Identification of Precise 3D CT Radiomics for Habitat Computation by Machine Learning in Cancer

Purpose To identify precise three-dimensional radiomics features in CT images that enable computation of stable and biologically meaningful habitats with machine learning for cancer heterogeneity assessment. Materials and Methods This retrospective study included 2436 liver or lung lesions from 605 CT scans (November 2010-December 2021) in 331 patients with cancer (mean age, 64.5 years ± 10.1 [SD]; 185 male patients). Three-dimensional radiomics were computed from original and perturbed (simulated retest) images with different combinations of feature computation kernel radius and bin size. The lower 95% confidence limit (LCL) of the intraclass correlation coefficient (ICC) was used to measure repeatability and reproducibility. Precise features were identified by combining repeatability and reproducibility results (LCL of ICC ≥ 0.50). Habitats were obtained with Gaussian mixture models in original and perturbed data using precise radiomics features and compared with habitats obtained using all features. The Dice similarity coefficient (DSC) was used to assess habitat stability. Biologic correlates of CT habitats were explored in a case study, with a cohort of 13 patients with CT, multiparametric MRI, and tumor biopsies. Results Three-dimensional radiomics showed poor repeatability (LCL of ICC: median [IQR], 0.442 [0.312-0.516]) and poor reproducibility against kernel radius (LCL of ICC: median [IQR], 0.440 [0.33-0.526]) but excellent reproducibility against bin size (LCL of ICC: median [IQR], 0.929 [0.853-0.988]). Twenty-six radiomics features were precise, differing in lung and liver lesions. Habitats obtained with precise features (DSC: median [IQR], 0.601 [0.494-0.712] and 0.651 [0.52-0.784] for lung and liver lesions, respectively) were more stable than those obtained with all features (DSC: median [IQR], 0.532 [0.424-0.637] and 0.587 [0.465-0.703] for lung and liver lesions, respectively; P < .001). In the case study, CT habitats correlated quantitatively and qualitatively with heterogeneity observed in multiparametric MRI habitats and histology. Conclusion Precise three-dimensional radiomics features were identified on CT images that enabled tumor heterogeneity assessment through stable tumor habitat computation. Keywords: CT, Diffusion-weighted Imaging, Dynamic Contrast-enhanced MRI, MRI, Radiomics, Unsupervised Learning, Oncology, Liver, Lung Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Sagreiya in this issue.

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression

Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunotherapy response. However, quantification of PD-L1 status in pathology slides is challenging. Neither manual quantification nor a computer-based mimicking of manual readouts is perfectly reproducible, and the predictive performance of both approaches regarding immunotherapy response is limited. In this study, we developed a deep learning (DL) method to predict PD-L1 status directly from raw IHC image data, without explicit intermediary steps such as cell detection or pigment quantification. We trained the weakly supervised model on PD-L1-stained slides from the non-small cell lung cancer (NSCLC)-Memorial Sloan Kettering (MSK) cohort (N = 233) and validated it on the pan-cancer-Vall d'Hebron Institute of Oncology (VHIO) cohort (N = 108). We also investigated the performance of the model to predict response to immune checkpoint inhibitors (ICI) in terms of progression-free survival. In the pan-cancer-VHIO cohort, the performance was compared with tumor proportion score (TPS) and combined positive score (CPS). The DL model showed good performance in predicting PD-L1 expression (TPS ≥ 1%) in both NSCLC-MSK and pan-cancer-VHIO cohort (AUC 0.88 ± 0.06 and 0.80 ± 0.03, respectively). The predicted PD-L1 status showed an improved association with response to ICIs [HR: 1.5 (95% confidence interval: 1-2.3), P = 0.049] compared with TPS [HR: 1.4 (0.96-2.2), P = 0.082] and CPS [HR: 1.2 (0.79-1.9), P = 0.386]. Notably, our explainability analysis showed that the model does not just look at the amount of brown pigment in the IHC slides, but also considers morphologic factors such as lymphocyte conglomerates. Overall, end-to-end weakly supervised DL shows potential for improving patient stratification for cancer immunotherapy by analyzing PD-L1 IHC, holistically integrating morphology and PD-L1 staining intensity.

