Clinicopathological factors predict residual lymph node metastasis in locally advanced rectal cancer with ypT0-2 after neoadjuvant chemoradiotherapy.

PURPOSE: Residual lymph node metastases (RLNM) remained a great concern in the implementation of organ-preserving strategies and led to poor prognosis in locally advanced rectal cancer (LARC). In this study, we aimed to identify the clinicopathological factors correlated with RLNM in LARC patients with ypT0-2 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 417 patients histologically diagnosed middle-low LARC after NCRT and total mesorectal excision (TME), whose pathological staging was ypT0-2. All patients received pelvic magnetic resonance imaging (MRI) before NCRT. The radiation doses were 50-50.6 Gy for the planning gross tumor volume and 41.8-45 Gy for the planning target volume, respectively. A nomogram for predicting RLNM was constructed using a binary logistic regression. Nomogram performance was assessed by receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC). RESULTS: After surgery, 191 patients (45.8%) were ypT0, 43 patients (10.3%) were ypT1 and 183 patients (43.9%) were ypT2, and a total of 49 patients (11.8%) were found the presence of RLNM. Multivariable analyses identified MRI-defined mesorectal fascia (MRF)-positive, high-grade histopathology at biopsy, advanced ypT-category, and the presence of perineural invasion (PNI) as the predictive factors. The nomogram, incorporating all these predictors, showed good discrimination and calibration efficacy, with the areas under the ROC curve of 0.690 (95% CI: 0.610-0.771). Both DCA and CIC demonstrated that this nomogram has good clinical usefulness. CONCLUSION: The nomogram model can predict RLNM in patients with ypT0-2 tumors. It can help select suitable patients for performing organ-preserving strategies after NCRT.

Effect of oxygen-containing functional group contents on sorption of lead ions by acrylate-functionalized hydrochar.

The surface functional groups of hydrochar are crucial to its surface properties, and their contents are strongly positively correlated with the adsorption performance. In this study, acrylate-functionalized hydrochar (AHC) with varying contents of O-containing functional groups (OFGs) was synthesized via hydrothermal carbonization (HTC) of bamboo, acrylic acid and an initiator, and then deprotonated with NaOH. The AHCs were analyzed by various characterization techniques. During HTC, the higher amount of acrylic acid added led to higher carbon, oxygen and carboxyl contents, and to the larger specific surface area and pore volume of AHC. The adsorption kinetics, isotherms, thermodynamic, ionic strength and pH effects of Pb(II) on AHC were studied. Adsorption isotherms and kinetics obeyed Langmuir and pseudo-second-order models, respectively, indicating adsorption is monolayer chemical process. The adsorptive ability was well linearly related to the OFG contents of AHC. When acrylic acid was added to 25 mL during HTC, the adsorbing ability of AHC over Pb(II) reached 193.90 mg g-1. Hence, direct HTC of acrylic acid, biomass and an initiator can prepare hydrochar with controllable OFG contents, which is a prospective adsorbent for treating metal cations.

Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.

Hyperactive ribosome biogenesis (RiboSis) fuels unrestricted cell proliferation, whereas genomic hallmarks and therapeutic targets of RiboSis in cancers remain elusive, and efficient approaches to quantify RiboSis activity are still limited. Here, we have established an in silico approach to conveniently score RiboSis activity based on individual transcriptome data. By employing this novel approach and RNA-seq data of 14 645 samples from TCGA/GTEx dataset and 917 294 single-cell expression profiles across 13 cancer types, we observed the elevated activity of RiboSis in malignant cells of various human cancers, and high risk of severe outcomes in patients with high RiboSis activity. Our mining of pan-cancer multi-omics data characterized numerous molecular alterations of RiboSis, and unveiled the predominant somatic alteration in RiboSis genes was copy number variation. A total of 128 RiboSis genes, including EXOSC4, BOP1, RPLP0P6 and UTP23, were identified as potential therapeutic targets. Interestingly, we observed that the activity of RiboSis was associated with TP53 mutations, and hyperactive RiboSis was associated with poor outcomes in lung cancer patients without TP53 mutations, highlighting the importance of considering TP53 mutations during therapy by impairing RiboSis. Moreover, we predicted 23 compounds, including methotrexate and CX-5461, associated with the expression signature of RiboSis genes. The current study generates a comprehensive blueprint of molecular alterations in RiboSis genes across cancers, which provides a valuable resource for RiboSis-based anti-tumor therapy.

