Characterization of Genomic Alterations in Colorectal Liver Metastasis and Their Prognostic Value

Colorectal liver metastases (CRLMs) are clinically heterogeneous lesions with poor prognosis. Genetic alterations play a crucial role in their progression. The traditional Fong clinical risk score (Fong-CRS) is commonly used for risk stratification and prognosis prediction. By identifying the genomic alterations of CRLMs, we aimed to develop a mutation-based gene-signature-based clinical score (mut-CS) system to improve clinical prognostication. Tumour tissues from 144 patients with CRLMs were analysed with next-generation sequencing (NGS). A mut-CS scoring system considering the unique mutation-based gene signature, primary site, and Fong-CRS was developed and could identify CRLM patients with poor prognosis. The mean time-dependent receiver operating characteristic curve AUC value of the mut-CS system was greater than that of previously established scoring measures (the Fong-CRS, the e-clinical score, the presence of concomitant RAS and TP53 mutations, and other clinical traits). Taking together, we identified a mutant signature that exhibits a strong prognostic effect for CRLMs. Traditional clinical scoring system characteristics were incorporated into the new mut-CS scoring system to help determine the appropriate treatment for CRLMs.

Single-cell immune signature for detecting early-stage HCC and early assessing anti-PD-1 immunotherapy efficacy

Background

The early diagnosis of hepatocellular carcinoma (HCC) can greatly improve patients’ 5-year survival rate, and the early efficacy assessment is important for oncologists to harness the anti-programmed cell death protein 1 (PD-1) immunotherapy in patients with advanced HCC. The lack of effective predicting biomarkers not only leads to delayed detection of the disease but also results in ineffective immunotherapy and limited clinical survival benefit.

Methods

We exploited the single-cell approach (cytometry by time of flight (CyTOF)) to analyze peripheral blood mononuclear cells from multicohorts of human samples. Immune signatures for different stages of patients with HCC were systematically profiled and statistically compared. Furthermore, the dynamic changes of peripheral immune compositions for both first-line and second-line patients with HCC after anti-PD-1 monotherapy were also evaluated and systematically compared.

Results

We identified stage-specific immune signatures for HCC and constructed a logistic AdaBoost-SVM classifier based on these signatures. The classifier provided superior performance in predicting early-stage HCC over the commonly used serum alpha-fetoprotein level. We also revealed the treatment stage-specific immune signatures from peripheral blood and their dynamical changing patterns, all of which were integrated to achieve early discrimination of patients with non-durable benefit for both first-line and second-line anti-PD-1 monotherapies.

Conclusions

Our newly identified single-cell peripheral immune signatures provide promising non-invasive biomarkers for early detection of HCC and early assessment for anti-PD-1 immunotherapy efficacy in patients with advanced HCC. These new findings can potentially facilitate early diagnosis and novel immunotherapy for patients with HCC in future practice and further guide the utility of CyTOF in clinical translation of cancer research.

Trial registration numbers

NCT02576509 and NCT02989922.

Interleukin-33 as an early predictor of cetuximab treatment efficacy in patients with colorectal cancer

Background

Cetuximab is used for colorectal cancer (CRC) treatment. However, the early biomarker of treatment efficacy of cetuximab has not been identified.

Methods

After 1 year of cetuximab treatment, patients were divided into an effective group and an ineffective group. The interleukin‐33 (IL‐33) level and the distribution of lymphatic cells in patients were investigated by analyzing the peripheral blood mononuclear cells via flow cytometry analysis and ELISA. The correlation between IL‐33 immunomodulatory effect and cetuximab treatment efficacy was determined through experiments in vivo and in vitro.

