Single cell and bulk RNA sequencing identifies tumor microenvironment subtypes and chemoresistance-related IGF1+ cancer-associated fibroblast in gastric cancer.

BACKGROUND: The tumor microenvironment (TME) significantly influences prognosis and drug resistance in various tumors, yet its heterogeneity and the mechanisms affecting therapeutic response remain unclear in gastric cancer (GC). METHODS: The heterogenous TME were explored with single-cell RNA-sequencing (scRNA-seq) data of 50 primary GC samples. We then identified four GC TME subtypes with nonnegative matrix factorization (NMF) and constructed a pearson nearest-centroid classifier based on subtype-specific upregulated genes. Genomic features and clinical significance of four subtypes were comprehensively evaluated. We reclustered fibroblasts to identify cancer-associated fibroblast (CAF) subtype associated with poor clinical outcomes. RT-qPCR and double immunofluorescence staining were applied to validate the findings. Cellchat analysis elucidated potential molecular mechanisms of the CAF subtype in GC disease progression and chemotherapy resistance. FINDINGS: The GC TME exhibited high heterogeneity, influencing chemo-sensitivity. Four TME-based subtypes predicting response to immunotherapy and chemotherapy were identified and validated in 1406 GC patients. Among which, ISG1 subtype displayed higher fibroblasts infiltration and heightened oncogenic pathways, and inferior response to chemotherapy with unfavorable prognosis. Microsatellite instability-high (MSI-H) GCs within four TME subtypes showed immunological heterogeneity. We then reported an IGF1-overexpressing CAF was associated with chemo-resistance and GC recurrence. Cell communication analysis revealed IGF1+ CAF may induce drug-resistant phenotypes in tumor cells through IGF1-α6ß4 integrin ligand-receptor binding and activation of EMT biological process. INTERPRETATION: We identified four TME-based subtypes with different clinical outcomes and IGF1+ CAFs contributing to poor clinical outcomes in GC, which might provide guidance for individualized treatment and facilitate the development of novel therapeutic targets.

Exploring Circular RNA Profile and Expression in Extracellular Vesicles.

Extracellular vesicles (EVs) are small vesicles secreted by various cell types and are enriched in multiple body fluids. EVs containing RNA have the potential to modulate biological processes and are being investigated for their diagnostic and therapeutic applications. Circular RNAs (circRNAs), generated through back-splicing of exons, are enriched in EVs. Given their unique characteristics and diverse functions, EV-circRNAs are important players in disease pathology. This chapter describes a workflow for investigating the expression profile of EV-circRNAs, which includes EVs separation, library preparation, and bioinformatics analysis. This workflow can aid the investigation of EV-circRNAs and their potential role in disease pathology.

Induction Toripalimab and Chemotherapy for Organ Preservation in Locally Advanced Laryngeal and Hypopharyngeal Cancer: A Single-Arm Phase II Clinical Trial.

PURPOSE: The aim of this study was to assess the efficacy, toxicities, and potential role of larynx preservation of induction chemotherapy combined with programmed cell death protein 1 (PD-1) inhibitor in locally advanced laryngeal and hypopharyngeal cancer. PATIENTS AND METHODS: This is a single-arm phase II study. Patients with histopathologically confirmed, resectable locally advanced laryngeal/hypopharyngeal squamous cell carcinoma and Eastern Cooperative Oncology Group Performance Status 0-1 were eligible. Three cycles of induction chemotherapy (paclitaxel 175 mg/m2 d1, cisplatin 25 mg/m2 d1-3) combined with PD-1 inhibitor (toripalimab 240 mg d0) were administered. Response assessment was performed after induction chemoimmunotherapy using RECIST 1.1 criteria. Patients with a complete/partial response of the primary tumor received concurrent chemoradiation, followed by maintenance therapy of toripalimab. Otherwise, patients were referred to surgery, followed by adjuvant (chemo) radiation and maintenance therapy of toripalimab. The primary endpoint is a larynx preservation rate at 3 months postradiation. RESULTS: Twenty-seven patients were enrolled. Most cases exhibited stage IV disease (81.5%), with T4 representing 37.0%. Five patients underwent pretreatment tracheostomy because of impaired larynx function. Overall response rate of induction chemoimmunotherapy was 85.2%. At 3 months postradiation, the larynx preservation rate was 88.9%. With a median follow-up of 18.7 months, the 1-year overall survival rate, progression-free survival rate, and larynx preservation rate were 84.7%, 77.6%, and 88.7%, respectively. When excluding those with pretreatment tracheostomy, the 1-year larynx preservation rate was 95.5%. Exploratory analysis revealed that relapse correlated with enrichment of RNA signature of hypoxia and M2 macrophage-associated genes. CONCLUSIONS: Induction toripalimab combined with chemotherapy provided encouraging activity, promising larynx preservation rate and acceptable toxicity in this cohort of extensively locally advanced laryngeal and hypopharyngeal cancer.

