Molecular Profiling Provides Clinical Insights Into Targeted and Immunotherapies as Well as Colorectal Cancer Prognosis.

BACKGROUND & AIMS: Tumor genetic testing is indispensable in the management of primary and metastatic colorectal cancer (CRC), yet the indications for genomics-guided precision medicine and immunotherapy must be better understood and defined. METHODS: We prospectively sequenced tumors from 869 Chinese patients with CRC by a large panel and evaluated the clinical significance of single-gene somatic mutations and co-occurring events in metastatic CRC, as well as their functional effects and tumorigenic mechanisms. We systematically assessed the heterogeneity of the tumor immune microenvironment in different genomic contexts through the combined analysis of Immunoscore, multiplex immunostaining, whole-exome sequencing, transcriptome, and single-cell sequencing. RESULTS: Single-gene somatic mutations in BRAF or RBM10 were associated with shorter progression-free survival in patients with metastatic CRC. Functional studies suggested RBM10 acts as a tumor suppressor in CRC development. Co-mutations of KRAS/AMER1 or KRAS/APC were enriched in the metastatic cohort, which had poor progression-free survival and did not benefit from bevacizumab due to accelerated drug metabolism. Forty patients (4.6%) carried pathogenic or likely pathogenic germline alterations in the DNA damage repair pathway and 37.5% of these tumors had secondary-hit events with loss of heterozygosity or biallelic alterations. A high tumor insertion or deletion burden with high microsatellite instability suggested immunogenicity with numerous activated tumor-infiltrating lymphocytes, whereas polymerase epsilon exonuclease mutation with ultrahigh tumor mutation burden indicated a relatively quiescent immunophenotype. The heterogeneous genomic-immunologic interactions were reflected in the divergent neoantigen presentation and depletion, immune checkpoint expression, PD-1/PD-L1 interaction, and T-cell responsiveness to pembrolizumab. CONCLUSIONS: Our integrated analysis provides insights into CRC prognostic stratification, drug response, and personalized genomics-guided targeted and immunotherapies.

Nomogram for Predicting Breast Cancer-Specific Mortality of Elderly Women with Breast Cancer.

BACKGROUND The objectives of this study were to evaluate the cumulative incidence of breast cancer-specific death (BCSD) and other cause-specific death in elderly patients with breast cancer (BC) and to develop an individualized nomogram for estimating BCSD. MATERIAL AND METHODS Data were retrieved from the Surveillance, Epidemiology, and End Results program. A total of 25 241 patients older than 65 years with stage I-III BC diagnosed between 2004 and 2008 was included in the study cohort. We used the cumulative incidence function (CIF) to describe the cause-specific mortality and Gray's test to compare the differences in CIF among the groups. Fine and Gray's proportional subdistribution hazard model was applied to validate the independent prognostic factors, upon which the competing-risks nomogram and web-based calculator was built. The performance of the nomogram was assessed with the C-indexes and calibration plot diagrams. RESULTS After data screening, 25 241 cases were included for statistical analysis. In the training cohort, the 5-, 8-, and 10-year cumulative incidence of BCSD was 5.7, 8.1, and 9.1%, respectively. Ten independent prognostic factors associated with BCSD were identified. The C-index of the nomogram was 0.818 (0.804-0.831) in the training cohort and 0.808 (0.783-0.833) in the validation cohort. Calibration plot diagrams showed near-ideal consistency between the predicted probabilities and actual observations. CONCLUSIONS We built a reliable dynamic nomogram for predicting BCSD in elderly patients, and this individualized predictive tool is favorable for risk classification and complex personalized treatment decision making in clinical practice.

Host Genotype and Precipitation Influence of Fungal Endophyte Symbiosis and Mycotoxin Abundance in a Locoweed.