Results

The IL‐33 level in the peripheral blood was increased at 4 weeks after cetuximab administration of effective group, meanwhile, the osteopontin (OPN) was reduced. Whereas neither IL‐33 level nor OPN level of ineffective patients changed. In the effective group, the number of natural killer (NK) and CD8⁺ T cells were increased. Moreover, CD137 and CD107a expression on NK cells were higher in the effective group compared to the ineffective group. In vitro cetuximab treatment also increased the number of NK and CD8⁺ T cells as well as CD137 and CD107a expression upon IL‐33 stimulation. Moreover, the secretion of OPN was inhibited by IL‐33 administration in cetuximab‐treated PBMCs from the effective group patients. IL‐33 upregulated the cytotoxicity of NK cells and inhibited tumor cells growth in the effective cetuximab treatment mice.

Conclusion

Effective cetuximab treatment induced a change of IL‐33 and OPN at the early stage and triggered the NK cells antitumor activity. Consequently, significantly increased IL‐33 level and decreased OPN level in the peripheral blood at the early treatment are proposed as potential predictors of cetuximab treatment efficacy.

Emerging treatment evolutions and integrated molecular characteristics of biliary tract cancers

Biliary tract cancers (BTCs) consist of a group of highly heterogeneous malignancies that are characterized by genomic differences among tumors from different anatomic sites. The current treatment for BTC includes surgery, chemotherapy, target therapy, and immunotherapy. Although surgery remains the primary option for localized disease, representing the only potential curative treatment, a high risk of recurrence cannot be neglected. Chemotherapy has been considered the standard of care for both advanced and metastatic disease and in adjuvant settings. However, drug resistance is a major obstacle associated with chemotherapy. The development of genetic testing technologies, including next‐generation sequencing, has opened the door for the identification of drug targets and candidate molecules. A series of preclinical studies has demonstrated the role of gene mutations, abnormal signaling pathways, and immunosuppression in the pathogenesis of BTC, laying the foundation for the application of targeted therapy and immunotherapy. A variety of molecularly targeted agents, including pemigatinib, have shown promising survival benefits in patients with advanced disease. The rapidly evolving role of multimodal therapy represents the subject of this review.

Signaling pathway perturbation analysis for assessment of biological impact of cigarette smoke on lung cells

Exposure to cigarette smoke (CS) results in injury to the epithelial cells of the human respiratory tract and has been implicated as a causative factor in the development of chronic obstructive pulmonary disease and lung cancers. The application of omics-scale methodologies has improved the capacity to understand cellular signaling processes underlying response to CS exposure. We report here the development of an algorithm based on quantitative assessment of transcriptomic profiles and signaling pathway perturbation analysis (SPPA) of human bronchial epithelial cells (HBEC) exposed to the toxic components present in CS. HBEC were exposed to CS of different compositions and for different durations using an ISO3308 smoking regime and the impact of exposure was monitored in 2263 signaling pathways in the cell to generate a total effect score that reflects the quantitative degree of impact of external stimuli on the cells. These findings support the conclusion that the SPPA algorithm provides an objective, systematic, sensitive means to evaluate the biological impact of exposures to CS of different compositions making a powerful comparative tool for commercial product evaluation and potentially for other known or potentially toxic environmental smoke substances.

Immunotherapy for targeting cancer stem cells in hepatocellular carcinoma

The rapid development and remarkable success of checkpoint inhibitors have provided significant breakthroughs in cancer treatment, including hepatocellular carcinoma (HCC). However, only 15-20% of HCC patients can benefit from checkpoint inhibitors. Cancer stem cells (CSCs) are responsible for recurrence, metastasis, and local and systemic therapy resistance in HCC. Accumulating evidence has suggested that HCC CSCs can create an immunosuppressive microenvironment through certain intrinsic and extrinsic mechanisms, resulting in immune evasion. Intrinsic evasion mechanisms mainly include activation of immune-related CSC signaling pathways, low-level expression of antigen presenting molecules, and high-level expression of immunosuppressive molecules. External evasion mechanisms are mainly related to HBV/HCV infection, alcoholic/nonalcoholic steatohepatitis, hypoxia stimulation, abnormal angiogenesis, and crosstalk between CSCs and immune cells. A better understanding of the complex mechanisms of CSCs involved in immune evasion will contribute to therapies for HCC. Here we will outline the detailed mechanisms of immune evasion for CSCs, and provide an overview of the current immunotherapies targeting CSCs in HCC.

