Based on statistical independence, cell-specific network (CSN) is able to quantify the overall associations between genes for each cell, yet suffering from a problem of overestimation related to indirect effects. To overcome this problem, we propose the c-CSN method, which can construct the conditional cell-specific network (CCSN) for each cell. c-CSN method can measure the direct associations between genes by eliminating the indirect associations. c-CSN can be used for cell clustering and dimension reduction on a network basis of single cells. Intuitively, each CCSN can be viewed as the transformation from less "reliable" gene expression to more "reliable" gene-gene associations in a cell. Based on CCSN, we further design network flow entropy (NFE) to estimate the differentiation potency of a single cell. A number of scRNA-seq datasets were used to demonstrate the advantages of our approach. 1) One direct association network is generated for one cell. 2) Most existing scRNA-seq methods designed for gene expression matrices are also applicable to c-CSN-transformed degree matrices. 3) CCSN-based NFE helps resolving the direction of differentiation trajectories by quantifying the potency of each cell. c-CSN is publicly available at https://github.com/LinLi-0909/c-CSN.

ZFP57 dictates allelic expression switch of target imprinted genes.

ZFP57 is a master regulator of genomic imprinting. It has both maternal and zygotic functions that are partially redundant in maintaining DNA methylation at some imprinting control regions (ICRs). In this study, we found that DNA methylation was lost at most known ICRs in Zfp57 mutant embryos. Furthermore, loss of ZFP57 caused loss of parent-of-origin-dependent monoallelic expression of the target imprinted genes. The allelic expression switch occurred in the ZFP57 target imprinted genes upon loss of differential DNA methylation at the ICRs in Zfp57 mutant embryos. Specifically, upon loss of ZFP57, the alleles of the imprinted genes located on the same chromosome with the originally methylated ICR switched their expression to mimic their counterparts on the other chromosome with unmethylated ICR. Consistent with our previous study, ZFP57 could regulate the NOTCH signaling pathway in mouse embryos by impacting allelic expression of a few regulators in the NOTCH pathway. In addition, the imprinted Dlk1 gene that has been implicated in the NOTCH pathway was significantly down-regulated in Zfp57 mutant embryos. Our allelic expression switch models apply to the examined target imprinted genes controlled by either maternally or paternally methylated ICRs. Our results support the view that ZFP57 controls imprinted expression of its target imprinted genes primarily through maintaining differential DNA methylation at the ICRs.

Chromobox 4 facilitates tumorigenesis of lung adenocarcinoma through the Wnt/ß-catenin pathway.

Chromobox 4 (CBX4) is a core component of polycomb-repressive complex 1 with important roles in cancer biology and tissue homeostasis. Aberrant expression of CBX4 has been implicated in several human malignancies. However, its role and underlying mechanisms in the tumorigenesis of lung adenocarcinoma (LUAD) have not been defined in vivo. Here, we found that expression of CBX4 was frequently up-regulated in human LUAD samples and correlated with poor patient survival. Importantly, genetic ablation of CBX4 greatly dampened lung tumor formation and improved survival in the KrasG12D/P53L/L (KP) autochthonous mouse model of LUAD. In addition, CBX4 depletion significantly inhibited proliferation and anchorage-independent growth of KP mouse embryonic fibroblasts. Moreover, ectopic CBX4 expression clearly promoted proliferation and anchorage-independent growth in both human and mouse LUAD cells, whereas silencing of CBX4 exerted opposite effects. Mechanistically, CBX4 promoted growth of LUAD cells through activation of the Wnt/ß-catenin pathway. Furthermore, expression levels of CBX4 were positively correlated with ß-catenin in human LUAD samples. In conclusion, our data suggest that CBX4 plays an oncogenic role via the Wnt/ß-catenin pathway and could serve as a potential therapeutic target in LUAD.

QKI-5 regulates the alternative splicing of cytoskeletal gene ADD3 in lung cancer.

Accumulating evidence indicates that the alternative splicing program undergoes extensive changes during cancer development and progression. The RNA-binding protein QKI-5 is frequently downregulated and exhibits anti-tumor activity in lung cancer. Howeve-r, little is known about the functional targets and regulatory mechanism of QKI-5. Here, we report that upregulation of exon 14 inclusion of cytoskeletal gene Adducin 3 (ADD3) significantly correlates with a poor prognosis in lung cancer. QKI-5 inhibits cell proliferation and migration in part through suppressing the splicing of ADD3 exon 14. Through genome-wide mapping of QKI-5 binding sites in vivo at nucleotide resolution by iCLIP-seq analysis, we found that QKI-5 regulates alternative splicing of its target mRNAs in a binding position-dependent manner. By binding to multiple sites in an upstream intron region, QKI-5 represses the splicing of ADD3 exon 14. We also identified several QKI mutations in tumors, which cause dysregulation of the splicing of QKI targets ADD3 and NUMB. Taken together, our results reveal that QKI-mediated alternative splicing of ADD3 is a key lung cancer-associated splicing event, which underlies in part the tumor suppressor function of QKI.

A systematic survey of PRMT interactomes reveals the key roles of arginine methylation in the global control of RNA splicing and translation.