Many plant endophytes produce mycotoxins, but how host genetic variation influences endophyte colonization and mycotoxin production under natural conditions is poorly understood. This interaction has not been fully considered in many previous studies which used controlled experiments with agronomic or model plant species. Here, we investigated this interaction in a naturally occurring forb (a locoweed species) Oxytropis ochrocephala, its symbiotic endophyte Alternaria oxytropis, and the mycotoxin swainsonine. Host genetic variation was characterized by microsatellite markers. Endophyte infection rate and swainsonine levels were determined by PCR and HPLC, respectively. Genetic markers defined two distinct host populations and revealed that host genetics were significantly correlated with geographical location, elevation, and precipitation. As the host diverged, symbiotic interactions were reduced or failed to produce detectable swainsonine in one host population. Host genotype and precipitation had a significant impact in shaping swainsonine production at the population level. This study highlights the effect of host genotype in influencing this interaction in locoweeds.

Dynamic Hybrid Models With Active Sampling and Adaptive Selection of Double-Domain Features for the Tuning of Microwave Cavity Filters.

Microwave cavity filters are essential electromechanical coupling devices in communication systems. Structural-parameter tuning by experienced operators improves the filter performance but is demanding and time-consuming. The automatic tuning method has received extensive research attentions using data-driven modeling approaches. However, two main issues affect the accuracy and efficiency of the model construction: 1) features of tuning processes, as model inputs, have limited adaptability and extraction accuracy to different resonant states and 2) models require plentiful training data and the training process is time-consuming. Thus, dynamic hybrid models are developed in this study with self-selected inputs, self-organized samples, and a self-learning structure. First, spatial features are extracted to flexibly depict the tuning characteristic, and double-domain (spatial or circuital) features are selected adaptively to accommodate distinct resonance states. Second, a trustworthiness-curiosity-driven active sampling method is exploited to attain fewer and better-training data. Third, an improved glsms broad learning system acrlong BLS is developed using new modules of incremental node calculation and weight pruning, characterized by more lightweight and flexible structures. The proposed method is effective and flexible demonstrated by simulations and experiments, and the tuning task of microwave cavity filters is fulfilled in a more accurate and efficient manner.

In vivo multidimensional CRISPR screens identify Lgals2 as an immunotherapy target in triple-negative breast cancer.

Immune checkpoint inhibitors exhibit limited response rates in patients with triple-negative breast cancer (TNBC), suggesting that additional immune escape mechanisms may exist. Here, we performed two-step customized in vivo CRISPR screens targeting disease-related immune genes using different mouse models with multidimensional immune-deficiency characteristics. In vivo screens characterized gene functions in the different tumor microenvironments and recovered canonical immunotherapy targets such as Ido1. In addition, functional screening and transcriptomic analysis identified Lgals2 as a candidate regulator in TNBC involving immune escape. Mechanistic studies demonstrated that tumor cell-intrinsic Lgals2 induced the increased number of tumor-associated macrophages, as well as the M2-like polarization and proliferation of macrophages through the CSF1/CSF1R axis, which resulted in the immunosuppressive nature of the TNBC microenvironment. Blockade of LGALS2 using an inhibitory antibody successfully arrested tumor growth and reversed the immune suppression. Collectively, our results provide a theoretical basis for LGALS2 as a potential immunotherapy target in TNBC.

Large-scale genomic sequencing reveals adaptive opportunity of targeting mutated-PI3Kα in early and advanced HER2-positive breast cancer.

BACKGROUND: Few studies have discussed the contradictory roles of mutated-PI3Kα in HER2-positive (HER2+) breast cancer. Thus, we characterised the adaptive roles of PI3Kα mutations among HER2+ tumour progression. METHODS: We conducted prospective clinical sequencing of 1923 Chinese breast cancer patients and illustrated the clinical significance of PIK3CA mutations in locally advanced and advanced HER2+ cohort. A high-throughput PIK3CA mutations-barcoding screen was performed to reveal impactful mutation sites in tumour growth and drug responses. RESULTS: PIK3CA mutations acted as a protective factor in treatment-naïve patients; however, advanced/locally advanced patients harbouring mutated-PI3Kα exhibited a higher progressive disease rate (100% vs. 15%, p = .000053) and a lower objective response rate (81.7% vs. 95.4%, p = .0008) in response to trastuzumab-based therapy. Meanwhile, patients exhibiting anti-HER2 resistance had a relatively high variant allele fraction (VAF) of PIK3CA mutations; we defined the VAF > 12.23% as a predictor of poor anti-HER2 neoadjuvant treatment efficacy. Pooled mutations screen revealed that specific PI3Kα mutation alleles mediated own biological effects. PIK3CA functional mutations suppressed the growth of HER2+ cells, but conferred anti-HER2 resistance, which can be reversed by the PI3Kα-specific inhibitor BYL719. CONCLUSIONS: We proposed adaptive treatment strategies that the mutated PIK3CA and amplified ERBB2 should be concomitantly inhibited when exposing to continuous anti-HER2 therapy, while the combination of anti-HER2 and anti-PI3Kα treatment was not essential for anti-HER2 treatment-naïve patients. These findings improve the understanding of genomics-guided treatment in the different progressions of HER2+ breast cancer.