SIGNIFICANCE

The weakly supervised DL model to predict PD-L1 status from raw IHC data, integrating tumor staining intensity and morphology, enables enhanced patient stratification in cancer immunotherapy compared with traditional pathologist assessment.

Expression of TILs and Patterns of Gene Expression from Paired Samples of Malignant Pleural Mesothelioma (MPM) Patients

MPM is an aggressive disease with an immunosuppressive tumor microenvironment, and interest in exploring immunotherapy in this disease has been increasing. In the first line of treatment, the combination of nivolumab and ipilimumab demonstrated an improvement in survival over chemotherapy. The presence of TILs has been recognized as a marker of antitumor immune response to chemotherapy in solid tumors. The aim of our study is to identify the effect of treatment on immune cells and the immune gene profile in MPM. We investigated the changes in expression of TILs in 10 human MPM paired tumor tissues using immunohistochemistry and gene expression analysis from paired untreated and treated samples. In this small series, we demonstrated that during the evolution of disease without any treatment there was an increase in the inflammatory component in tumor samples. After systemic treatment there was a decrease in the number of TILs. We observed that after systemic treatment or disease progression immune gene signatures were suppressed. Our integrated analysis of paired samples with immune profile and genomic changes on MPM suggested that during the evolution of the disease the immune system tends to switch, turning off with treatment.

T-cell infiltration in matched samples from malignant pleural mesothelioma (MPM) during evolution of disease

e20595

Background: MPM is an aggressive cancer associated with asbestos exposure. Chemotherapy has been a mainstay of therapy and recently immunotherapy has been associated with survival improvements. Chemotherapy and immunotherapy influence the tumor microenvironment and some reports have shown increased of TIL after chemotherapy in MPM. The purpose of this study was to determine dynamic changes in the tumor immune environment during mesothelioma evolution and after systemic therapies in paired samples. Methods: We examined 20 matched formalin-fixed paraffin embedded tissue samples from 10 patients (p) with MPM taken at diagnosis and at disease progression (follow-up), including untreated and treated with chemotherapy or immunotherapy. Tissue densities (number of cells/mm2) of key immune effector cells such as total lymphocytes (CD3), cytotoxic T cells (CD8), regulatory T cells (FOXP3) and monocytes/macrophages (CD163) were quantified by image analysis using multiplexed immunohistochemistry (IHC). PD-L1 expression in both tumor cells and immune cells was analysed by singleplex IHC and quantified using the CPS score. Results: Median age was 62 years (range 53-84), 7 p were male and all p presented epithelioid histology. Three matched samples belong to patients that did not receive any systemic treatment between biopsies and the other 7 pair of samples belong to patients treated with chemotherapy +/- immunotherapy. The median interval between paired biopsies was 12 m (3-33 m). Median overall survival was 27.8 months (1 m-NR). Median densities of T cells and macrophages in diagnostic and matched follow-up samples were: CD3+:982 vs 712; CD8+:422 vs 334, FOXP3+: 22 vs 25 and CD163+: 2086 vs 1706. Median PD-L1 CPS was 2.5 and 4 in diagnostic and follow-up samples, respectively. In p receiving treatment between sample pairs, the median densities in diagnostic and follow-up matched samples were: CD3+:979 vs 407; CD8+:467 vs 225, FOXP3+: 25 vs 15, CD163+: 1583 vs 1508, and PD-L1: 2 and 1. In p without any systemic treatment between sample pairs, the median densities were CD3+:1645 vs 2397; CD8+:376 vs 1605, FOXP3+: 19 vs 121, CD163+: 2102 vs 2377, and PD-L1: 3 vs 25. Conclusions: In our small series with paired samples from MPM p, we observed immune cells infiltration changes during MPM evolution with a trend towards a decrease after systemic therapy. Further investigation in tumor microenvironment in MPM to define the most appropriate time for immunotherapy is needed.

Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors

Patient-derived organoids (PDOs) recapitulate tumor architecture, contain cancer stem cells and have predictive value supporting personalized medicine. Here we describe a large-scale functional screen of dual-targeting bispecific antibodies (bAbs) on a heterogeneous colorectal cancer PDO biobank and paired healthy colonic mucosa samples. More than 500 therapeutic bAbs generated against Wingless-related integration site (WNT) and receptor tyrosine kinase (RTK) targets were functionally evaluated by high-content imaging to capture the complexity of PDO responses. Our drug discovery strategy resulted in the generation of MCLA-158, a bAb that specifically triggers epidermal growth factor receptor degradation in leucine-rich repeat-containing G-protein-coupled receptor 5-positive (LGR5+) cancer stem cells but shows minimal toxicity toward healthy LGR5+ colon stem cells. MCLA-158 exhibits therapeutic properties such as growth inhibition of KRAS-mutant colorectal cancers, blockade of metastasis initiation and suppression of tumor outgrowth in preclinical models for several epithelial cancer types.

A Novel Antagonistic CD73 Antibody for Inhibition of the Immunosuppressive Adenosine Pathway

Despite some impressive clinical results with immune checkpoint inhibitors, the majority of patients with cancer do not respond to these agents, in part due to immunosuppressive mechanisms in the tumor microenvironment. High levels of adenosine in tumors can suppress immune cell function, and strategies to target the pathway involved in its production have emerged. CD73 is a key enzyme involved in adenosine production. This led us to identify a novel humanized antagonistic CD73 antibody, mAb19, with distinct binding properties. mAb19 potently inhibits the enzymatic activity of CD73 in vitro, resulting in an inhibition of adenosine formation and enhanced T-cell activation. We then investigated the therapeutic potential of combining CD73 antagonism with other immune modulatory and chemotherapeutic agents. Combination of mAb19 with a PD-1 inhibitor increased T-cell activation in vitro Interestingly, this effect could be further enhanced with an agonist of the adenosine receptor ADORA3. Adenosine levels were found to be elevated upon doxorubicin treatment in vivo, which could be blocked by CD73 inhibition. Combining CD73 antagonism with doxorubicin resulted in superior responses in vivo Furthermore, a retrospective analysis of rectal cancer patient samples demonstrated an upregulation of the adenosine pathway upon chemoradiation, providing further rationale for combining CD73 inhibition with chemotherapeutic agents.This study demonstrates the ability of a novel CD73 antibody to enhance T-cell function through the potent suppression of adenosine levels. In addition, the data highlight combination opportunities with standard of care therapies as well as with an ADORA3 receptor agonist to treat patients with solid tumors.

Performance of 16S Metagenomic Profiling in Formalin-Fixed Paraffin-Embedded versus Fresh-Frozen Colorectal Cancer Tissues

Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most widely available clinical material to study colorectal cancer (CRC). However, the accuracy and clinical validity of FFPE microbiome profiling in CRC is uncertain. Here, we compared the microbial composition of 10 paired fresh-frozen (FF) and FFPE CRC tissues using 16S rRNA sequencing and RNA-ISH. Both sample types showed different microbial diversity and composition. FF samples were enriched in archaea and representative CRC-associated bacteria, such as Firmicutes, Bacteroidetes and Fusobacteria. Conversely, FFPE samples were mainly enriched in typical contaminants, such as Sphingomonadales and Rhodobacterales. RNA-ISH in FFPE tissues confirmed the presence of CRC-associated bacteria, such as Fusobacterium and Bacteroides, as well as Propionibacterium allowing discrimination between tumor-associated and contaminant taxa. An internal quality index showed that the degree of similarity within sample pairs inversely correlated with the dominance of contaminant taxa. Given the importance of FFPE specimens for larger studies in human cancer genomics, our findings may provide useful indications on potential confounding factors to consider for accurate and reproducible metagenomics analyses.

