Plasma cell-free DNA chromosomal instability analysis by low-pass whole-genome sequencing to monitor breast cancer relapse.

BACKGROUND: Chromosomal instabilities (CIN) of plasma cell-free DNA (cfDNA) are common in breast cancer. We aimed to investigate the value of cfDNA CIN in monitoring the breast cancer relapse and additionally to compare it with the traditional biomarkers (CA15-3 and CEA). METHODS: Overall 62 recurrent breast cancer patients and 20 healthy controls were recruited. Low-pass whole-genome sequencing (LPWGS) was performed to detect cfDNA CIN. A CIN score was calculated. The performance of CA15-3, CEA, and CIN score in monitoring the recurrence was investigated with receiver operating characteristic (ROC) curve and the area under curve (AUC). Multivariable Cox proportional hazard model was established to analyze the correlations between copy number gain/loss and disease-free survival (DFS). RESULTS: cfDNA CIN achieved the positive rate of 77.6% [(95% confidence interval (CI) 73.4-95.3%)] among recurrent breast cancer patients, with an AUC value of 0.933, superior to CA15-3 (positive rate: 38.7%; AUC: 0.864) and CEA (positive rate: 41.93%; AUC: 0.878) (P < 0.01). The combination of cfDNA CIN with two biomarkers further increased the positive rate to 88.7% (95% confidence interval 77.5-95.0%). cfDNA CIN achieved better performance in patients with shorter DFS (≤ 41 months), with an AUC value of 0.975. CONCLUSIONS: cfDNA CIN yields a higher accuracy in monitoring breast cancer recurrence compared to traditional biomarkers (CA15-3 and CEA), especially for biomarker-negative patients. The combination of cfDNA CIN to traditional biomarkers further improved the detection rate of recurrence, which may provide a new method for monitoring the early relapse of breast cancer, though further investigations are warranted.

Recurrent amplification of MYC and TNFRSF11B in 8q24 is associated with poor survival in patients with gastric cancer.

BACKGROUND: Gastric cancer (GC) is an aggressive malignancy whose mechanisms of development and progression are poorly understood. The identification of prognosis-related genomic loci and genes may suffer from the relatively small case numbers and a lack of systematic validation in previous studies. METHODS: Array-based comparative genomic hybridization (aCGH) coupled with patient clinical information was applied to identify prognosis-related loci and genes with high-frequency recurrent gains in 129 GC patients. The candidate loci and genes were then validated using an independent cohort of 384 patients through branched DNA signal amplification analysis (QuantiGene assays). RESULTS: In the 129 patients, a copy number gain of three chromosome regions-namely, 8q22 (including ESRP1 and CCNE2), 8q24 (including MYC and TNFRSF11B), and 20q11-q13 (including SRC, MMP9, and CSE1L)--conferred poor survival for patients. In addition, the correlation between the branched DNA signal amplification analysis results and the aCGH results was analyzed in 73 of these 129 patients, and MYC, TNFRSF11B, ESRP1, CSE1L, and MMP9 were found to be well correlated. Further validation using an independent cohort (n = 384) verified that only MYC and TNFRSF11B within 8q24 are related to survival. Patients with gains in both MYC and TNFRSF11B had poorer survival than those with no gains, particularly those with noncardia GC. Gains in both of these genes were also a significant independent prognostic indicator. CONCLUSIONS: Our results revealed that copy number gains in MYC and TNFRSF11B located at 8q24 are associated with survival in GC, particularly noncardia GC.

Oncogenic HER2 fusions in gastric cancer.