Metabolic-Pathway-Based Subtyping of Triple-Negative Breast Cancer Reveals Potential Therapeutic Targets.

Triple-negative breast cancer (TNBC) remains an unmet medical challenge. We investigated metabolic dysregulation in TNBCs by using our multi-omics database (n = 465, the largest to date). TNBC samples were classified into three heterogeneous metabolic-pathway-based subtypes (MPSs) with distinct metabolic features: MPS1, the lipogenic subtype with upregulated lipid metabolism; MPS2, the glycolytic subtype with upregulated carbohydrate and nucleotide metabolism; and MPS3, the mixed subtype with partial pathway dysregulation. These subtypes were validated by metabolomic profiling of 72 samples. These three subtypes had distinct prognoses, molecular subtype distributions, and genomic alterations. Moreover, MPS1 TNBCs were more sensitive to metabolic inhibitors targeting fatty acid synthesis, whereas MPS2 TNBCs showed higher sensitivity to inhibitors targeting glycolysis. Importantly, inhibition of lactate dehydrogenase could enhance tumor response to anti-PD-1 immunotherapy in MPS2 TNBCs. Collectively, our analysis demonstrated the metabolic heterogeneity of TNBCs and enabled the development of personalized therapies targeting unique tumor metabolic profiles.

Characterization of the genomic landscape and actionable mutations in Chinese breast cancers by clinical sequencing.

The remarkable advances in next-generation sequencing technology have enabled the wide usage of sequencing as a clinical tool. To promote the advance of precision oncology for breast cancer in China, here we report a large-scale prospective clinical sequencing program using the Fudan-BC panel, and comprehensively analyze the clinical and genomic characteristics of Chinese breast cancer. The mutational landscape of 1,134 breast cancers reveals that the most significant differences between Chinese and Western patients occurred in the hormone receptor positive, human epidermal growth factor receptor 2 negative breast cancer subtype. Mutations in p53 and Hippo signaling pathways are more prevalent, and 2 mutually exclusive and 9 co-occurring patterns exist among 9 oncogenic pathways in our cohort. Further preclinical investigation partially suggests that NF2 loss-of-function mutations can be sensitive to a Hippo-targeted strategy. We establish a public database (Fudan Portal) and a precision medicine knowledge base for data exchange and interpretation. Collectively, our study presents a leading approach to Chinese precision oncology treatment and reveals potentially actionable mutations in breast cancer.

Co-Expression Network Analysis Identified Gene Signatures in Osteosarcoma as a Predictive Tool for Lung Metastasis and Survival.

Osteosarcoma (OS) is the most common primary bone tumor, whose poor prognosis is mainly due to lung metastasis. The aim of this study is to build a practical and valid diagnostic test that can predict the risk of OS metastasis and progression. We performed weighted gene co-expression network analysis (WGCNA) on GSE21257 from the Gene Expression Omnibus (GEO) database, which contains microarray data of biopsies from OS patients. In these modules, the highest association was found between the blue module and metastasis stage (r = -0.52) by Pearson's correlation analysis. Based on Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we derived eight clinically significant genes and constructed an eight-gene signature for metastasis status. It showed great efficacy to distinguish metastasis from non-metastasis (AUC = 0.886) and the results were validated in The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis of hub genes showed that their biological processes focused on immune-related pathways, suggesting the important roles of immune cells, immune pathways and the tumor microenvironment in metastasis development. In conclusion, we discovered an efficient gene signature with great efficacy to distinguish metastasis status, which may help improve early diagnosis and treatment, enhancing the clinical outcomes of OS patients. Besides we created an effective protocol to seek for several hub genes in high-throughput data by combining WGCNA and LASSO Cox regression.