Association of CD2AP neuronal deposits with Braak neurofibrillary stage in Alzheimer's disease

Genome-wide association studies have described several genes as genetic susceptibility loci for Alzheimer's disease (AD). Among them, CD2AP encodes CD2-associated protein, a scaffold protein implicated in dynamic actin remodeling and membrane trafficking during endocytosis and cytokinesis. Although a clear link between CD2AP defects and glomerular pathology has been described, little is known about the function of CD2AP in the brain. The aim of this study was to analyze the distribution of CD2AP in the AD brain and its potential associations with tau aggregation and β-amyloid (Aβ) deposition. First, we performed immunohistochemical analysis of CD2AP expression in brain tissue from AD patients and controls (N = 60). Our results showed granular CD2AP immunoreactivity in the human brain endothelium in all samples. In AD cases, no CD2AP was found to be associated with Aβ deposits in vessels or parenchymal plaques. CD2AP neuronal inclusions similar to neurofibrillary tangles (NFT) and neuropil thread-like deposits were found only in AD samples. Moreover, immunofluorescence analysis revealed that CD2AP colocalized with pTau. Regarding CD2AP neuronal distribution, a hierarchical progression from the entorhinal to the temporal and occipital cortex was detected. We found that CD2AP immunodetection in neurons was strongly and positively associated with Braak neurofibrillary stage, independent of age and other pathological hallmarks. To further investigate the association between pTau and CD2AP, we included samples from cases of primary tauopathies (corticobasal degeneration [CBD], progressive supranuclear palsy [PSP], and Pick's disease [PiD]) in our study. Among these cases, CD2AP positivity was only found in PiD samples as neurofibrillary tangle-like and Pick body-like deposits, whereas no neuronal CD2AP deposits were detected in PSP or CBD samples, which suggested an association of CD2AP neuronal expression with 3R-Tau-diseases. In conclusion, our findings open a new road to investigate the complex cellular mechanism underlying the tangle conformation and tau pathology in the brain.

Severe SARS-CoV-2 placenta infection can impact neonatal outcome in the absence of vertical transmission

The effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the pathophysiology of the placenta and its impact on pregnancy outcome has not yet been fully elucidated. Here, we present a comprehensive clinical, morphological, and molecular analysis of placental tissues from pregnant women with and without SARS-CoV-2 infection. SARS-CoV-2 could be detected in half of placental tissues from SARS-CoV-2-positive women. The presence of the virus was not associated with any distinctive pathological, maternal, or neonatal outcome features. SARS-CoV-2 tissue load was low in all but one patient who exhibited severe placental damage leading to neonatal neurological manifestations. The placental transcriptional response induced by high viral load of SARS-CoV-2 showed an immunopathology phenotype similar to autopsy lung tissues from patients with severe coronavirus disease 2019. This finding contrasted with the lack of inflammatory response in placental tissues from SARS-CoV-2-positive women with low viral tissue load and from SARS-CoV-2-negative women. Importantly, no evidence of vertical transmission of SARS-CoV-2 was found in any newborns, suggesting that the placenta may be an effective maternal-neonatal barrier against the virus even in the presence of severe infection. Our observations suggest that severe placental damage induced by the virus may be detrimental for the neonate independently of vertical transmission.

Immune microenvironment characterisation and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer

Despite their recognised role in HER2-positive (HER2+) breast cancer (BC), the composition, localisation and functional orientation of immune cells within tumour microenvironment, as well as its dynamics during anti-HER2 treatment, is largely unknown. We here investigate changes in tumour-immune contexture, as assessed by stromal tumour-infiltrating lymphocytes (sTILs) and by multiplexed spatial cellular phenotyping, during treatment with lapatinib-trastuzumab in HER2+ BC patients (PAMELA trial). Moreover, we evaluate the relationship of tumour-immune contexture with hormone receptor status, intrinsic subtype and immune-related gene expression. sTIL levels increase after 2 weeks of HER2 blockade in HR-negative disease and HER2-enriched subtype. This is linked to a concomitant increase in cell density of all four immune subpopulations (CD3+, CD4+, CD8+, Foxp3+). Moreover, immune contexture analysis showed that immune cells spatially interacting with tumour cells have the strongest association with response to anti-HER2 treatment. Subsequently, sTILs consistently decrease at the surgery in patients achieving pathologic complete response, whereas most residual tumours at surgery remain inflamed, possibly reflecting a progressive loss of function of T cells. Understanding the features of the resulting tumour immunosuppressive microenvironment has crucial implications for the design of new strategies to de-escalate or escalate systemic therapy in early-stage HER2+ BC.

Immune cell profiling of the cerebrospinal fluid enables the characterization of the brain metastasis microenvironment

Brain metastases are the most common tumor of the brain with a dismal prognosis. A fraction of patients with brain metastasis benefit from treatment with immune checkpoint inhibitors (ICI) and the degree and phenotype of the immune cell infiltration has been used to predict response to ICI. However, the anatomical location of brain lesions limits access to tumor material to characterize the immune phenotype. Here, we characterize immune cells present in brain lesions and matched cerebrospinal fluid (CSF) using single-cell RNA sequencing combined with T cell receptor genotyping. Tumor immune infiltration and specifically CD8⁺ T cell infiltration can be discerned through the analysis of the CSF. Consistently, identical T cell receptor clonotypes are detected in brain lesions and CSF, confirming cell exchange between these compartments. The analysis of immune cells of the CSF can provide a non-invasive alternative to predict the response to ICI, as well as identify the T cell receptor clonotypes present in brain metastasis.

The use of CSF for diagnosis of metastatic brain tumors could be of clinical and patient benefit. Here the authors undertake a single-cell RNA analysis of CSF and brain to determine whether the phenotype in the CSF is reflective of the phenotype in the tumor.

Fusobacterium nucleatum persistence and risk of recurrence after preoperative treatment in locally advanced rectal cancer

BACKGROUND

Accumulating evidence has identified Fusobacterium as an important pathogenic gut bacterium associated with colorectal cancer. Nevertheless, only limited data exist about the role of this bacterium in locally advanced rectal cancer (LARC). In this study, we quantified Fusobacterium nucleatum in untreated and post-neoadjuvant chemoradiotherapy (nCRT) samples from LARC patients and investigated its association with therapy response and survival.

PATIENTS AND METHODS

A total of 254 samples from 143 patients with rectal adenocarcinomas were analyzed for the presence and abundance of F. nucleatum using RNA in situ hybridization and digital image analysis. Assay accuracy was determined using infected cell lines and tumor samples with available quantitative PCR data. We studied the impact of F. nucleatum load on pathologic complete response and relapse-free survival. Treatment-induced changes were evaluated in paired pre- and post-nCRT samples (n = 71). Finally, tumor microenvironment changes during nCRT were assessed in paired samples (n = 45) by immune contexture analysis.

RESULTS

F. nucleatum tissue levels by RNA in situ hybridization strongly correlated with quantitative PCR (r = 0.804, P < 0.001). F. nucleatum abundance was higher in untreated [median, 7.4; 95% confidence interval (3.7-16.2)] compared with treated [median, 1.6; 95% confidence interval (1.3-2.4)] tumors (P <0.001) with 58% (73/126) and 26% (22/85) positive tumors, respectively (P < 0.001). Baseline F. nucleatum levels were not associated with pathologic complete response. F. nucleatum positivity after nCRT, but not baseline status, significantly increased risk of relapse [hazard ratio = 7.5, 95% confidence interval (3.0-19.0); P < 0.001]. Tumors that turned F. nucleatum-negative after nCRT had a strong increase in CD8+ T cells post-nCRT (P < 0.001), while those that persisted F. nucleatum-positive after nCRT lacked CD8+ T cells induction in post-nCRT samples compared with baseline (P = 0.69).