BACKGROUND: Genetic amplification of HER2 drives tumorigenesis and cancer progression in a subset of patients with gastric cancer (GC), and treatment with trastuzumab, a humanized HER2-neutralizing antibody, improves the overall survival rate of HER2-positive patients. However, a considerable portion of the patients does not respond to trastuzumab and the molecular mechanisms underlying the intrinsic resistance to anti-HER2 therapy in GC is not fully understood. METHODS: We performed whole-transcriptome sequencing on 21 HER2-positive tumor specimens from Chinese GC patients. Whole genome sequencing was performed on the three samples with HER2 fusion to discover the DNA integration structure. A multicolor FISH assay for HER2 split screening was conducted to confirm HER2 fusion and IHC (HercepTest™) was used to detect the membranous expression of HER2. Fusion cDNA were transfected into NIH/3T3 cells and generate stable cell line by lentivirus. The expression of exogenous HER2 fusion proteins and pHER2 were examined by western blot analysis. In vitro efficacy studies were also conducted by PD assay and softagar assay in cell line expression wild type and fusion HER2. T-DM1 was used to assess its binding to NIH/3T3 cells ectopically expressing wild-type and fusion HER2. Finally, the anti-tumor efficacy of trastuzumab was tested in NIH/3 T3 xenografts expressing the HER2 fusion variants. RESULTS: We identified three new HER2 fusions with ZNF207, MDK, or NOS2 in 21 HER2-amplified GC samples (14%; 3/21). Two of the fusions, ZNF207-HER2, and MDK-HER2, which are oncogenic, lead to aberrant activation of HER2 kinase. Treatment with trastuzumab inhibited tumor growth significantly in xenografts expressing MDK-HER2 fusion. In contrast, trastuzumab had no effect on the growth of xenografts expressing ZNF207-HER2 fusion, due to its inability to bind to trastuzumab. CONCLUSIONS: Our results provide the molecular basis of a novel resistance mechanism to trastuzumab-based anti-HER2 therapy, supporting additional molecule stratification within HER2-positive GC patients for more effective therapy options.

Identification and validation of dysregulated MAPK7 (ERK5) as a novel oncogenic target in squamous cell lung and esophageal carcinoma.

BACKGROUND: MAPK7/ERK5 (extracellular-signal-regulated kinase 5) functions within a canonical three-tiered MAPK (mitogen activated protein kinase) signaling cascade comprising MEK (MAPK/ERK kinase) 5, MEKK(MEK kinase) 2/3 and ERK5 itself. Despite being the least well studied of the MAPK-modules, evidence supports a role for MAPK7-signaling in the pathology of several cancer types. METHODS AND RESULTS: Fluorescence in situ hybridization (FISH) analysis identified MAPK7 gene amplification in 4% (3/74) of non-small cell lung cancers (NSCLC) (enriched to 6% (3/49) in squamous cell carcinoma) and 2% (2/95) of squamous esophageal cancers (sqEC). Immunohistochemical (IHC) analysis revealed a good correlation between MAPK7 gene amplification and protein expression. MAPK7 was validated as a proliferative oncogenic driver by performing in vitro siRNA knockdown of MAPK7 in tumor cell lines. Finally, a novel MEK5/MAPK7 co-transfected HEK293 cell line was developed and used for routine cell-based pharmacodynamic screening. Phosphorylation antibody microarray analysis also identified novel downstream pharmacodynamic (PD) biomarkers of MAPK7 kinase inhibition in tumor cells (pMEF2A and pMEF2D). CONCLUSIONS: Together, these data highlight a broader role for dysregulated MAPK7 in driving tumorigenesis within niche populations of highly prevalent tumor types, and describe current efforts in establishing a robust drug discovery screening cascade.

Whole genome gene copy number profiling of gastric cancer identifies PAK1 and KRAS gene amplification as therapy targets.

Gastric cancer is the second leading cause of death from cancer worldwide, with an approximately 20% 5-year survival rate. To identify molecular subtypes associated with the clinical prognosis, in addition to genetic aberrations for potential targeted therapeutics, we conducted a comprehensive whole-genome analysis of 131 Chinese gastric cancer tissue specimens using whole-genome array comparative genomic hybridization. The analyses revealed gene focal amplifications, including CTSB, PRKCI, PAK1, STARD13, KRAS, and ABCC4, in addition to ERBB2, FGFR2, and MET. The growth of PAK1-amplified gastric cancer cells in vitro and in vivo was inhibited when the corresponding mRNA was knocked down. Furthermore, both KRAS amplification and KRAS mutation were identified in the gastric cancer specimens. KRAS amplification was associated with worse clinical outcomes, and the KRAS gene mutation predicted sensitivity to the MEK1/2 inhibitor AZD6244 in gastric cancer cell lines. In summary, amplified PAK1, as well as KRAS amplification/mutation, may represent unique opportunities for developing targeted therapeutics for the treatment of gastric cancer.

CD147 protein molecule expression and chromosomal instability in the pathogenesis and prognosis of thyroid cancer.