Nutrition and metabolism status alteration in advanced hepatocellular carcinoma patients treated with anti-PD-1 immunotherapy

PURPOSE

The aim of this study was to evaluate the nutrition and metabolism status alteration during immunotherapy in advanced hepatocellular carcinoma (HCC) patients.

METHODS

Patients with advanced HCC who participated in the clinical trials of single-agent anti-PD-1 immunotherapy or sorafenib were retrospectively included. We analyzed self-comparison of the nutritional and metabolic indices of patients in the anti-PD-1 and sorafenib treatment group. We conducted mutual-comparison of the mentioned indices between the disease progression group and disease control group among anti-PD-1 treatment patients. We further analyzed those indices with statistical differences by partial correlation and survival analysis.

RESULTS

Both self-comparison before and after treatment in the anti-PD-1 group and mutual-comparison of disease progression and the control group showed significant differences in multiple indices, but we did not observe significant differences in the sorafenib group. Strikingly, albumin (ALB)/prognostic nutritional index (PNI, calculated by serum albumin and lymphocyte count) decreased distinctly in the immunotherapy disease progression group patients. However, changes in ALB/PNI were not significant in disease progression patients from the sorafenib group or in the disease control patients with immunotherapy. Partial correlation analysis suggested that ALB and PNI were positively correlated with the efficacy of immunotherapy. Furthermore, survival analysis showed that the median progression-free survival and median overall survival of patients in the ALB/PNI decreased group were significantly shorter than those of patients from the ALB/PNI increased group.

CONCLUSION

Anti-PD-1 immunotherapy might alter the nutritional and metabolic status in advanced HCC patients. We also should pay attention to the nutritional and metabolic status of patients when drug resistance is detected.

Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy

BACKGROUND

Microsatellite instability in colon cancer implies favorable therapeutic outcomes after checkpoint blockade immunotherapy. However, the molecular nature of microsatellite instability is not well elucidated.

METHODS

We examined the immune microenvironment of colon cancer using assessments of the bulk transcriptome and the single-cell transcriptome focusing on molecular nature of microsatellite stability (MSS) and microsatellite instability (MSI) in colorectal cancer from a public database. The association of the mutation pattern and microsatellite status was analyzed by a random forest algorithm in The Cancer Genome Atlas (TCGA) and validated by our in-house dataset (39 tumor mutational burden (TMB)-low MSS colon cancer, 10 TMB-high MSS colon cancer, 15 MSI colon cancer). A prognostic model was constructed to predict the survival potential and stratify microsatellite status by a neural network.

RESULTS

Despite the hostile CD8+ cytotoxic T lymphocyte (CTL)/Th1 microenvironment in MSI colon cancer, a high percentage of exhausted CD8+ T cells and upregulated expression of immune checkpoints were identified in MSI colon cancer at the single-cell level, indicating the potential neutralizing effect of cytotoxic T-cell activity by exhausted T-cell status. A more homogeneous highly expressed pattern of PD1 was observed in CD8+ T cells from MSI colon cancer; however, a small subgroup of CD8+ T cells with high expression of checkpoint molecules was identified in MSS patients. A random forest algorithm predicted important mutations that were associated with MSI status in the TCGA colon cancer cohort, and our in-house cohort validated higher frequencies of BRAF, ARID1A, RNF43, and KM2B mutations in MSI colon cancer. A robust microsatellite status-related gene signature was built to predict the prognosis and differentiate between MSI and MSS tumors. A neural network using the expression profile of the microsatellite status-related gene signature was constructed. A receiver operating characteristic curve was used to evaluate the accuracy rate of neural network, reaching 100%.