CONCLUSION

F. nucleatum persistence post-nCRT is associated with high relapse rates in LARC, potentially linked to suppression of immune cytotoxicity.

Sequential immunohistochemistry and virtual image reconstruction using a single slide for quantitative KI67 measurement in breast cancer

Objective

Ki67 is a prognostic and predictive marker in breast cancer (BC). However, manual scoring (MS) by visual assessment suffers from high inter-observer variability which limits its clinical use. Here, we developed a new digital image analysis (DIA) workflow, named KiQuant for automated scoring of Ki67 and investigated its equivalence with standard pathologist's assessment.

Methods

Sequential immunohistochemistry of Ki67 and cytokeratin, for precise tumor cell recognition, were performed in the same section of 5 tissue microarrays containing 329 tumor cores from different breast cancer subtypes. Slides were digitalized and subjected to DIA and MS for Ki67 assessment. The intraclass correlation coefficient (ICC) and Bland-Altman plot were used to evaluate inter-observer reproducibility. The Kaplan-Meier analysis was used to determine the prognostic potential.

Results

KiQuant showed an excellent correlation with MS (ICC:0.905,95%CI:0.878–0.926) with satisfactory inter-run (ICC:0.917,95%CI:0.884–0.942) and inter-antibody reproducibilities (ICC:0.886,95%CI:0.820–0.929). The distance between KiQuant and MS increased with the magnitude of Ki67 measurement and positively correlated with analyzed tumor area and breast cancer subtype. Agreement rates between KiQuant and MS within the clinically relevant 14% and 30% cut-off points ranged from 33% to 44% with modest interobserver reproducibility below the 20% cut-off (0.606, 95%CI:0.467–0.727). High Ki67 by KiQuant correlated with worse outcome in all BC and in the luminal subtype (P = 0.028 and P = 0.043, respectively). For MS, the association with survival was significant only in 1 out of 3 observers.

Conclusions

KiQuant represents an easy and accurate methodology for Ki67 measurement providing a step toward utilizing Ki67 in the clinical setting.

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Automated Ki67 scoring workflow improved reproducibility.

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Sequential immunohistochemistry in the same section for precise cell recognition.

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Use of a tumor mask for automatic tumor region selection.

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Outperform pathologist-based Ki67 scoring in prognostic prediction.

Preclinical Activity of PI3K Inhibitor Copanlisib in Gastrointestinal Stromal Tumor

KIT or PDGFRA gain-of-function mutations are the primary drivers of gastrointestinal stromal tumor (GIST) growth and progression throughout the disease course. The PI3K/mTOR pathway is critically involved in the transduction of KIT/PDGFRA oncogenic signaling regardless of the type of primary and secondary mutations, and therefore emerges as a relevant targetable node in GIST biology. We evaluated in GIST preclinical models the antitumor activity of copanlisib, a novel pan-class-I PI3K inhibitor with predominant activity against p110α and p110δ isoforms, as single-agent and in combination with first-line KIT inhibitor imatinib. In vitro studies undertaken in one imatinib-sensitive (GIST-T1) and two imatinib-resistant (GIST-T1/670 and GIST430/654) GIST cell models showed that single-agent copanlisib effectively suppressed PI3K pathway activation leading to decreased cell viability and proliferation in both imatinib-sensitive and -resistant cells irrespective of the type of primary or secondary KIT mutations. Simultaneous PI3K and KIT inhibition with copanlisib and imatinib resulted in enhanced impairment of cell viability in both imatinib-sensitive and -resistant GIST cell models, although apoptosis was mostly triggered in GIST-T1. Single-agent copanlisib inhibited GIST growth in vivo, and conjoined inhibition of PI3K and KIT was the most active therapeutic intervention in imatinib-sensitive GIST-T1 xenografts. IHC stain for cleaved-caspase 3 and phospho-S6 support a predominant antiproliferative effect of copanlisib in GIST. In conclusion, copanlisib has single-agent antitumor activity in GIST regardless KIT mutational status or sensitivity to imatinib. Effective KIT inhibition is necessary to achieve synergistic or additive effects with the combination of imatinib and any given PI3K/mTOR pathway inhibition.