Low-coverage whole genome sequencing was performed for tissue samples from thyroid patients who received surgery treatment from 2015 to 2021. The potential biological significance of CD147 protein in thyroid cancer was explored through correlation analysis of CD147 protein expression level and clinical features of thyroid cancer patients. Low coverage whole genome sequencing was performed on the extracted DNA samples. The copy number analysis software was used to analyze the sequencing data, calculate the copy number of CD147 gene, further verify the expression of CD147 gene, and analyze its association with clinical features. The relationship between CIN and high risk was evaluated in the internal cohort. The association of CIN with the disease-free survival was validated in the cohort from The Cancer Genome Atlas Program. Thyroglobulin plays a key role in regulating thyroid function and maintaining normal metabolic rate. By sequencing tissue samples from this study, we can gain a deeper understanding of the association between cin and thyroid disease. The percentage of high risk patients in the multiple CIN group (77.8 %) was significantly higher than that in the 22q negative group (31.3 %), BRAF V600E group (22.2 %) and all negative group (25.0 %; p = 0.043).

Preoperative urine sediment chromosomal instability level predicts urothelial cancer prognosis.

PURPOSE: Urothelial carcinomas (UCs) are often characterized by frequent recurrences after surgery, making UC one of the costliest cancers. Chromosomal instability (CIN) has been proven to be a hallmark of UCs and is related to the prognosis of many cancer types. In this study, we evaluated CIN of urine sediments as a prognostic indicator for UCs. METHODS: Patients with UC were prospectively recruited. Preoperative urine samples were collected for whole genome sequencing and urine cytology tests. Patients underwent standard-of-care treatment and were followed up until disease relapse or study ended. Concordance and accuracy of CIN alone or in combination with cytology in predicting disease relapse were assessed. The value of CIN combined with European Organization for Research and Treatment of Cancer (EORTC) model were also analyzed. RESULTS: A total of 137 patients with UCs were included in this study. Median follow-up was 44.2 months and 41.61% patients suffered from cancer relapse. Patients with CIN-high indicated higher relapse rate, and this distinction was significant for patients underwent transurethral resection of bladder tumor (57.89% vs. 34.29%, P = 0.016). Combination of cytology and CIN result could further classified patients into subgroups with distinct relapse risks. Meanwhile, the combination of CIN and EORTC model significantly improved the prediction accuracy compared with EORTC alone (Harrel's C-index: 0.71 vs. 0.65). CONCLUSION: CIN level of preoperative urine exfoliated cells had robust prognostic value for bladder cancer patients underwent TURBT. The prognostic model by combining CIN and EORTC may help in stratifying patients to optimize follow-up regimen.

Virtual screening combined with experimental verification reveals the potential mechanism of Fuzitang decoction against Gouty Arthritis.

Background: and Purpose: Fuzitang decoction (FZT), a classic prescription of traditional Chinese medicine (TCM), has excellent efficacy in treating gouty arthritis (GA). However, the underlying molecular mechanism remains obscure. In the present study, we aimed to explore the underlying mechanisms of FZT in treating GA by virtual screening combined with experimental verification. Methods: In this study, the active components of FZT and their corresponding targets were screened from the TCMSP database and TargetNet database. Then, the potential targets of FZT against GA were retrieved from multiple databases to generate a network. Protein-protein interaction, herbal-component-target, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were applied to identify potential targets and related signaling pathways. Furthermore, molecular docking simulation was applied to identify the interactions between the drug and targets. Finally, in vitro experiments were conducted to validate the potential targets and signaling pathways. Results: In the present study, several crucial components, including kaempferol, luteolin, catechin, deoxyandrographolide, and perlolyrine in FZT, were obtained through network pharmacology, and several potential targets to treat GA were developed, such as PPARG, CYP3A4, PTGS2 (known as COX2), VEGFA, and CYP1A1. Experimental validation suggested that deoxyandrographolide significantly suppressed the expression of IL-1ß, COX2, NLRP3 and IL-6 in inflammatory monocyte cells. Conclusions: Our results identified a novel anti-inflammatory compound, deoxyandrographolide, which helps to explain the potential mechanism of FZT in treating GA and provides evidence to support FZT's clinical use.

High chromosome instability identified by low-pass whole-genome sequencing assay is associated with TP53 copy loss and worse prognosis in BRCA1 germline mutation breast cancer.