CONCLUSION

Our analysis unraveled the difference in the molecular nature and genomic variance in MSI and MSS colon cancer. The microsatellite status-related gene signature is better at predicting the prognosis of patients with colon cancer and response to the combination of immune checkpoint inhibitor-based immunotherapy and anti-VEGF therapy.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC

Triple-negative breast cancer (TNBC) is characterized by a more aggressive clinical course with extensive inter- and intra-tumour heterogeneity. Combination of single-cell and bulk tissue transcriptome profiling allows the characterization of tumour heterogeneity and identifies the association of the immune landscape with clinical outcomes. We identified inter- and intra-tumour heterogeneity at a single-cell resolution. Tumour cells shared a high correlation amongst stemness, angiogenesis, and EMT in TNBC. A subset of cells with concurrent high EMT, stemness and angiogenesis was identified at the single-cell level. Amongst tumour-infiltrating immune cells, M2-like tumour-associated macrophages (TAMs) made up the majority of macrophages and displayed immunosuppressive characteristics. CIBERSORT was applied to estimate the abundance of M2-like TAM in bulk tissue transcriptome file from The Cancer Genome Atlas (TCGA). M2-like TAMs were associated with unfavourable prognosis in TNBC patients. A TAM-related gene signature serves as a promising marker for predicting prognosis and response to immunotherapy. Two commonly used machine learning methods, random forest and SVM, were applied to find the genes that were mostly associated with M2-like TAM densities in the gene signature. A neural network-based deep learning framework based on the TAM-related gene signature exhibits high accuracy in predicting the immunotherapy response.

Ultra-stable Biomembrane Force Probe for Accurately Determining Slow Dissociation Kinetics of PD-1 Blockade Antibodies on Single Living Cells

Immune checkpoint blockade with monoclonal antibodies (mAbs) that target programmed cell death protein-1 (PD-1) has remarkably revolutionized cancer therapy. Their binding kinetics measured by surface plasmon resonance does not always correlate well with their immunotherapeutic efficacies, mainly due to the lack of two-dimensional cell plasma membrane and the capability of force sensing and manipulation. In this regard, based on a more suitable and ultra-sensitive biomechanical nanotool, biomembrane force probe (BFP), we developed a Double-edge Smart Feedback control system as an ultra-stable platform to characterize ultra-long bond lifetimes of receptor-ligand binding on living cells. We further benchmarked the dissociation kinetics for three clinically approved PD-1 blockade mAbs (Nivolumab, Pembrolizumab, and Camrelizumab), intriguingly correlating well with the objective response rates in the hepatocellular carcinoma second-line treatment. This ultra-stable BFP potentially provides a compelling kinetic platform to direct the screening, optimization, and clinical selection of therapeutic antibodies in the future.

SCAU-Net: Spatial-Channel Attention U-Net for Gland Segmentation

With the development of medical technology, image semantic segmentation is of great significance for morphological analysis, quantification, and diagnosis of human tissues. However, manual detection and segmentation is a time-consuming task. Especially for biomedical image, only experts are able to identify tissues and mark their contours. In recent years, the development of deep learning has greatly improved the accuracy of computer automatic segmentation. This paper proposes a deep learning image semantic segmentation network named Spatial-Channel Attention U-Net (SCAU-Net) based on current research status of medical image. SCAU-Net has an encoder-decoder-style symmetrical structure integrated with spatial and channel attention as plug-and-play modules. The main idea is to enhance local related features and restrain irrelevant features at the spatial and channel levels. Experiments on the gland dataset GlaS and CRAG show that the proposed SCAU-Net model is superior to the classic U-Net model in image segmentation task, with 1% improvement on Dice score and 1.5% improvement on Jaccard score.