Targeted multiplex proteomics for molecular prescreening and biomarker discovery in metastatic colorectal cancer

Protein biomarkers are widely used in cancer diagnosis, prognosis, and prediction of treatment response. Here we introduce the use of targeted multiplex proteomics (TMP) as a tool to simultaneously measure a panel of 54 proteins involved in oncogenic, tumour suppression, drug metabolism and resistance, in patients with metastatic colorectal cancer (mCRC). TMP provided valuable diagnostic information by unmasking an occult neuroendocrine differentiation and identifying a misclassified case based on abnormal proteins phenotype. No significant differences in protein levels between unpaired primary and metastatic samples were observed. Four proteins were found differentially expressed in KRAS-mutant as compared to wild-type tumours (overexpressed in mutant: KRAS, EGFR; overexpressed in wild-type: TOPO1, TOP2A). Survival analyses revealed the association between mesothelin expression and poor overall survival, whereas lack of PTEN protein expression associated with lower progression-free survival with anti-EGFR-based therapy in the first-line setting for patients with RAS wild-type tumour. Finally, outlier analysis identified putative targetable proteins in 65% of patients lacking a targetable genomic alteration. Our data show that TMP constitutes a promising, novel molecular prescreening tool in mCRC to identify protein expression alterations that may impact on patient outcomes and more precisely guide patient eligibility to clinical trials with novel targeted experimental therapies.

Analysis of Fusobacterium persistence and antibiotic response in colorectal cancer

Colorectal cancers comprise a complex mixture of malignant cells, nontransformed cells, and microorganisms. Fusobacterium nucleatum is among the most prevalent bacterial species in colorectal cancer tissues. Here we show that colonization of human colorectal cancers with Fusobacterium and its associated microbiome-including Bacteroides, Selenomonas, and Prevotella species-is maintained in distal metastases, demonstrating microbiome stability between paired primary and metastatic tumors. In situ hybridization analysis revealed that Fusobacterium is predominantly associated with cancer cells in the metastatic lesions. Mouse xenografts of human primary colorectal adenocarcinomas were found to retain viable Fusobacterium and its associated microbiome through successive passages. Treatment of mice bearing a colon cancer xenograft with the antibiotic metronidazole reduced Fusobacterium load, cancer cell proliferation, and overall tumor growth. These observations argue for further investigation of antimicrobial interventions as a potential treatment for patients with Fusobacterium-associated colorectal cancer.

Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914

On September 14, 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

Properties of the Binary Black Hole Merger GW150914

On September 14, 2015, the Laser Interferometer Gravitational-Wave Observatory (LIGO) detected a gravitational-wave transient (GW150914); we characterize the properties of the source and its parameters. The data around the time of the event were analyzed coherently across the LIGO network using a suite of accurate waveform models that describe gravitational waves from a compact binary system in general relativity. GW150914 was produced by a nearly equal mass binary black hole of masses 36_{-4}^{+5}M_{⊙} and 29_{-4}^{+4}M_{⊙}; for each parameter we report the median value and the range of the 90% credible interval. The dimensionless spin magnitude of the more massive black hole is bound to be <0.7 (at 90% probability). The luminosity distance to the source is 410_{-180}^{+160}  Mpc, corresponding to a redshift 0.09_{-0.04}^{+0.03} assuming standard cosmology. The source location is constrained to an annulus section of 610  deg^{2}, primarily in the southern hemisphere. The binary merges into a black hole of mass 62_{-4}^{+4}M_{⊙} and spin 0.67_{-0.07}^{+0.05}. This black hole is significantly more massive than any other inferred from electromagnetic observations in the stellar-mass regime.