BACKGROUND: Though BRCA1 mutation is the most susceptible factor of breast cancer, its prognostic value is disputable. Here in this study, we use a novel method which based on whole-genome analysis to evaluate the chromosome instability (CIN) value and identified the potential relationship between CIN and prognosis of breast cancer patients with germline-BRCA1 mutation. MATERIALS AND METHODS: Sanger sequencing or a 98-gene panel sequencing assay was used to screen for BRCA1 germline small mutations in 1151 breast cancer patients with high-risk factors. MLPA assay was employed to screen BRCA1 large genomic rearrangements in familial breast cancer patients with BRCA1 negative for small mutations. Thirty-two samples with unique BRCA1 germline mutation patterns were further subjected to CIN evaluation by LPWGS (low-pass whole-genome sequencing) technology. RESULTS: Firstly, 113 patients with germline BRCA1 mutations were screened from the cohort. Further CIN analysis by the LPWGS assay indicated that CIN was independent from the mutation location or type of BRCA1. Patients with high CIN status had shorter disease-free survival rates (DFS) (HR = 6.54, 95% CI 1.30-32.98, P = 0.034). The TP53 copy loss was also characterized by LPWGS assay. The rates of TP53 copy loss in CIN high and CIN low groups were 85.71% (12/14) and 16.67% (3/18), respectively. CONCLUSION: CIN-high is a prognostic factor correlated with shorter DFS and was independent with the germline BRCA1 mutation pattern. Higher CIN values were significantly correlated with TP53 copy loss in breast cancer patients with germline BRCA1 mutation. Our results revealed a reliable molecular parameter for distinguishing patients with poor prognosis from the BRCA1-mutated breast cancer patients.

Investigating Acupoint Selection and Combinations of Acupuncture for Tic Disorders: An Association Rule Mining and Network Analysis Study.

Objective: Tic disorders (TDs) are common mental disorders in children and adolescents, and the clinical application of acupuncture for treating TDs is becoming increasingly widespread. However, the criteria for selecting acupoint prescriptions and combinations have not been summarized. Therefore, data mining was used herein to determine the treatment principles and the most effective acupoint selection and compatibility criteria for the treatment of TDs. Methods: Clinical studies and observations of the efficacy of acupuncture treatment for TDs were obtained from the PubMed, Cochrane Library, EMBASE, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Chinese Biomedical (CBM) databases. The data on the acupoint prescriptions applied in these studies were collected, and network and association analyses were used to reveal the relationships between acupoints and to identify acupoint combinations. Additionally, the principles of acupuncture for TDs were determined through cluster analysis. Subgroup analysis of acupuncture prescriptions based on specific categorical diagnoses was performed to further assess the selection of acupoints. Results: Eighty-six trials were identified, and 257 groups of effective prescriptions involving 121 acupoints were extracted. Bai-hui (DU20), Feng-chi (GB20), Tai-chong (LR3), He-gu (LI4), and San-yin-jiao (SP6) were the most regularly used acupoints for treating TDs. The Governor Vessel, gallbladder, and large intestine meridians were more commonly used than other meridians. Moreover, most acupoint sites focused on the head and neck. Network analysis revealed potentially effective acupoint prescriptions for their commonly used acupoints, namely, Bai-hui (DU20), Si-shen-cong (EX-HN1), Feng-chi (GB20), Nei-guan (PC6), Shen-men (HT7), He-gu (LI4), Zu-san-li (ST36), San-yin-jiao (SP6) and Tai-chong (LR3). Association rule mining indicated that potential point combinations that should be prioritized in TD treatment are Bai-hui (DU20), Neiguan (PC6) and Sanyinjiao (SP6). Cluster analysis revealed the treatment principle of "coordinating yin and yang, tonifying qi and blood, dispelling pathogenic wind and eliminating phlegm". The core acupoint prescription of TS treatment comprised He-gu (LI4), Feng-chi (GB20), Tai-chong (LR3), Bai-hui (DU20), Yin-tang (EX-HN3), Si-shen-cong (EX-HN1), San-yin-jiao (SP6), and Nei-guan (PC6). The core group included He-gu (LI4) and Feng-chi (GB20). Proximal points were usually used in TS as an additional method of point selection. Conclusion: Using data mining analysis of published studies, this study provides valuable information regarding the selection of the most effective acupoints and point combinations for clinical acupuncture practice for treating TDs.