A liquid biopsy signature of circulating extracellular vesicles-derived RNAs predicts response to first line chemotherapy in patients with metastatic colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the most threatening tumors in the world, and chemotherapy remains dominant in the treatment of metastatic CRC (mCRC) patients. The purpose of this study was to develop a biomarker panel to predict the response of the first line chemotherapy in mCRC patients. METHODS: Totally 190 mCRC patients treated with FOLFOX or XEOLX chemotherapy in 3 different institutions were included. We extracted the plasma extracellular vesicle (EV) RNA, performed RNA sequencing, constructed a model and generated a signature through shrinking the number of variables by the random forest algorithm and the least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort (n = 80). We validated it in an internal validation cohort (n = 62) and a prospective external validation cohort (n = 48). RESULTS: We established a signature consisted of 22 EV RNAs which could identify responders, and the area under the receiver operating characteristic curve (AUC) values was 0.986, 0.821, and 0.816 in the training, internal validation, and external validation cohort respectively. The signature could also identify the progression-free survival (PFS) and overall survival (OS). Besides, we constructed a 7-gene signature which could predict tumor response to first-line oxaliplatin-containing chemotherapy and simultaneously resistance to second-line irinotecan-containing chemotherapy. CONCLUSIONS: The study was first to develop a signature of EV-derived RNAs to predict the response of the first line chemotherapy in mCRC with high accuracy using a non-invasive approach, indicating that the signature could help to select the optimal regimen for mCRC patients.

A pyroptosis-related signature in colorectal cancer: exploring its prognostic value and immunological characteristics.

Background: The heterogeneity of colorectal cancer (CRC) is the main cause of the disparity of drug sensitivity and the variability of prognosis. Pyroptosis is closely associated with the development and prognosis of various tumors, including CRC. Dividing CRC into distinct subgroups based on pyroptosis is a worthwhile topic for improving the precision treatment and prognosis prediction of CRC. Methods: We classified patients into two clusters using the consensus clustering based on the pyroptosis-related genes (PRGs). Next, the prognostic signature was developed with LASSO regression analysis using the screened genes from differentially expressed genes (DEGs) by univariate and multivariate Cox analyses. According to the pyroptosis-related score (PR score) calculated with the signature, patients belonged to two groups with distinct prognosis. Moreover, we assessed the immune profile to explore the relationship between the signature and immunological characteristics. Two single cell sequencing databases were adopted for further exploration of tumor immune microenvironment (TME). In addition, we applied our own cohort and Drugbank to explore the correlation of the signature and clinical therapies. We also studied the expression of key genes by immunohistochemistry. Results: The signature performed well in predicting the prognosis of CRC as the high area under curve (AUC) value demonstrated. Patients with a higher PR score had poorer prognosis and higher expression of immune checkpoints but more abundant infiltration of immune cells. Combining with the indicator of therapeutic analysis, they might benefit more from immune checkpoint blockade (ICB) and neo-adjuvant chemoradiotherapy (nCRT). Conclusion: In conclusion, our study is based on genomics and transcriptomics to investigate the role of PRGs in CRC. We have established a prognostic signature and integrated single-cell data to study the relationship between the signature with the TME in CRC. Its clinical application in reliable prediction of prognosis and personalized treatment was validated by public and own sequencing cohort. It provided a new insight for the personalized treatment of CRC.