The ypT may better predict the efficacy of neoadjuvant chemoradiotherapy than tumor regression grade in locally advanced rectal cancer patients diagnosed ypT1-4N0.

PURPOSE: This study aimed to assess the impact of ypT stage and tumor regression grade (TRG) on the long-term prognosis of patients with locally advanced rectal cancer (LARC) stage ypT1-4N0 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 585 patients with histologically diagnosed middle-low LARC (cT3-4 or cN + by pelvic MRI) from 2014 to 2019. All patients underwent NCRT, followed by total mesorectal excision. Disease-free survival (DFS) rates were compared among patients with different ypT stages and TRGs by Kaplan-Meier survival analysis. The chi-square test was used to analyze the relationship between clinicopathological or therapeutic factors and ypT stage. RESULTS: The median follow-up was 35.8 months (range 2.8-71.8 months). The 3-year DFS was 79.5%. A better 3-year DFS was achieved in patients with a pathologic complete response (94.0% vs. 74.3%, p < 0.001) and those in the ypT0-2 (86.5% vs. 66.6%, p < 0.001), ypN0 (85.0% vs. 60.2%, p < 0.001), and TRG0 + 1 (83.1% vs. 73.0%, p = 0.004) subgroups. A total of 309 patients (52.8%) achieved stage ypT1-4N0 after surgery. Among these patients, the ypT1-2N0 subgroup achieved a significantly higher 3-year DFS than the ypT3-4N0 subgroup (85.4% vs. 72.8%, p = 0.018); in contrast, the 3-year DFS did not significantly differ between the TRG1 and TRG2 + 3 subgroups (79.9% vs. 81.1%, p = 0.833). In the ypT1-2N0 or ypT3-4N0 subgroup, different TRG had no significant effect on failure patterns. CONCLUSIONS: For LARC patients with a ypT1-4N0 status after NCRT, ypT stage may be a more effective predictor of long-term prognosis than TRG.

KRAS status predicted by pretreatment MRI radiomics was associated with lung metastasis in locally advanced rectal cancer patients.

BACKGROUND: Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explore the association between the KRAS status or model predictions and lung metastasis. METHODS: In this retrospective multicentre study, LARC patients from two institutions between January 2012 and January 2019 were randomly divided into training and testing cohorts. Least absolute shrinkage and selection operator (LASSO) regression and the support vector machine (SVM) classifier were utilized to select significant radiomic features and establish a prediction model, which was validated by radiomic score distribution and decision curve analysis. The association between the model stratification and lung metastasis was investigated by Cox regression and Kaplan‒Meier survival analysis; the results were compared by the log-rank test. RESULTS: Overall, 103 patients were enrolled (73 and 30 in the training and testing cohorts, respectively). The median follow-up was 38.1 months (interquartile range: 26.9, 49.4). The radiomic model had an area under the curve (AUC) of 0.983 in the training cohort and 0.814 in the testing cohort. Using a cut-off of 0.679 defined by the receiver operating characteristic (ROC) curve, patients with a high radiomic score (RS) had a higher risk for lung metastasis (HR 3.565, 95% CI 1.337, 9.505, p = 0.011), showing similar predictive performances for the mutant and wild-type KRAS groups (HR 3.225, 95% CI 1.249, 8.323, p = 0.016, IDI: 1.08%, p = 0.687; NRI 2.23%, p = 0.766). CONCLUSIONS: We established and validated a radiomic model for predicting KRAS status in LARC. Patients with high RS experienced more lung metastases. The model could noninvasively detect KRAS status and may help individualize clinical decision-making.

Spatial transcriptomics delineates molecular features and cellular plasticity in lung adenocarcinoma progression.

Indolent (lepidic) and aggressive (micropapillary, solid, and poorly differentiated acinar) histologic subtypes often coexist within a tumor tissue of lung adenocarcinoma (LUAD), but the molecular features associated with different subtypes and their transitions remain elusive. Here, we combine spatial transcriptomics and multiplex immunohistochemistry to elucidate molecular characteristics and cellular plasticity of distinct histologic subtypes of LUAD. We delineate transcriptional reprogramming and dynamic cell signaling that determine subtype progression, especially hypoxia-induced regulatory network. Different histologic subtypes exhibit heterogeneity in dedifferentiation states. Additionally, our results show that macrophages are the most abundant cell type in LUAD, and identify different tumor-associated macrophage subpopulations that are unique to each histologic subtype, which might contribute to an immunosuppressive microenvironment. Our results provide a systematic landscape of molecular profiles that drive LUAD subtype progression, and demonstrate potentially novel therapeutic strategies and targets for invasive lung adenocarcinoma.