Washout DNA copy number analysis by low-coverage whole genome sequencing for assessment of thyroid FNAs.

Background: Papillary thyroid microcarcinoma (PTMC) is defined as a papillary carcinoma measuring ≤ 10 mm. The current management of PTMC has become more conservative; however, there are high-risk tumor features that can be revealed only postoperatively. For thyroid cancer, BRAF mutations and somatic copy number variation (CNV) are the most common genetic events. Molecular testing may contribute to clinical decision-making by molecular risk stratification, for example predicting lymph node (LN) metastasis. Here, we build a risk stratification model based on molecular profiling of thyroid fine needle aspiration (FNA) washout DNA (wDNA) for the differential diagnosis of thyroid nodules. Methods: Fifty-eight patients were recruited, FNA wDNA samples were analyzed using CNV profiling through low-coverage whole genome sequencing (LC-WGS) and BRAF mutation was analyzed using quantitative PCR. FNA pathology was reported as a Bethesda System for Reporting Thyroid Cytopathology (BSRTC) score. Ultrasound examination produced a Thyroid Imaging Reporting and Data System (TIRADS) score. Results: In total, 37 (63.8%) patients with a TIRADS score of 4A, 13 (22.4%) patients with a TIRADS score of 4B, and 8 (13.8%) patients with a TIRADS score of 4C were recruited after ultrasound examination. All patients underwent FNA with wDNA profiling. CNVs were identified in 17 (29.3%) patients. CNVs were frequent in patients with a BSRTC score of V or VI, including eight (47.1%) patients with a score of VI and five (29.4%) with a score of V, but not in patients with a score of III, II, or I (0%). BRAF mutation was not significantly correlated with BSRTC score. LN metastasis was found more frequently in CNV-positive (CNV+) than in CNV-negative (CNV-) patients (85.7% vs. 34.6%, odds ratio = 11.33, p = 0.002). In total, three molecular subtypes of thyroid nodules were identified in this study: 1) CNV+, 2) CNV- and BRAF positive (BRAF+), and 3) CNV- and BRAF negative (BRAF-). For the CNV+ subtype, 10 (83.3%) lesions with LN metastasis were found, including four (100%) small lesions (i.e. ≤ 5 mm). For the CNV- and BRAF+ nodules, LN metastases were detected in only seven (60.0%) larger tumors (i.e. > 5 mm). For CNV- and BRAF- tumors, LN metastasis was also frequently found in larger tumors only. Conclusions: It is feasible to identify high-risk LN metastasis thyroid cancer from FNA washout samples preoperatively using wDNA CNV profiling using LC-WGS.

Copy number variation of urine exfoliated cells by low-coverage whole genome sequencing for diagnosis of prostate adenocarcinoma: a prospective cohort study.

BACKGROUND: Non-invasive, especially the urine-based diagnosis of prostate cancer (PCa) remains challenging. Although prostate cancer antigen (PSA) is widely used in prostate cancer screening, the false positives may result in unnecessary invasive procedures. PSA elevated patients are triaged to further evaluation of free/total PSA ratio (f/t PSA), to find out potential clinically significant PCa before undergoing invasive procedures. Genomic instability, especially chromosomal copy number variations (CNVs) were proved much more tumor specific. Here we performed a prospective study to evaluate the diagnostic value of CNV via urine-exfoliated cell DNA analysis in PCa. METHODS: We enrolled 28 PSA elevated patients (≥ 4 ng/ml), including 16 PCa, 9 benign prostate hypertrophy (BPH) and 3 prostatic intraepithelial neoplasia (PIN). Fresh initial portion urine was collected after hospital admission. Urine exfoliated cell DNA was analyzed by low coverage Whole Genome Sequencing, followed by CNV genotyping by the prostate cancer chromosomal aneuploidy detector (ProCAD). CNVs were quantified in absolute z-score (|Z|). Serum free/total PSA ratio (f/t PSA) was reported altogether. RESULTS: In patients with PCa, the most frequent CNV events were chr3q gain (n = 2), chr8q gain (n = 2), chr2q loss (n = 4), and chr18q loss (n = 3). CNVs were found in 81.2% (95% Confidence Interval (CI) 53.7-95.0%) PCa. No CNV was identified in BPH patients. A diagnosis model was established by incorporating all CNVs. At the optimal cutoff of |Z|≥ 2.50, the model reached an AUC of 0.91 (95% CI 0.83-0.99), a sensitivity of 81.2% and a specificity of 100%. The CNV approach significantly outperformed f/t PSA (AUC = 0.62, P = 0.012). Further analyses showed that the CNV positive rate was significantly correlated with tumor grade. CNVs were found in 90.9% (95% CI 57.1-99.5%) high grade tumors and 60.0% (95% CI 17.0-92.7%) low grade tumors. No statistical significance was found for patient age, BMI, disease history and family history. CONCLUSIONS: Urine exfoliated cells harbor enriched CNV features in PCa patients. Urine detection of CNV might be a biomarker for PCa diagnosis, especially in terms of the clinically significant high-grade tumors.