KLF5 Promotes Tumor Progression and Parp Inhibitor Resistance in Ovarian Cancer.

One major characteristic of tumor cells is the aberrant activation of epigenetic regulatory elements, which remodel the tumor transcriptome and ultimately promote cancer progression and drug resistance. However, the oncogenic functions and mechanisms of ovarian cancer (OC) remain elusive. Here, super-enhancer (SE) regulatory elements that are aberrantly activated in OC are identified and it is found that SEs drive the relative specific expression of the transcription factor KLF5 in OC patients and poly(ADP-ribose) polymerase inhibitor (PARPi)-resistant patients. KLF5 expression is associated with poor outcomes in OC patients and can drive tumor progression in vitro and in vivo. Mechanistically, KLF5 forms a transcriptional complex with EHF and ELF3 and binds to the promoter region of RAD51 to enhance its transcription, strengthening the homologous recombination repair (HRR) pathway. Notably, the combination of suberoylanilide hydroxamic acid (SAHA) and olaparib significantly inhibits tumor growth and metastasis of PARPi-resistant OC cells with high KLF5. In conclusion, it is discovered that SEs-driven KLF5 is a key regulatory factor in OC progression and PARPi resistance; and potential therapeutic strategies for OC patients with PARPi resistance and high KLF5 are identified.

Extracellular vesicles long RNA profiling identifies abundant mRNA, circRNA and lncRNA in human bile as potential biomarkers for cancer diagnosis.

Extracellular vesicles (EVs) are bilayered membrane vesicles produced by living cells and secreted into the extracellular matrix. Bile is a special body fluid that is secreted by the liver cells, and extracellular vesicles long RNAs (exLRs) have not been explored in bile. In this study, exLR sequencing (exLR-seq) was performed on 19 bile samples from patients with malignant cancer or patients with biliary stones. A total of 8649 mRNAs, 13 823 circRNAs and 1105 lncRNAs were detected. The KEGG pathway analysis revealed that differentially expressed exLRs were enriched in mTOR and AMPK signaling pathway. We identified five mRNAs (EID2, LLPH, ATP6V0A2, RRP9 and MTRNR2L10), three lncRNAs (AC015922.2, AL135905.1 and LINC00921) and six circRNAs (circASH1L, circATP9A, circCLIP1, circRNF138, circTIMMDC1 and circANKRD12) were enriched in bile EV samples with cancer, and these exLRs may be potential markers used to distinguish malignant cancers from benign biliary diseases. Moreover, the tissue/cellular source components of EVs were analyzed using the EV-origin algorithm. The absolute abundance of CD4_naive and Th1 cell source in bile EVs from cancer patients were significantly increased. In summary, our study presented abundant exLRs in human bile EVs and provides some basis for the selection of tumor diagnostic markers.

Genomic and transcriptional characterization of early esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a highly heterogeneous cancer that lacks comprehensive understanding and effective treatment. Although multi-omics study has revealed features and underlying drivers of advanced ESCC, research on molecular characteristics of the early stage ESCC is quite limited. MATERIALS AND METHODS: We presented characteristics of genomics and transcriptomics in 10 matched pairs of tumor and normal tissues of early ESCC patients in the China region. RESULTS: We identified the specific patterns of cancer gene mutations and copy number variations. We also found a dramatic change in the transcriptome, with more than 4,000 genes upregulated in cancer. Among them, more than one-third of HOX family genes were specifically and highly expressed in early ESCC samples of China and validated by RT-qPCR. Gene regulation network analysis indicated that alteration of Hox family genes promoted the proliferation and metabolism remodeling of early ESCC. CONCLUSIONS: We characterized the genomic and transcriptomic landscape of 10 paired normal adjacent and early ESCC tissues in the China region, and provided a new perspective to understand the development of ESCC and insight into potential prevention and diagnostic targets for the management of early ESCC in China.