Comparative transcriptome characterization of esophageal squamous cell carcinoma and adenocarcinoma.

Background: Esophageal cancers are primarily categorized as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While various (epi) genomic alterations associated with tumor development in ESCC and EAC have been documented, a comprehensive comparison of the transcriptomes in these two cancer subtypes remains lacking. Methods: We collected 551 gene expression profiles from publicly available sources, including normal, ESCC, and EAC tissues or cell lines. Subsequently, we conducted a systematic analysis to compare the transcriptomes of these samples at various levels, including gene expression, promoter activity, alternative splicing (AS), alternative polyadenylation (APA), and gene fusion. Results: Seven distinct cluster gene expression patterns were identified among the differentially expressed genes in normal, ESCC, and EAC tissues. These patterns were enriched in the PI3K-Akt signaling pathway and the activation of extracellular matrix organization and exhibited repression of epidermal development. Notably, we observed additional genes or unique expression levels enriched in these shared pathways and biological processes related to tumor development and immune activation. In addition to the differentially expressed genes, there was an enrichment of lncRNA co-expression networks and downregulation of promoter activity associated with the repression of epidermal development in both ESCC and EAC. This indicates a common feature between these two cancer subtypes. Furthermore, differential AS and APA patterns in ESCC and EAC appear to partially affect the expression of host genes associated with bacterial or viral infections in these subtypes. No gene fusions were observed between ESCC and EAC, thus highlighting the distinct molecular mechanisms underlying these two cancer subtypes. Conclusions: We conducted a comprehensive comparison of ESCC and EAC transcriptomes and uncovered shared and distinct transcriptomic signatures at multiple levels. These findings suggest that ESCC and EAC may exhibit common and unique mechanisms involved in tumorigenesis.

Gut microbiota-mediated nucleotide synthesis attenuates the response to neoadjuvant chemoradiotherapy in rectal cancer.

Preoperative neoadjuvant chemoradiotherapy (nCRT) is a standard treatment for locally advanced rectal cancer (LARC) patients, yet little is known about the mediators underlying the heterogeneous patient response. In this longitudinal study, we performed 16S rRNA sequencing on 353 fecal specimens and find reduced microbial diversity after nCRT. Multi-omics data integration reveals that Bacteroides vulgatus-mediated nucleotide biosynthesis associates with nCRT resistance in LARC patients, and nonresponsive tumors are characterized by the upregulation of genes related to DNA repair and nucleoside transport. Nucleosides supplementation or B. vulgatus gavage protects cancer cells from the 5-fluorouracil or irradiation treatment. An analysis of 2,205 serum samples from 735 patients suggests that uric acid is a potential prognosis marker for LARC patients receiving nCRT. Our data unravel the role of intestinal microbiota-mediated nucleotide biosynthesis in the response of rectal tumors to nCRT, and highlight the importance of deciphering the cross-talk between cancer cells and gut microorganisms during cancer therapies.

MRI-based radiomics to predict neoadjuvant chemoradiotherapy outcomes in locally advanced rectal cancer: A multicenter study.

Background and purpose: Predicting tumour response would be useful for selecting patients with locally advanced rectal cancer (LARC) for organ preservation strategies. We aimed to develop and validate a prediction model for T downstaging (ypT0-2) in LARC patients after neoadjuvant chemoradiotherapy and to identify those who may benefit from consolidation chemotherapy. Materials and methods: cT3-4 LARC patients at three tertiary medical centers from January 2012 to January 2019 were retrospectively included, while a prospective cohort was recruited from June 2021 to March 2022. Eight filter (principal component analysis, least absolute shrinkage and selection operator, partial least-squares discriminant analysis, random forest)-classifier (support vector machine, logistic regression) models were established to select radiomic features. A nomogram combining radiomics and significant clinical features was developed and validated by calibration curve and decision curve analysis. Interaction test was conducted to investigate the consolidation chemotherapy benefits. Results: A total of 634 patients were included (426 in training cohort, 174 in testing cohort and 34 in prospective cohort). A radiomic prediction model using partial least-squares discriminant analysis and a support vector machine showed the best performance (AUC: 0.832 [training]; 0.763 [testing]). A nomogram combining radiomics and clinical features showed significantly better prognostic performance (AUC: 0.842 [training]; 0.809 [testing]) than the radiomic model. The model was also tested in the prospective cohort with AUC 0.727. High-probability group (score > 81.82) may have potential benefits from ≥ 4 cycles consolidation chemotherapy (OR: 4.173, 95 % CI: 0.953-18.276, p = 0.058, pinteraction = 0.021). Conclusion: We identified and validated a model based on multicenter pre-treatment radiomics to predict ypT0-2 in cT3-4 LARC patients, which may facilitate individualised treatment decision-making for organ-preservation strategies and consolidation chemotherapy.

Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality.

Codon optimality has been demonstrated to be an important determinant of mRNA stability and expression levels in multiple model organisms and human cell lines. However, tissue-specific codon optimality has not been developed to investigate how codon optimality is usually perturbed by somatic synonymous mutations in human cancers. Here, we determined tissue-specific codon optimality in 29 human tissues based on mRNA expression data from the Genotype-Tissue Expression project. We found that optimal codons were associated with differentiation, whereas non-optimal codons were correlated with proliferation. Furthermore, codons biased toward differentiation displayed greater tissue specificity in codon optimality, and the tissue specificity of codon optimality was primarily present in amino acids with high degeneracy of the genetic code. By applying tissue-specific codon optimality to somatic synonymous mutations in 8532 tumor samples across 24 cancer types and to those in 416 normal cells across six human tissues, we found that synonymous mutations frequently increased optimal codons in tumor cells and cancer-related genes (e.g., genes involved in cell cycle). Furthermore, an elevated frequency of optimal codon gain was found to promote tumor cell proliferation in three cancer types characterized by DNA damage repair deficiency and could act as a prognostic biomarker for patients with triple-negative breast cancer. In summary, this study profiled tissue-specific codon optimality in human tissues, revealed alterations in codon optimality caused by synonymous mutations in human cancers, and highlighted the non-negligible role of optimal codon gain in tumorigenesis and therapeutics.

Transcriptomic signatures associated with autoimmune thyroiditis in papillary thyroid carcinoma and cancer immunotherapy-induced thyroid dysfunction.

Up to 20% of patients treated with anti-PD-1/PD-L1 inhibitors suffered from thyroid dysfunctions, yet the mediators associated with their occurrence remain unclear. The increasing coincidence of papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) and the high vulnerability of thyroid to immunotherapy motivated us to discover the similarities and their underlying transcriptomic basis. Clinical characteristics analysis of 468 PTC patients from two independent cohorts and meta-analysis of 22,155 PTC patients unveiled a strong negative association between HT and recurrence in PTC patients. Transcriptome analysis of both cohorts showed PTC patients with HT were enriched in macrophages, CD8+ and CD4+ cytotoxic T cells, which was further validated by single-cell transcriptome analysis of 17,438 cells from PTC patients, and CD8+ T cells were correlated with disease-free survival of PTC patients. In both cohorts and single-cell dataset, elevated expression of PD-1-related genes was observed in the HT group, and CD3D appeared to be a target for enhancing the activation of CD8+ T cells. Correlation analysis of 3,318 thyroid adverse events from 39,123 patients across 24 tumor types and molecular signatures demonstrated similar signatures associated with autoimmune thyroiditis in PTC and thyroid immune-related adverse events (irAEs), and several multi-omics signatures, including signatures of CD8A and CD8+ T cells, showed positive associations with the odds ratio of thyroid irAEs. Our results unveil shared molecular signatures underlying thyroid dysfunction between patients receiving immunotherapies and PTC patients suffering from HT, which may shed light on managing the adverse events during cancer immunotherapy.

MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer.

BACKGROUND: To analyse the performance of multicentre pre-treatment MRI-based radiomics (MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment modalities to predict complete response to neoadjuvant (chemo)radiotherapy in locally advanced rectal cancer (LARC). METHODS: Baseline MRI and clinical characteristics with neoadjuvant treatment modalities at four centres were collected. Decision tree, support vector machine and five-fold cross-validation were applied for two non-imaging and three radiomics-based models' development and validation. RESULTS: We finally included 674 patients. Pre-treatment CEA, T stage, and histologic grade were selected to generate two non-imaging models: C model (clinical baseline characteristics alone) and CT model (clinical baseline characteristics combining neoadjuvant treatment modalities). The prediction performance of both non-imaging models were poor. The MBR signatures comprising 30 selected radiomics features, the MBR signatures combining clinical baseline characteristics (CMBR), and the CMBR incorporating neoadjuvant treatment modalities (CTMBR) all showed good discrimination with mean AUCs of 0.7835, 0.7871 and 0.7916 in validation sets, respectively. The three radiomics-based models had insignificant discrimination in performance. CONCLUSIONS: The performance of the radiomics-based models were superior to the non-imaging models. MBR signatures seemed to reflect LARC's true nature more accurately than clinical parameters and helped identify patients who can undergo organ preservation strategies.