Anti-PD-1/PD-L1 Blockade Immunotherapy Employed in Treating Hepatitis B Virus Infection-Related Advanced Hepatocellular Carcinoma: A Literature Review

Hepatitis B virus (HBV) infection is regarded as the main etiological risk factor in the process of hepatocellular carcinoma (HCC), as it promotes an immunosuppressive microenvironment that is partially mediated by the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) signaling pathway. The tumor microenvironment (TME) of HBV-related HCC is indeed more immunosuppressive than microenvironments not associated with viruses. And compared to TME in hepatitis C virus (HCV) infected HCC, TME of HBV-related HCC is less vascularized and presents different immune components resulting in similar immunosuppression. However, few studies are focusing on the specific side effects and efficacy of PD-1/PD-L1 blockade immunotherapy in HBV-related HCC patients, as well as on the underlying mechanism. Herein, we reviewed the basic research focusing on potential TME alteration caused by HBV infection, especially in HCC patients. Moreover, we reviewed PD-1/PD-L1 blockade immunotherapy clinical trials to clarify the safety and efficacy of this newly developed treatment in the particular circumstances of HBV infection. We found that patients with HBV-related HCC displayed an acceptable safety profile similar to those of non-infected HCC patients. However, we could not determine the antiviral activity of PD-1/PD-L1 blockade because standard anti-viral therapies were conducted in all of the current clinical trials, which made it difficult to distinguish the potential influence of PD-1/PD-L1 blockade on HBV infection. Generally, the objective response rates (ORRs) of PD-1/PD-L1 blockade immunotherapy did not differ significantly between virus-positive and virus-negative patients, except that disease control rates (DCRs) were obviously lower in HBV-infected HCC patients.

Dynamic alterations of genome and transcriptome in KRAS G13D mutant CRC PDX model treated with cetuximab

Background

KRAS mutations have been characterized as the major predictive biomarkers for resistance to cetuximab treatment. However, studies indicate that not all KRAS mutations are associated with equivalent treatment outcomes. KRAS G13D mutations were observed to account for approximately 16% of all KRAS mutations in advanced colorectal cancer patients, and whether these patients can benefit from cetuximab has not been determined.

Methods

An established KRAS G13D mutant colorectal cancer (CRC) patient-derived xenograft (PDX) model was treated with cetuximab. After repeated use of cetuximab, treatment-resistant PDX models were established. Tissue samples were collected before and during treatment, and multiomics data were subsequently sequenced and processed, including whole-exome, mRNA and miRNA data, to explore potential dynamic changes.

Results

Cetuximab treatment initially slowed tumor growth, but resistance developed not long after treatment. WES (whole-exome sequencing) and RNA sequencing found that 145 genes had low P values (< 0.01) when analyzed between the locus genotype and its related gene expression level. Among these genes, SWAP70 was believed to be a probable cause of acquired resistance. JAK2, PRKAA1, FGFR2 and RALBP1, as well as 10 filtered immune-related genes, also exhibited dynamic changes during the treatment.

Conclusions

Cetuximab may be effective in KRAS G13D mutation patients. Dynamic changes in transcription, as determined by WES and RNA sequencing, occurred after repeated drug exposure, and these changes were believed to be the most likely cause of drug resistance.

Gut microbiome affects the response to anti-PD-1 immunotherapy in patients with hepatocellular carcinoma

Background

Checkpoint-blockade immunotherapy targeting programmed cell death protein 1 (PD-1) has recently shown promising efficacy in hepatocellular carcinoma (HCC). However, the factors affecting and predicting the response to anti-PD-1 immunotherapy in HCC are still unclear. Herein, we report the dynamic variation characteristics and specificities of the gut microbiome during anti-PD-1 immunotherapy in HCC using metagenomic sequencing.

Results

Fecal samples from patients responding to immunotherapy showed higher taxa richness and more gene counts than those of non-responders. For dynamic analysis during anti-PD-1 immunotherapy, the dissimilarity of beta diversity became prominent across patients as early as Week 6. In non-responders, Proteobacteria increased from Week 3, and became predominant at Week 12. Twenty responder-enriched species, including Akkermansia muciniphila and Ruminococcaceae spp., were further identified. The related functional genes and metabolic pathway analysis, such as carbohydrate metabolism and methanogenesis, verified the potential bioactivities of responder-enriched species.