Low level of ARID1A contributes to adaptive immune resistance and sensitizes triple-negative breast cancer to immune checkpoint inhibitors.

BACKGROUND: Immune checkpoint inhibitors (ICIs) shed new light on triple-negative breast cancer (TNBC), but only a minority of patients demonstrate response. Therefore, adaptive immune resistance (AIR) needs to be further defined to guide the development of ICI regimens. METHODS: Databases, including The Cancer Genome Atlas, Gene Ontology Resource, University of California Santa Cruz Genome Browser, and Pubmed, were used to screen epigenetic modulators, regulators for CD8+ T cells, and transcriptional regulators of programmed cell death-ligand 1 (PD-L1). Human peripheral blood mononuclear cell (Hu-PBMC) reconstruction mice were adopted for xenograft transplantation. Tumor specimens from a TNBC cohort and the clinical trial CTR20191353 were retrospectively analyzed. RNA-sequencing, Western blotting, qPCR and immunohistochemistry were used to assess gene expression. Coculture assays were performed to evaluate the regulation of TNBC cells on T cells. Chromatin immunoprecipitation and transposase-accessible chromatin sequencing were used to determine chromatin-binding and accessibility. RESULTS: The epigenetic modulator AT-rich interaction domain 1A (ARID1A) gene demonstrated the highest expression association with AIR relative to other epigenetic modulators in TNBC patients. Low ARID1A expression in TNBC, causing an immunosuppressive microenvironment, promoted AIR and inhibited CD8+ T cell infiltration and activity through upregulating PD-L1. However, ARID1A did not directly regulate PD-L1 expression. We found that ARID1A directly bound the promoter of nucleophosmin 1 (NPM1) and that low ARID1A expression increased NPM1 chromatin accessibility as well as gene expression, further activating PD-L1 transcription. In Hu-PBMC mice, atezolizumab demonstrated the potential to reverse ARID1A deficiency-induced AIR in TNBC by reducing tumor malignancy and activating anti-tumor immunity. In CTR20191353, ARID1A-low patients derived more benefit from pucotenlimab compared to ARID1A-high patients. CONCLUSIONS: In AIR epigenetics, low ARID1A expression in TNBC contributed to AIR via the ARID1A/NPM1/PD-L1 axis, leading to poor outcome but sensitivity to ICI treatment.

Aldolase A Accelerates Cancer Progression by Modulating mRNA Translation and Protein Biosynthesis via Noncanonical Mechanisms.

Aldolase A (ALDOA), a crucial glycolytic enzyme, is often aberrantly expressed in various types of cancer. Although ALDOA has been reported to play additional roles beyond its conventional enzymatic role, its nonmetabolic function and underlying mechanism in cancer progression remain elusive. Here, it is shown that ALDOA promotes liver cancer growth and metastasis by accelerating mRNA translation independent of its catalytic activity. Mechanistically, ALDOA interacted with insulin- like growth factor 2 mRNA-binding protein 1 (IGF2BP1) to facilitate its binding to m6 A-modified eIF4G mRNA, thereby increasing eIF4G protein levels and subsequently enhancing overall protein biosynthesis in cells. Importantly, administration of GalNAc-conjugated siRNA targeting ALDOA effectively slows the tumor growth of orthotopic xenografts. Collectively, these findings uncover a previously unappreciated nonmetabolic function of ALDOA in modulating mRNA translation and highlight the potential of specifically targeting ALDOA as a prospective therapeutic strategy in liver cancer.

Enhanced BCAT1 activity and BCAA metabolism promotes RhoC activity in cancer progression.