Cost-effective low-coverage whole-genome sequencing assay for the risk stratification of gastric cancer.

BACKGROUND: Gastric cancer (GC), a multifactorial disease, is caused by pathogens, such as Helicobacter pylori (H. pylori) and Epstein-Barr virus (EBV), and genetic components. AIM: To investigate microbiomes and host genome instability by cost-effective, low-coverage whole-genome sequencing, as biomarkers for GC subtyping. METHODS: Samples from 40 GC patients were collected from Taizhou Hospital, Zhejiang Province, affiliated with Wenzhou Medical University. DNA from the samples was subjected to low-coverage whole-genome sequencing with a median genome coverage of 1.86 × (range: 1.03 × to 3.17 ×) by Illumina × 10, followed by copy number analyses using a customized bioinformatics workflow ultrasensitive chromosomal aneuploidy detector. RESULTS: Of the 40 GC samples, 20 (50%) were found to be enriched with microbiomes. EBV DNA was detected in 5 GC patients (12.5%). H. pylori DNA was found in 15 (37.5%) patients. The other 20 (50%) patients were found to have relatively higher genomic instability. Copy number amplifications of the oncogenes, ERBB2 and KRAS, were found in 9 (22.5%) and 7 (17.5%) of the GC samples, respectively. EBV enrichment was found to be associated with tumors in the gastric cardia and fundus. H. pylori enrichment was found to be associated with tumors in the pylorus and antrum. Tumors with elevated genomic instability showed no localization and could be observed in any location. Additionally, H. pylori-enriched GC was found to be associated with the Borrmann type II/III and gastritis history. EBV-enriched GC was not associated with gastritis. No statistically significant correlation was observed between genomic instability and gastritis. Furthermore, these three different molecular subtypes showed distinct survival outcomes (P = 0.019). EBV-positive tumors had the best prognosis, whereas patients with high genomic instability (CIN+) showed the worst survival. Patients with H. pylori infection showed intermediate prognosis compared with the other two subtypes. CONCLUSION: Thus, using low-coverage whole-genome sequencing, GC can be classified into three categories based on disease etiology; this classification may prove useful for GC diagnosis and precision medicine.

Combination treatment for advanced hepatocellular carcinoma with portal vein tumour thrombus: A case report.

We present a case of a 43-year-old man with advanced hepatocellular carcinoma (HCC) with portal vein tumour thrombus. Initially, transcatheter arterial chemoembolization (TACE) was performed. Although alpha-fetoprotein (AFP) levels decreased, circulating tumour DNA (ctDNA) levels showed an upward trend, and abdominal magnetic resonance imaging (MRI) showed that tumours in the portal vein had increased. Based on ctDNA profiling, apatinib and anti-programmed cell death protein 1 (anti-PD-1) antibodies and were sequentially administered. Approximately three months later, intrahepatic tumours had significantly diminished and AFP and ctDNA levels had reduced. The response was sustained at the 23-month follow-up and the patient was in good health. Combination treatment of TACE, apatinib and anti-PD-1 antibodies was effective, and profiling of ctDNA fragmentation may be beneficial in the therapeutic management of patients with HCC.

Seven Genes Associated With Lymphatic Metastasis in Thyroid Cancer That Is Linked to Tumor Immune Cell Infiltration.