Conclusions

Gut microbiome may have a critical impact on the responses of HCC patients treated with anti-PD-1 immunotherapy. The dynamic variation characteristics of the gut microbiome may provide early predictions of the outcomes of immunotherapy in HCC, which is critical for disease-monitoring and treatment decision-making.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0650-9) contains supplementary material, which is available to authorized users.

Antibiotics and immunotherapy in gastrointestinal tumors: Friend or foe?

The incidence of gastrointestinal (GI) tumors is increasing year by year, and its pathogenesis is closely related to the intestinal flora. At present, the use of antibiotics is very common in the clinic. And cancer patients with low immunity are vulnerable to all sorts of infections, such as respiratory tract infections and urinary tract infections. Moreover, cancer patients easily run into fever and neutropenia induced by myelosuppression. Therefore, antibiotics are used extensively and even overused in many conditions. However, because of the special anatomical location of the gastrointestinal tract, the antibiotic usage will bring changes to the intestinal flora. Besides, with the expanding popularity of immunotherapy, various factors affecting the efficacy of immune checkpoint inhibitors (ICIs) have been extensively explored, including cancer-associated inflammation and the local and systemic factors that lead to immunosuppression. Some biomarkers for ICIs, including the expression of PD-L1, tumor mutation load, and microbiota, also have been investigated, and many studies have confirmed that gut microbiota can affect the efficacy of immunotherapy. But further studies on the influence of antibiotics directly on immunotherapy are rare. In this review, we discuss the relationship between GI tumors and antibiotics, the current status of immunotherapy in GI tumors, and the influence of antibiotics on immunotherapy.

Advantage of Next-Generation Sequencing in Dynamic Monitoring of Circulating Tumor DNA over Droplet Digital PCR in Cetuximab Treated Colorectal Cancer Patients

Epidermal growth factor receptor (EGFR) blockade resistance is common in the treatment of RAS wide type colorectal cancer (CRC). During the treatment of cetuximab, acquired resistant genomic alterations always occurs earlier than disease progression observed by medical images. Identification of genomic alterations dynamically might have certain clinical significance. Because of the limitation of repeated tissue biopsy, liquid biopsy is increasingly recognized. Droplet digital polymerase chain reaction (ddPCR) is the main detection methods for circulating tumor DNA (ctDNA), however, the application of next-generation sequencing (NGS) for ctDNA detection becomes more and more popular. Here we develop a NGS-based ctDNA assay and evaluated its sensitivity and specificity while using ddPCR as control. These two technologies were both used for genomic alteration detection for the peripheral blood samples from cetuximab-treated colorectal cancer patients dynamically. Fifteen patients were enrolled in this study, including eight males and seven females. The sensitivity and specificity of our NGS assay were 87.5% and 100% respectively, and liner regression analysis comparing variant allele frequency (VAF) revealed high concordance between NGS and ddPCR (R² = 0.98). NGS actually found more mutation information than ddPCR such as the additional dynamic changes of TP53 which were observed in the disease progression patients. Moreover, the variant allele fraction of TP53 was also found by NGS to be changed along with the clinical efficacy evaluation dynamically during the whole treatment process. In conclusion, our newly developed NGS-based ctDNA assay shows similar performance with ddPCR but have more advantages of its high throughput of multigenetic detection for the dynamic monitoring during the treatment of cetuximab in metastasis CRC patients.