Increased expression of branched-chain amino acid transaminase 1 or 2 (BCAT1 and BCAT2) has been associated with aggressive phenotypes of different cancers. Here we identify a gain of function of BCAT1 glutamic acid to alanine mutation at codon 61 (BCAT1E61A) enriched around 2.8% in clinical gastric cancer samples. We found that BCAT1E61A confers higher enzymatic activity to boost branched-chain amino acid (BCAA) catabolism, accelerate cell growth and motility and contribute to tumor development. BCAT1 directly interacts with RhoC, leading to elevation of RhoC activity. Notably, the BCAA-derived metabolite, branched-chain α-keto acid directly binds to the small GTPase protein RhoC and promotes its activity. BCAT1 knockout-suppressed cell motility could be rescued by expressing BCAT1E61A or adding branched-chain α-keto acid. We also identified that candesartan acts as an inhibitor of BCAT1E61A, thus repressing RhoC activity and cancer cell motility in vitro and preventing peritoneal metastasis in vivo. Our study reveals a link between BCAA metabolism and cell motility and proliferation through regulating RhoC activation, with potential therapeutic implications for cancers.

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases.

Chronic liver diseases usually developed through stepwise pathological transitions under the persistent risk factors. The molecular changes during liver transitions are pivotal to improve liver diagnostics and therapeutics yet still remain elusive. Cumulative large-scale liver transcriptomic studies have been revealing molecular landscape of various liver conditions at bulk and single-cell resolution, however, neither single experiment nor databases enabled thorough investigations of transcriptomic dynamics along the progression of liver diseases. Here we establish GepLiver, a longitudinal and multidimensional liver expression atlas integrating expression profiles of 2469 human bulk tissues, 492 mouse samples, 409,775 single cells from 347 human samples and 27 liver cell lines spanning 16 liver phenotypes with uniformed processing and annotating methods. Using GepLiver, we have demonstrated dynamic changes of gene expression, cell abundance and crosstalk harboring meaningful biological associations. GepLiver can be applied to explore the evolving expression patterns and transcriptomic features for genes and cell types respectively among liver phenotypes, assisting the investigation of liver transcriptomic dynamics and informing biomarkers and targets for liver diseases.

Plasma extracellular vesicle transcriptomics identifies CD160 for predicting immunochemotherapy efficacy in lung cancer.

Better biomarkers are needed to improve the efficacy of immune checkpoint inhibitors in lung adenocarcinoma (LUAD) treatment. We investigated the plasma extracellular vesicle (EV)-derived long RNAs (exLRs) in unresectable/advanced LUAD to explore biomarkers for immunochemotherapy. Seventy-four LUAD patients without targetable mutations receiving first-line anti-programmed cell death 1 (PD-1) immunochemotherapy were enrolled. Their exLRs were profiled through plasma EV transcriptome sequencing. Biomarkers were analyzed against response rate and survival using pre- and post-treatment samples in the retrospective cohort (n = 36) and prospective cohort (n = 38). The results showed that LUAD patients demonstrated a distinct exLR profile from the healthy individuals (n = 56), and T-cell activation-related pathways were enriched in responders. Among T-cell activation exLRs, CD160 exhibited a strong correlation with survival. In the retrospective cohort, the high baseline EV-derived CD160 level correlated with prolonged progression-free survival (PFS) (P < 0.001) and overall survival (OS) (P = 0.005), with an area under the curve (AUC) of 0.784 for differentiating responders from non-responders. In the prospective cohort, the CD160-high patients also showed prolonged PFS (P = 0.003) and OS (P = 0.014) and a promising AUC of 0.648. The predictive value of CD160 expression was validated by real-time quantitative PCR. We also identified the dynamics of EV-derived CD160 for monitoring therapeutic response. The elevated baseline CD160 reflected a higher abundance of circulating NK cells and CD8+ -naïve T cells, suggesting more active host immunity. In addition, increased CD160 levels of tumors also correlated with a favorable prognosis in LUAD patients. Together, plasma EV transcriptome analysis revealed the role of the baseline CD160 level and early post-treatment CD160 dynamics for predicting the response to anti-PD-1 immunochemotherapy in LUAD patients.

A NOTCH1 Mutation Found in a Newly Established Ovarian Cancer Cell Line (FDOVL) Promotes Lymph Node Metastasis in Ovarian Cancer.

