Search

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.

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 associationsbetween 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.

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.

ABSTRACTAlterations of gut microbiota have been implicated in multiple diseases including cancer. However, the gut microbiota spectrum in lung cancer remains largely unknown. Here we profiled the gut microbiota composition in a discovery cohort containing 42 early-stage lung cancer patients and 65 healthy individuals through the 16S ribosomal RNA (rRNA) gene sequencing analysis. We found that lung cancer patients displayed a significant shift of microbiota composition in contrast to the healthy populations. To identify the optimal microbiota signature for noninvasive diagnosis purpose, we took advantage of Support-Vector Machine (SVM) and found that the predictive model with 13 operational taxonomic unit (OTU)-based biomarkers achieved a high accuracy in lung cancer prediction (area under curve, AUC = 97.6%). This signature performed reasonably well in the validation cohort (AUC = 76.4%), which contained 34 lung cancer patients and 40 healthy individuals. To facilitate potential clinical practice, we further constructed a ‘patient discrimination index’ (PDI), which largely retained the prediction efficiency in both the discovery cohort (AUC = 92.4%) and the validation cohort (AUC = 67.7%). Together, our study uncovered the microbiota spectrum of lung cancer patients and established the specific gut microbial signature for the potential prediction of the early-stage lung cancer.

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.

Methylation of cytosine to 5-methylcytosine (5mC) is a prevalent DNA modification found in many organisms. Sequential oxidation of 5mC by ten-eleven translocation (TET) dioxygenases results in a cascade of additional epigenetic marks and promotes demethylation of DNA in mammals1,2. However, the enzymatic activity and function of TET homologues in other eukaryotes remains largely unexplored. Here we show that the green alga Chlamydomonas reinhardtiicontains a 5mC-modifying enzyme (CMD1) that is a TET homologue and catalyses the conjugation of a glyceryl moiety to the methyl group of 5mC through a carbon–carbon bond, resulting in two stereoisomeric nucleobase products. The catalytic activity of CMD1 requires Fe(ii) and the integrity of its binding motif His-X-Asp, which is conserved in Fe-dependent dioxygenases3. However, unlike previously described TET enzymes, which use 2-oxoglutarate as a co-substrate4, CMD1 uses l-ascorbic acid (vitamin C) as an essential co-substrate. Vitamin C donates the glyceryl moiety to 5mC with concurrent formation of glyoxylic acid and CO2. The vitamin-C-derived DNA modification is present in the genome of wild-type C. reinhardtiibut at a substantially lower level in a CMD1mutant strain. The fitness of CMD1mutant cells during exposure to high light levels is reduced. LHCSR3, a gene that is critical for the protection of C. reinhardtiifrom photo-oxidative damage under high light conditions, is hypermethylated and downregulated in CMD1mutant cells compared to wild-type cells, causing a reduced capacity for photoprotective non-photochemical quenching. Our study thus identifies a eukaryotic DNA base modification that is catalysed by a divergent TET homologue and unexpectedly derived from vitamin C, and describes its role as a potential epigenetic mark that may counteract DNA methylation in the regulation of photosynthesis. An algal TET dioxygenase homologue, CMD1, uses vitamin C as a glycerol donor to modify 5-methylcytosine and helps to regulate gene transcription in response to high light levels.

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.

Lung squamous cell carcinoma (SCC) is one of the major subtypes of lung cancer. Our current knowledge of oncogenic drivers in this specific subtype of lung cancer is largely limited compared with lung adenocarcinoma (ADC). Through exon array analyses, molecular analyses and functional studies, we here identify the TRA2B-DNAH5 fusion as a novel oncogenic driver in lung SCC. We found that this gene fusion occurs exclusively in lung SCC (3.1%, 5/163), but not in lung ADC (0/119). Through mechanistic studies, we further revealed that this TRA2B-DNAH5 fusion promotes lung SCC malignant progression through regulating a SIRT6-ERK1/2-MMP1 signaling axis. We show that inhibition of ERK1/2 activation using selumetinib efficiently inhibits the growth of lung SCC with TRA2B-DNAH5 fusion expression. These findings improve our current knowledge of oncogenic drivers in lung SCC and provide a potential therapeutic strategy for lung SCC patients with TRA2B-DNAH5 fusion.

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, ARID2knockdown significantly promotes cell proliferation in human and mice lung cancer cells. Through integrative analyses of ChIP-Seq and RNA-Seq data, we find that Hspa1ais up-regulated by Arid2loss. Knockdown of Hspa1aspecifically 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.

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 associationsbetween 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.