Identifying the clonal origin of synchronous multifocal tumors in the hepatobiliary and pancreatic system using multi-omic platforms

Synchronous multifocal tumors often pose a diagnostic challenge for oncologists. The purpose of this study was to determine the clonal origin and metastatic relationship of synchronous multifocal tumors in the hepatobiliary and pancreatic system using multi-omic platforms. DNA samples were extracted from three masses harvested from a 50-year-old Han Chinese male patient who suffered from synchronous multifocal tumors in the pancreatic tail, upper biliary duct, and omentum at the time of diagnosis. The clonal origin of these samples was tested using two platforms: next-generation sequencing (NGS) of 390 key genes harboring cancer-relevant actionable mutations and whole-genome copy number variation (CNV) chip analysis. The NGS approach revealed high mutational concordance, and the gene CNV profiles were similar between lesions. Whole-genome CNVs for the three samples were further investigated using an Affymetrix chip. Using matched CNV chip data from The Cancer Genome Atlas (TCGA), we developed a computational model that generated tissue-specific CNV signatures for hepatocellular carcinoma, pancreatic carcinoma, and cholangiocarcinoma to accurately identify the origin of the tumor samples. After adding the patient's CNV chip data to the model, all three samples were clustered into the pancreatic cancer branch. Both our NGS and CNV chip analyses suggested that clinically diagnosed synchronous pancreatic cancer and cholangiocarcinoma originated from the same cell population in the pancreas in our patient. This study highlights the use of genomic tools to infer the origin of synchronous multifocal tumors, which could help to improve the accuracy of cancer diagnosis.

A naive Bayes algorithm for tissue origin diagnosis (TOD-Bayes) of synchronous multifocal tumors in the hepatobiliary and pancreatic system

Synchronous multifocal tumors are common in the hepatobiliary and pancreatic system but because of similarities in their histological features, oncologists have difficulty in identifying their precise tissue clonal origin through routine histopathological methods. To address this problem and assist in more precise diagnosis, we developed a computational approach for tissue origin diagnosis based on naive Bayes algorithm (TOD-Bayes) using ubiquitous RNA-Seq data. Massive tissue-specific RNA-Seq data sets were first obtained from The Cancer Genome Atlas (TCGA) and ∼1,000 feature genes were used to train and validate the TOD-Bayes algorithm. The accuracy of the model was >95% based on tenfold cross validation by the data from TCGA. A total of 18 clinical cancer samples (including six negative controls) with definitive tissue origin were subsequently used for external validation and 17 of the 18 samples were classified correctly in our study (94.4%). Furthermore, we included as cases studies seven tumor samples, taken from two individuals who suffered from synchronous multifocal tumors across tissues, where the efforts to make a definitive primary cancer diagnosis by traditional diagnostic methods had failed. Using our TOD-Bayes analysis, the two clinical test cases were successfully diagnosed as pancreatic cancer (PC) and cholangiocarcinoma (CC), respectively, in agreement with their clinical outcomes. Based on our findings, we believe that the TOD-Bayes algorithm is a powerful novel methodology to accurately identify the tissue origin of synchronous multifocal tumors of unknown primary cancers using RNA-Seq data and an important step toward more precision-based medicine in cancer diagnosis and treatment.

Aberrant Expression of HOXA5 and HOXA9 in AML

BACKGROUND

Aberrant expression of HOX gene expression has been observed in cancer. The purpose of this study was to investigate the alteration of HOXA5 and HOXA9 expression and their clinical significance in acute meloid leukemia (AML).

MATERIALS AND METHODS

The expression of HOXA5 and HOXA9 genes of bone marrow samples from 75 newly diagnosed AML patients and 22 healthy controls for comparison were examined by Real- time quantitative PCR (RQ-PCR) assay. Statistical analysis was conducted to evaluate HOXA5 and HOXA9 expression as possible biomarkers for AML.

RESULTS

The results showed that the complete remission rate (52.6%) of the patients who highly expressed HOXA5 and HOXA9 was significantly lower than that (88.9%) in patients who lowly express the genes (P=0.015). Spearmann correlation coefficients indicated that the expression levels for HOXA5 and HOXA9 genes were highly interrelated (r=0.657, P<0.001). Meanwhile, we detected significant correlations between HOXA9 expression and age in this limited set of patients (P=0.009).

CONCLUSIONS

The results suggest a prognostic impact of increased expression of HOXA5 and HOXA9 in AML patients.