OBJECTIVE: Since there are few studies exploring genes associated with lymphatic metastasis of thyroid carcinoma (THCA), this study was conducted to explore genes associated with lymphatic metastasis of THCA and to investigate the relationship with immune infiltration. METHODS: Differentially expressed genes associated with THCA lymphatic metastasis were analyzed based on The Cancer Genome Atlas Program (TCGA) database; a protein-protein interaction(PPI)network was constructed to screen for pivotal genes. Based on the identified hub genes, their expression in THCA with and without lymphatic metastasis were determined. Functional enrichment analysis was performed. The correlation between the identified genes and immune cell infiltration was explored. LASSO logistic regression analysis was performed to determine the risk score of the most relevant gene constructs and multifactor COX regression analysis based on genes in the risk score formula. RESULTS: A total of 115 genes were differentially expressed in THCA with and without lymphatic metastasis, including 28 upregulated genes and 87 downregulated genes. The PPI network identified seven hub genes (EVA1A, TIMP1, SERPINA1, FAM20A, FN1, TNC, MXRA8); the expression of all seven genes was upregulated in the group with lymphatic metastasis; Immuno-infiltration analysis showed that all seven genes were significantly positively correlated with macrophage M1 and NK cells and negatively correlated with T-cell CD4+ and myeloid dendritic cells. LASSO logistic regression analysis identified the five most relevant genes (EVA1A, SERPINA1, FN1, TNC, MXRA8), and multi-factor COX regression analysis showed EVA1A, SERPINA1 and FN1 as independent prognostic factors. CONCLUSION: Seven genes were associated with lymphatic metastasis of THCA and with tumor immune cell infiltration.

Non-invasive detection of biliary tract cancer by low-coverage whole genome sequencing from plasma cell-free DNA: A prospective cohort study.

BACKGROUND: The diagnosis of biliary tract cancer (BTC) is challenging in clinical practice. We performed a prospective study to evaluate the value of plasma copy number variation (CNV) assays in diagnosing BTC. METHODS: 47 treatment-naïve patients with suspicious biliary lesions were recruited. Plasma samples were collected at admission. Cell-free DNA was analyzed by low coverage whole genome sequencing, followed by CNV analyses via a customized bioinformatics workflow, namely the ultrasensitive chromosomal aneuploidy detector. RESULTS: 29 patients were pathologically diagnosed as BTC, including 8 gallbladder cancers (GBCs) and 21 cholangiocarcinomas (CCs). Cancer patients had more CNV signals as compared with benign patients (26/29 vs. 2/18, P < 0.001). The most frequent copy number gains were chr3q (7/29) and chr8q (6/29). The most frequent copy number losses were chr7p (6/29), chr17p (6/29), and chr19p (6/29). The sensitivity and specificity of plasma CNV assays in diagnosing BTC were 89.7% and 88.9%, respectively. For CA 19-9 (cutoff: 37 U/ml), the sensitivity was 58.6% and the specificity was 72.2%. The diagnostic accuracy of CNV assays significantly outperformed CA 19-9 (AUC 0.91 vs. 0.62, P = 0.004). Compared with CA 19-9 alone, the adding of CNV profiles to CA 19-9 increased the sensitivity in diagnosing GBC (75.0% vs. 25.0%) and CC (100% vs. 52.4%). Higher CNV burden was also associated with decreased overall survival (Hazard ratio = 4.32, 95% CI 2.06-9.08, P = 0.033). DISCUSSION: Our results suggest that BTC harbors rich plasma CNV signals, and their assays might be useful for diagnosing BTC.

Prediction of interactiveness between small molecules and enzymes by combining gene ontology and compound similarity.

Determination of whether a small organic molecule interacts with an enzyme can help to understand the molecular and cellular functions of organisms, and the metabolic pathways. In this research, we present a prediction model, by combining compound similarity and enzyme similarity, to predict the interactiveness between small molecules and enzymes. A dataset consisting of 2859 positive couples of small molecule and enzyme and 286,056 negative couples was employed. Compound similarity is a measurement of how similar two small molecules are, proposed by Hattori et al., J Am Chem Soc 2003, 125, 11853 which can be availed at http://www.genome.jp/ligand-bin/search_compound, while enzyme similarity was obtained by three ways, they are blast method, using gene ontology items and functional domain composition. Then a new distance between a pair of couples was established and nearest neighbor algorithm (NNA) was employed to predict the interactiveness of enzymes and small molecules. A data distribution strategy was adopted to get a better data balance between the positive samples and the negative samples during training the prediction model, by singling out one-fourth couples as testing samples and dividing the rest data into seven training datasets-the rest positive samples were added into each training dataset while only the negative samples were divided. In this way, seven NNAs were built. Finally, simple majority voting system was applied to integrate these seven models to predict the testing dataset, which was demonstrated to have better prediction results than using any single prediction model. As a result, the highest overall prediction accuracy achieved 97.30%.