Peritoneal implantation and lymph node metastasis have different driving mechanisms in ovarian cancer. Elucidating the underlying mechanism of lymph node metastasis is important for treatment outcomes. A new cell line, FDOVL, was established from a metastatic lymph node of a patient with primary platinum-resistant ovarian cancer and was then characterized. The effect of NOTCH1-p.C702fs mutation and NOTCH1 inhibitor on migration was evaluated in vitro and in vivo. Ten paired primary sites and metastatic lymph nodes were analyzed by RNA sequencing. The FDOVL cell line with serious karyotype abnormalities could be stably passaged and could be used to generated xenografts. NOTCH1-p.C702fs mutation was found exclusively in the FDOVL cell line and the metastatic lymph node. The mutation promoted migration and invasion in cell and animal models, and these effects were markedly repressed by the NOTCH inhibitor LY3039478. RNA sequencing confirmed CSF3 as the downstream effector of NOTCH1 mutation. Furthermore, the mutation was significantly more common in metastatic lymph nodes than in other peritoneal metastases in 10 paired samples (60% vs. 20%). The study revealed that NOTCH1 mutation is probably a driver of lymph node metastasis in ovarian cancer, which offers new ideas for the treatment of ovarian cancer lymph node metastasis with NOTCH inhibitors.

circTMEM181 upregulates ARHGAP29 to inhibit hepatocellular carcinoma migration and invasion by sponging miR-519a-5p.

AIM: Circular RNAs (circRNAs) are a novel class of noncoding RNAs and are conserved in various species. Although numerous circRNAs have been identified, their role in cancer remains unclear. METHODS: The expression of circTMEM181 in 90 paired human hepatocellular carcinoma (HCC) and adjacent nontumor tissues were detected using quantitative reverse transcription-polymerase chain reaction. Transwell assay was performed for functional analysis of HCC cell migration and invasion. Luciferase reporter assay was used to verify the combination of circTMEM181 and miR-519a-5p. RESULTS: In this study, we identified a novel circRNA, named circTMEM181, was downregulated in HCC tissues. Decreased expression of circTMEM181 was associated with shorter overall survival of patients with HCC. CircTMEM181 overexpression reduced HCC cell migration and invasion abilities, while circTMEM181 knockdown increased cell motility. Mechanically, circTMEM181 could directly bind to miR-519a-5p and subsequently upregulate ARHGAP29 protein expression. CONCLUSION: These data provide the first evidence of clinical significance and function of circTMEM181, and suggest the circTMEM181/miR-519a-5p/ARHGAP29 axis in HCC development.

Transcriptomic characterization and construction of M2 macrophage-related prognostic and immunotherapeutic signature in ovarian metastasis of gastric cancer.