Comprehensive evaluation of computational methods for predicting cancer driver genes.

Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.

Corrigendum: Simultaneous Integrated Boost Intensity-Modulated Radiation Therapy Can Benefit the Locally Advanced Rectal Cancer Patients with Clinically Positive Lateral Pelvic Lymph Node.

[This corrects the article DOI: 10.3389/fonc.2020.627572.].

Genomic and epigenomic evolution of acquired resistance to combination therapy in esophageal squamous cell carcinoma.

BACKGROUNDTargeted arterial infusion of verapamil combined with chemotherapy (TVCC) is an effective clinical interventional therapy for esophageal squamous cell carcinoma (ESCC), but multidrug resistance (MDR) remains the major cause of relapse or poor prognosis, and the underlying molecular mechanisms of MDR, temporal intratumoral heterogeneity, and clonal evolutionary processes of resistance have not been determined.METHODSTo elucidate the roles of genetic and epigenetic alterations in the evolution of acquired resistance during therapies, we performed whole-exome sequencing on 16 serial specimens from 7 patients with ESCC at every cycle of therapeutic intervention from 3 groups, complete response, partial response, and progressive disease, and we performed whole-genome bisulfite sequencing for 3 of these 7 patients, 1 patient from each group.RESULTSPatients with progressive disease exhibited a substantially higher genomic and epigenomic temporal heterogeneity. Subclonal expansions driven by the beneficial new mutations were observed during combined therapies, which explained the emergence of MDR. Notably, SLC7A8 was identified as a potentially novel MDR gene, and functional assays demonstrated that mutant SLC7A8 promoted the resistance phenotypes of ESCC cell lines. Promoter methylation dynamics during treatments revealed 8 drug resistance protein-coding genes characterized by hypomethylation in promoter regions. Intriguingly, promoter hypomethylation of SLC8A3 and mutant SLC7A8 were enriched in an identical pathway, protein digestion and absorption, indicating a potentially novel MDR mechanism during treatments.CONCLUSIONOur integrated multiomics investigations revealed the dynamics of temporal genetic and epigenetic inter- and intratumoral heterogeneity, clonal evolutionary processes, and epigenomic changes, providing potential MDR therapeutic targets in treatment-resistant patients with ESCC during combined therapies.FUNDINGNational Natural Science Foundation of China, Science Foundation of Peking University Cancer Hospital, CAMS Innovation Fund for Medical Sciences, Major Program of Shenzhen Bay Laboratory, Guangdong Basic and Applied Basic Research Foundation, and the third round of public welfare development and reform pilot projects of Beijing Municipal Medical Research Institutes.

Effect of Simultaneous Integrated Boost Intensity Modulated Radiation Therapy (SIB-IMRT) and Non-Operative Strategy on Outcomes of Distal Rectal Cancer Patients with Clinically Positive Lateral Pelvic Lymph Node.

BACKGROUND: We aimed to analyze the effect of simultaneous integrated boost intensity modulated radiation therapy (SIB-IMRT) and non-operative treatment on the clinical outcomes of distal rectal cancer patients exhibiting clinically positive lateral pelvic lymph nodes (LPLNs). METHODS: We reviewed the medical records of patients diagnosed as having distal rectal adenocarcinoma with clinically positive LPLNs (≥7 mm, with irregular borders or mixed signal intensity) using primary pelvic magnetic resonance imaging (MRI). These patients had received SIB-IMRT-based neoadjuvant chemoradiotherapy (NCRT) and non-operative treatment according to the heterogeneity of the disease or personal preference. Chi-square tests were used to compare data between the two groups. Progression-free survival (PFS) and local regrowth were evaluated using the Kaplan-Meier method. RESULTS: Between 2016 and 2019, we analyzed 75 patients diagnosed as having clinically positive LPLNs using primary MRI. SIB-IMRT was delivered to the planning positive LPLNs (PGTVn) at a total dose of 56-60 Gy. After NCRT, 23 patients underwent non-operative treatment. Among these patients, the median short axis of LPLNs was 8 mm (range: 7-21 mm). Fifteen patients were categorized into the mesorectal fascia (MRF)-positive group. The median follow-up duration for these patients was 19.8 months, and no patient exhibited LPLN regrowth. The 2-year PFS rate was 85.6% for non-operative patients, 74.6% for operative patients, and 90.0% for the pathological complete response (pCR) subgroup. Eighteen patients who underwent non-operative treatment were included in the clinical complete response (cCR) subgroup. The 2-year PFS and local regrowth rates in this group were similar to those in patients with clinically negative LPLN who achieved cCR. During NCRT, 21 (28.0%) patients experienced grade 2-3 acute reversible toxicity. CONCLUSIONS: SIB-IMRT could eliminate metastases in LPLNs in a safe and effective manner, and non-operative strategies may be promising for cCR patients.

OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.

The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, 'Mutation', 'Gene', 'Pathway' and 'Cancer', to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

Inter- and intratumor DNA methylation heterogeneity associated with lymph node metastasis and prognosis of esophageal squamous cell carcinoma.

Background: Esophageal squamous cell carcinoma (ESCC), one of the leading causes of cancer mortality worldwide, is a heterogeneous cancer with diverse clinical manifestations. However, little is known about the epigenetic heterogeneity and its clinical relevance for this prevalent cancer. Methods: We generated 7.56 Tb single-base resolution whole-genome bisulfite sequencing data for 84 ESCC and paired paraneoplastic tissues. The analysis identified inter- and intratumor DNA methylation (DNAm) heterogeneity, epigenome-wide DNAm alterations together with the functional regulators involved in the hyper- or hypomethylated regions, and their association with clinical features. We then validated the correlation between the methylation level of specific regions and clinical outcomes of 96 ESCC patients in an independent cohort. Results: ESCC manifested substantial inter- and intratumor DNAm heterogeneity. The high intratumor DNAm heterogeneity was associated with lymph node metastasis and worse overall survival. Interestingly, hypermethylated regions in ESCC were enriched in promoters of numerous transcription factors, and demethylated noncoding regions related to RXR transcription factor binding appeared to contribute to the development of ESCC. Furthermore, we identified numerous DNAm alterations associated with carcinogenesis and lymph node metastasis of ESCC. We also validated three novel prognostic markers for ESCC, including one each in the promoter of CLK1, the 3' untranslated region of ZEB2, and the intergenic locus surrounded by several lncRNAs. Conclusions: This study presents the first population-level resource for dissecting base-resolution DNAm variation in ESCC and provides novel insights into the ESCC pathogenesis and progression, which might facilitate diagnosis and prognosis for this prevalent malignancy.

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

Prediction of Clinical Outcome in Locally Advanced Non-Small Cell Lung Cancer Patients Treated With Chemoradiotherapy by Plasma Markers.

PURPOSE: To identify cytokines in plasma that may predict objective response and progression-free survival (PFS) in patients with locally advanced non-small cell lung cancer (NSCLC) treated with chemoradiotherapy. MATERIALS AND METHODS: From April 2016 to May 2017, thirty-one patients with locally advanced inoperable/unresectable NSCLC were included, and treated with concurrent chemoradiotherapy (CCRT). No immune checkpoint inhibitors were administered after CCRT. Plasma from each patient was collected before radiotherapy, and 25 cytokines in the plasma were measured by Luminex or U-PLEX assays. Logistic regression and COX regression were performed to identify the predictive factors for objective response and PFS, respectively. Kaplan-Meier survival analysis was used to compare the PFS between the groups. RESULTS: High levels of IL-13 and TNF-α, and low levels of ICAM-1, IFN-γ, and soluble PD-L1 (sPD-L1) were significantly associated with objective response (P <0.05). High levels of IL-8, CCL5, and CXCL3 also showed a trend toward association with objective response (P <0.1). The combination of cytokines (IL-8 and ICAM-1, or TNF-α and sPD-L1) improved predictive accuracy. Univariate analysis identified IL-8 and ICAM-1 as potential markers to predict PFS. Multivariate analysis suggested that high level of IL-8 (P =0.010) and low level of ICAM-1 (P =0.011) correlated significantly with a longer PFS. CONCLUSION: IL-8 and ICAM-1 in plasma have the potential to predict objective response and PFS in patients with locally advanced NSCLC underwent chemoradiotherapy.