A knowledge-based method to predict the cooperative relationship between transcription factors.

Identifying the cooperation between transcription factors is crucial and challenging to uncover the mystery behind the complex gene expression patterns. Computational methods aimed to infer transcription factor cooperation are expected to get good results if we can integrate the knowledge (existed functional/structural annotations) of proteins. In this contribution, we proposed an information integrative computational framework to infer the cooperation between transcription factors, which relies on the hybridization-space method that can integrate the annotation information of proteins. In our computational experiments, by using function domain annotations only, on our testing dataset, the overall prediction accuracy and the specificity reaches 84.3% and 76.9%, respectively, which is a fairly good result and outperforms the prediction by both amino acid composition-based method and BLAST-based approach. The corresponding online service TFIPS (Transcription Factor Interaction Prediction System) is available on http://pcal.biosino.org/cgi-bin/TFIPS/TFIPS.pl.

Predicting miRNA's target from primary structure by the nearest neighbor algorithm.

We used a machine learning method, the nearest neighbor algorithm (NNA), to learn the relationship between miRNAs and their target proteins, generating a predictor which can then judge whether a new miRNA-target pair is true or not. We acquired 198 positive (true) miRNA-target pairs from Tarbase and the literature, and generated 4,888 negative (false) pairs through random combination. A 0/1 system and the frequencies of single nucleotides and di-nucleotides were used to encode miRNAs into vectors while various physicochemical parameters were used to encode the targets. The NNA was then applied, learning from these data to produce a predictor. We implemented minimum redundancy maximum relevance (mRMR) and properties forward selection (PFS) to reduce the redundancy of our encoding system, obtaining 91 most efficient properties. Finally, via the Jackknife cross-validation test, we got a positive accuracy of 69.2% and an overall accuracy of 96.0% with all the 253 properties. Besides, we got a positive accuracy of 83.8% and an overall accuracy of 97.2% with the 91 most efficient properties. A web-server for predictions is also made available at http://app3.biosino.org:8080/miRTP/index.jsp.

Identification of somatic copy number variations in plasma cell free DNA correlating with intrinsic resistances to EGFR targeted therapy in T790M negative non-small cell lung cancer.

BACKGROUND: About 20-30% EGFR-mutant non-small lung cancer show intrinsic resistance to EGFR targeted therapies. Compared to T790M positive in acquired resistance patients, little is known about EGFR-TKI intrinsic resistance for T790M negative patients. METHODS: Thirty-one patients with advanced stage lung cancer, including 18 patients with intrinsic resistance (PFS <6 months) and 13 patients with acquired resistance (PFS >36 months) but are negative for plasma T790M were recruited in the study. Plasma cell free DNA was profiled by low coverage whole genome sequencing with median genome coverage of 1.86X by Illumina X10. Sequencing coverage across chromosomes was summarized by samtools, and normalized by segmentation analysis as provided by R package 'DNACopy'. RESULTS: The most frequent chromosomal changes were found on chr7, chr1 and chr8. Among them, chr7p gains were found in 12 (66.7%) intrinsic resistance and 4 (30.7%) acquired resistance patients. The gene EGFR was found located on the focal amplification peak of chr7p. The performance of 7p gain to predict intrinsic resistance reaches AUC =0.902. Similarly, focal amplifications were also found on chromosome 5, 16 and 22, where tumor related gene PCDHA@, ADAMTS18 and CRKL were located. Focal deletions were also found in chr1, 8, 10 and 16, where genes SFTPA1/2, DLC1, PTEN and CDH1 are located. CONCLUSIONS: The results suggest cell free DNA copy number might be a useful peripheral blood tumor biomarker for predicting intrinsic resistance of EGFR targeted therapy and prognosis.