Thousands of proteins undergo arginine methylation, a widespread post-translational modification catalyzed by several protein arginine methyltransferases (PRMTs). However, global understanding of their biological functions is limited due to the lack of a complete picture of the catalytic network for each PRMT. Here, we systematically identified interacting proteins for all human PRMTs and demonstrated their functional importance in mRNA splicing and translation. We demonstrated significant overlapping of interactomes of human PRMTs with the known methylarginine-containing proteins. Different PRMTs are functionally redundant with a high degree of overlap in their substrates and high similarities between their putative methylation motifs. Importantly, RNA-binding proteins involved in regulating RNA splicing and translation contain highly enriched arginine methylation regions. Moreover, inhibition of PRMTs globally alternates alternative splicing (AS) and suppresses translation. In particular, ribosomal proteins are extensively modified with methylarginine, and mutations in their methylation sites suppress ribosome assembly, translation, and eventually cell growth. Collectively, our study provides a global view of different PRMT networks and uncovers critical functions of arginine methylation in regulating mRNA splicing and translation.

TransCirc: an interactive database for translatable circular RNAs based on multi-omics evidence.

TransCirc (https://www.biosino.org/transcirc/) is a specialized database that provide comprehensive evidences supporting the translation potential of circular RNAs (circRNAs). This database was generated by integrating various direct and indirect evidences to predict coding potential of each human circRNA and the putative translation products. Seven types of evidences for circRNA translation were included: (i) ribosome/polysome binding evidences supporting the occupancy of ribosomes onto circRNAs; (ii) experimentally mapped translation initiation sites on circRNAs; (iii) internal ribosome entry site on circRNAs; (iv) published N-6-methyladenosine modification data in circRNA that promote translation initiation; (v) lengths of the circRNA specific open reading frames; (vi) sequence composition scores from a machine learning prediction of all potential open reading frames; (vii) mass spectrometry data that directly support the circRNA encoded peptides across back-splice junctions. TransCirc provides a user-friendly searching/browsing interface and independent lines of evidences to predicte how likely a circRNA can be translated. In addition, several flexible tools have been developed to aid retrieval and analysis of the data. TransCirc can serve as an important resource for investigating the translation capacity of circRNAs and the potential circRNA-encoded peptides, and can be expanded to include new evidences or additional species in the future.

Mutational Landscape and Evolutionary Pattern of Liver and Brain Metastasis in Lung Adenocarcinoma.

INTRODUCTION: A comprehensive genomic analysis of paired primary tumors and their metastatic lesions may provide new insights into the biology of metastatic processes and therefore guide the development of novel strategies for intervention. To date, our knowledge of the genetic divergence and phylogenetic relationships among diverse metastatic lesions from cancer remains limited. METHODS: We performed whole-exome sequencing in 84 tissue and blood samples from 26 patients with lung adenocarcinoma having liver metastases (LiM) or brain metastases (BrM) before any systemic therapy, with the goal to molecularly characterize the metastatic process. Mutational landscape and evolutionary patterns were compared between paired primary lesions (primary lesion of LiM or BrM) and metastases (metastatic site of LiM or BrM). RESULTS: We found that common driver mutations, including TP53 and EGFR, were highly consistent between paired primary and metastatic tumors. Although tumor mutational burden was comparable among groups, the LiM group had significantly higher mutational and copy number variational similarity than the BrM group between paired primary lesions and metastases (p = 0.019 and p = 0.035, respectively). Phylogenetic analysis further revealed that LiM-competent disseminations had a higher level of genetic similarity to their paired primary lesions and were genetically diverged from their primary tumors at a relatively later stage than those of BrM. These results suggest that LiM favorably followed the linear progression model, whereas BrM was more consistent with the parallel progression model. CONCLUSIONS: This study suggests that the mutational landscape and evolutionary pattern was distinctly different between the LiM and BrM of lung adenocarcinoma.

Engineering the Berreman mode in mid-infrared polar materials.

We demonstrate coupling to and control over the broadening and dispersion of a mid-infrared leaky mode, known as the Berreman mode, in samples with different dielectric environments. We fabricate subwavelength films of AlN, a mid-infrared epsilon-near-zero material that supports the Berreman mode, on materials with a weakly negative permittivity, strongly negative permittivity, and positive permittivity. Additionally, we incorporate ultra-thin AlN layers into a GaN/AlN heterostructure, engineering the dielectric environment above and below the AlN. In each of the samples, coupling to the Berreman mode is observed in angle-dependent reflection measurements at wavelengths near the longitudinal optical phonon energy. The measured dispersion of the Berreman mode agrees well with numerical modes. Differences in the dispersion and broadening for the different materials is quantified, including a 13 cm-1 red-shift in the energy of the Berreman mode for the heterostructure sample.

TransBorrow: genome-guided transcriptome assembly by borrowing assemblies from different assemblers.

RNA-seq technology is widely used in various transcriptomic studies and provides great opportunities to reveal the complex structures of transcriptomes. To effectively analyze RNA-seq data, we introduce a novel transcriptome assembler, TransBorrow, which borrows the assemblies from different assemblers to search for reliable subsequences by building a colored graph from those borrowed assemblies. Then, by seeding reliable subsequences, a newly designed path extension strategy accurately searches for a transcript-representing path cover over each splicing graph. TransBorrow was tested on both simulated and real data sets and showed great superiority over all the compared leading assemblers.