BACKGROUND: Ovarian metastasis (OM) poses a major threat to the outcome of gastric cancer (GC) patients. Recently, immunotherapy emerged as a novel promising therapeutic strategy to treat late-stage GC, whereas its efficacy is influenced by tumor immune microenvironment (TIME). M2 macrophage, a key subset within TIME, plays dual immunosuppressive and pro-tumorigenic roles in cancer progression and is recognized as a potential therapeutic target. However, molecular mechanisms underlying OM remain elusive and the TIME-related prognostic and immunotherapeutic index for these patients is yet to establish. METHODS: Differential expressed genes (DEGs) between paired normal mucosa, primary GC and OM of patients from Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 6) were identified by transcriptome sequencing, followed by the functional annotation of enriched hallmark pathways of DEGs between them. CIBERSORT was used to profile the relative expression level of 22 immune cell subsets in normal tissues, primary and metastatic tumors, followed by weighted gene coexpression network analysis (WGCNA) uncovering immune cell-correlated gene sets. The intersected genes between DEGs and M2 macrophage-related genes were processed by least absolute shrinkage and selection operator (LASSO) regression analysis to construct a predictive signature, M2GO, which was further validated by training set and test set of The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD), GSE62254 and GSE84437 cohorts. GC patients were divided into M2GO-high and -low subgroup according to the optimal cutoff value of the M2GO score. Furthermore, the clinical, molecular and immune features between M2GO-high and -low subgroups were analyzed. Clinical cohorts of immunotherapy were used to validate the predictive value of M2GO in regard to immunotherapy effectiveness. RESULTS: Transcriptomic sequencing and follow-up analyses of triple-matched normal tissues, primary and ovarian metastatic tumors identified distinctive sets of DEGs and enriched immune-, cancer- and metastasis-related pathways between them. Of note, M2 macrophage, a major immunosuppressive and pro-tumorigenic component within TIME, was significantly up-regulated in OMs. WGCNA and LASSO regression were applied to establish a novel OM- and M2 macrophage-related predictive signature, M2GO, based on M2 macrophage-related prognostic genes including GJA1, MAGED1 and SERPINE1. M2GO served as an independent prognostic factor of GC patients. Comprehensive molecular and immune characterization of M2GO-based subgroups uncovered their distinctive features in terms of enriched functional pathways, tumor mutation burden, key immune checkpoints, major regulators of natural immune cGAS-STING pathway, infiltrated subsets of immune cells and tumor immune exclusion/dysfunction (TIDE) score. Notably, the M2GO score was significantly lower in responsive group than non-responsive group (P < 0.05) in clinical cohort of metastatic GC patients undergoing immunotherapy. CONCLUSION: Transcriptomic characterization of paired normal mucosae, primary and ovarian metastatic tumors revealed their unique molecular and immune features. Follow-up analyses established a novel OM- and M2 macrophage-related signature, M2GO, which served as a promising prognostic and immunotherapeutic biomarker to distinguish the clinical outcome, molecular and immune features of GC patients and predict their differential responses to immunotherapy.

Superenhancer drives a tumor-specific splicing variant of MARCO to promote triple-negative breast cancer progression.

The transcription variation, leading to various forms of transcripts and protein diversity, remains largely unexplored in triple-negative breast cancers (TNBCs). Here, we presented a comprehensive analysis of RNA splicing in breast cancer to illustrate the biological function and clinical implications of tumor-specific transcripts (TSTs) arising from these splicing junctions. Aberrant RNA splicing or TSTs were frequently harbored in TNBC and were correlated with a poor outcome. We discovered a tumor-specific splicing variant of macrophage receptor with collagenous structure-TST (MARCO-TST), which was distinguished from myeloid cell-specific wild-type MARCO. MARCO-TST expression was associated with poor outcomes in TNBC patients and could promote tumor progression in vitro and in vivo. Mechanically, MARCO-TST interacted with PLOD2 and enhanced the stability of HIF-1α, which resulted in the metabolic dysregulation of TNBC to form a hypoxic tumor microenvironment. MARCO-TST was initiated from a de novo alternative transcription initiation site that was activated by a superenhancer. Tumors with MARCO-TST expression conferred greater sensitivity to bromodomain and extraterminal protein inhibitors. This treatment strategy was further validated in patient-derived organoids. In conclusion, our results revealed the transcription variation landscape of TNBC, highlighting MARCO-TST as a crucial oncogenic transcript and therapeutic target.

Integrated proteogenomic characterization of medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is a rare neuroendocrine malignancy derived from parafollicular cells (C cells) of the thyroid. Here we presented a comprehensive multi-omics landscape of 102 MTCs through whole-exome sequencing, RNA sequencing, DNA methylation array, proteomic and phosphoproteomic profiling. Integrated analyses identified BRAF and NF1 as novel driver genes in addition to the well-characterized RET and RAS proto-oncogenes. Proteome-based stratification of MTCs revealed three molecularly heterogeneous subtypes named as: (1) Metabolic, (2) Basal and (3) Mesenchymal, which are distinct in genetic drivers, epigenetic modification profiles, clinicopathologic factors and clinical outcomes. Furthermore, we explored putative therapeutic targets of each proteomic subtype, and found that two tenascin family members TNC/TNXB might serve as potential prognostic biomarkers for MTC. Collectively, our study expands the knowledge of MTC biology and therapeutic vulnerabilities, which may serve as an important resource for future investigation on this malignancy.