Development and validation of nomograms for predicting overall and breast cancer-specific survival among patients with triple-negative breast cancer.

PURPOSE: TNBC is generally more aggressive than other BC subtypes and has limited therapeutic options. We aimed to construct comprehensive and reliable nomograms to predict the OS and BCSS of TNBC patients to offer clinicians therapeutic guidance for improving the prognosis of TNBC patients. PATIENTS AND METHODS: We used the SEER 19 Cancer Registry to identify 21,419 eligible TNBC patients diagnosed from January 1, 2010 to December 31, 2015, and divided the database randomly into a training cohort (n=10,709) and a validation cohort (n=10,710). The log-rank test and Cox analysis together with a competing risk model were utilized to identify independent prognostic factors for OS and BCSS, which were then integrated to construct nomograms. RESULTS: According to the training cohort, except for laterality, the following factors were all predictive of OS and BCSS: age at diagnosis, race, tumor size, number of positive lymph nodes, grade, and histological subtype. The 1-, 3-, and 5-year probabilities of BC-specific mortality were 2.7%, 12.5%, and 17.1%, respectively. The precision of the nomograms was assessed by the C-index value and calibration plot diagrams. The C-index value were 0.779 for OS and 0.793 for BCSS in the internal validation and 0.774 for OS and 0.792 for BCSS in the external validation. Both internal and external calibration plot diagrams showed good consistency between the actual and predicted outcomes, especially for 3- and 5-year OS and BCSS. CONCLUSION: These nomograms hold promise as a novel and accurate tool in predicting OS and BCSS of TNBC patients and could be used in clinical practice to assist clinicians in developing more effective therapeutic strategies and to evaluate prognostic personally.

De novo Transcriptome Assembly of a Chinese Locoweed (Oxytropis ochrocephala) Species Provides Insights into Genes Associated with Drought, Salinity, and Cold Tolerance.

BACKGROUND: Locoweeds (toxic Oxytropis and Astraglus species), containing the toxic agent swainsonine, pose serious threats to animal husbandry on grasslands in both China and the US. Some locoweeds have evolved adaptations in order to resist various stress conditions such as drought, salt and cold. As a result they replace other plants in their communities and become an ecological problem. Currently very limited genetic information of locoweeds is available and this hinders our understanding in the molecular basis of their environmental plasticity, and the interaction between locoweeds and their symbiotic swainsonine producing endophytes. Next-generation sequencing provides a means of obtaining transcriptomic sequences in a timely manner, which is particularly useful for non-model plants. In this study, we performed transcriptome sequencing of Oxytropis ochrocephala plants followed by a de nove assembly. Our primary aim was to provide an enriched pool of genetic sequences of an Oxytropis sp. for further locoweed research. RESULTS: Transcriptomes of four different O. ochrocephala samples, from control (CK) plants, and those that had experienced either drought (20% PEG), salt (150 mM NaCl) or cold (4°C) stress were sequenced using an Illumina Hiseq 2000 platform. From 232,209,506 clean reads 23,220,950,600 (~23 G nucleotides), 182,430 transcripts and 88,942 unigenes were retrieved, with an N50 value of 1237. Differential expression analysis revealed putative genes encoding heat shock proteins (HSPs) and late embryogenesis abundant (LEA) proteins, enzymes in secondary metabolite and plant hormone biosyntheses, and transcription factors which are involved in stress tolerance in O. ochrocephala. In order to validate our sequencing results, we further analyzed the expression profiles of nine genes by quantitative real-time PCR. Finally, we discuss the possible mechanism of O. ochrocephala's adaptations to stress environment. CONCLUSION: Our transcriptome sequencing data present useful genetic information of a locoweed species. This genetic information will underpin further research in elucidating the environmental acclimation mechanism in locoweeds and the endophyte-plant association.