Long noncoding RNA DLGAP1-AS2 promotes tumorigenesis and metastasis by regulating the Trim21/ELOA/LHPP axis in colorectal cancer.

BACKGROUND: Long noncoding RNAs (lncRNAs) have driven research focused on their effects as oncogenes or tumor suppressors involved in carcinogenesis. However, the functions and mechanisms of most lncRNAs in colorectal cancer (CRC) remain unclear. METHODS: The expression of DLGAP1-AS2 was assessed by quantitative RT-PCR in multiple CRC cohorts. The impacts of DLGAP1-AS2 on CRC growth and metastasis were evaluated by a series of in vitro and in vivo assays. Furthermore, the underlying mechanism of DLGAP1-AS2 in CRC was revealed by RNA pull down, RNA immunoprecipitation, RNA sequencing, luciferase assays, chromatin immunoprecipitation, and rescue experiments. RESULTS: We discovered that DLGAP1-AS2 promoted CRC tumorigenesis and metastasis by physically interacting with Elongin A (ELOA) and inhibiting its protein stability by promoting tripartite motif containing 21 (Trim21)-mediated ubiquitination modification and degradation of ELOA. In particular, we revealed that DLGAP1-AS2 decreases phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) expression by inhibiting ELOA-mediated transcriptional activating of LHPP and thus blocking LHPP-dependent suppression of the AKT signaling pathway. In addition, we also demonstrated that DLGAP1-AS2 was bound and stabilized by cleavage and polyadenylation specificity factor (CPSF2) and cleavage stimulation factor (CSTF3). CONCLUSIONS: The discovery of DLGAP1-AS2, a promising prognostic biomarker, reveals a new dimension into the molecular pathogenesis of CRC and provides a prospective treatment target for this disease.

Plasma Extracellular Vesicle Long RNA in Diagnosis and Prediction in Small Cell Lung Cancer.

(1) Introduction: The aim of this study was to identify the plasma extracellular vesicle (EV)-specific transcriptional profile in small-cell lung cancer (SCLC) and to explore the application value of plasma EV long RNA (exLR) in SCLC treatment prediction and diagnosis. (2) Methods: Plasma samples were collected from 57 SCLC treatment-naive patients, 104 non-small-cell lung cancer (NSCLC) patients and 59 healthy participants. The SCLC patients were divided into chemo-sensitive and chemo-refractory groups based on the therapeutic effects. The exLR profiles of the plasma samples were analyzed by high-throughput sequencing. Bioinformatics approaches were used to investigate the differentially expressed exLRs and their biofunctions. Finally, a t-signature was constructed using logistic regression for SCLC treatment prediction and diagnosis. (3) Results: We obtained 220 plasma exLRs profiles in all the participants. Totals of 5787 and 1207 differentially expressed exLRs were identified between SCLC/healthy controls, between the chemo-sensitive/chemo-refractory groups, respectively. Furthermore, we constructed a t-signature that comprised ten exLRs, including EPCAM, CCNE2, CDC6, KRT8, LAMB1, CALB2, STMN1, UCHL1, HOXB7 and CDCA7, for SCLC treatment prediction and diagnosis. The exLR t-score effectively distinguished the chemo-sensitive from the chemo-refractory group (p = 9.268 × 10-9) with an area under the receiver operating characteristic curve (AUC) of 0.9091 (95% CI: 0.837 to 0.9811) and distinguished SCLC from healthy controls (AUC: 0.9643; 95% CI: 0.9256-1) and NSCLC (AUC: 0.721; 95% CI: 0.6384-0.8036). (4) Conclusions: This study firstly characterized the plasma exLR profiles of SCLC patients and verified the feasibility and value of identifying biomarkers based on exLR profiles in SCLC diagnosis and treatment prediction.