GW150914: First results from the search for binary black hole coalescence with Advanced LIGO

On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) simultaneously observed the binary black hole merger GW150914. We report the results of a matched-filter search using relativistic models of compact-object binaries that recovered GW150914 as the most significant event during the coincident observations between the two LIGO detectors from September 12 to October 20, 2015. GW150914 was observed with a matched filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203000 years, equivalent to a significance greater than 5.1 σ.

GW150914: First results from the search for binary black hole coalescence with Advanced LIGO

On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) simultaneously observed the binary black hole merger GW150914. We report the results of a matched-filter search using relativistic models of compact-object binaries that recovered GW150914 as the most significant event during the coincident observations between the two LIGO detectors from September 12 to October 20, 2015. GW150914 was observed with a matched filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203000 years, equivalent to a significance greater than 5.1 σ.

Tests of General Relativity with GW150914

The LIGO detection of GW150914 provides an unprecedented opportunity to study the two-body motion of a compact-object binary in the large-velocity, highly nonlinear regime, and to witness the final merger of the binary and the excitation of uniquely relativistic modes of the gravitational field. We carry out several investigations to determine whether GW150914 is consistent with a binary black-hole merger in general relativity. We find that the final remnant's mass and spin, as determined from the low-frequency (inspiral) and high-frequency (postinspiral) phases of the signal, are mutually consistent with the binary black-hole solution in general relativity. Furthermore, the data following the peak of GW150914 are consistent with the least-damped quasinormal mode inferred from the mass and spin of the remnant black hole. By using waveform models that allow for parametrized general-relativity violations during the inspiral and merger phases, we perform quantitative tests on the gravitational-wave phase in the dynamical regime and we determine the first empirical bounds on several high-order post-Newtonian coefficients. We constrain the graviton Compton wavelength, assuming that gravitons are dispersed in vacuum in the same way as particles with mass, obtaining a 90%-confidence lower bound of 10^{13}  km. In conclusion, within our statistical uncertainties, we find no evidence for violations of general relativity in the genuinely strong-field regime of gravity.

GW150914: Implications for the Stochastic Gravitational-Wave Background from Binary Black Holes

The LIGO detection of the gravitational wave transient GW150914, from the inspiral and merger of two black holes with masses ≳30M_{⊙}, suggests a population of binary black holes with relatively high mass. This observation implies that the stochastic gravitational-wave background from binary black holes, created from the incoherent superposition of all the merging binaries in the Universe, could be higher than previously expected. Using the properties of GW150914, we estimate the energy density of such a background from binary black holes. In the most sensitive part of the Advanced LIGO and Advanced Virgo band for stochastic backgrounds (near 25 Hz), we predict Ω_{GW}(f=25  Hz)=1.1_{-0.9}^{+2.7}×10^{-9} with 90% confidence. This prediction is robustly demonstrated for a variety of formation scenarios with different parameters. The differences between models are small compared to the statistical uncertainty arising from the currently poorly constrained local coalescence rate. We conclude that this background is potentially measurable by the Advanced LIGO and Advanced Virgo detectors operating at their projected final sensitivity.

GW150914: The Advanced LIGO Detectors in the Era of First Discoveries

Following a major upgrade, the two advanced detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) held their first observation run between September 2015 and January 2016. With a strain sensitivity of 10^{-23}/sqrt[Hz] at 100 Hz, the product of observable volume and measurement time exceeded that of all previous runs within the first 16 days of coincident observation. On September 14, 2015, the Advanced LIGO detectors observed a transient gravitational-wave signal determined to be the coalescence of two black holes [B. P. Abbott et al., Phys. Rev. Lett. 116, 061102 (2016)], launching the era of gravitational-wave astronomy. The event, GW150914, was observed with a combined signal-to-noise ratio of 24 in coincidence by the two detectors. Here, we present the main features of the detectors that enabled this observation. At full sensitivity, the Advanced LIGO detectors are designed to deliver another factor of 3 improvement in the signal-to-noise ratio for binary black hole systems similar in mass to GW150914.

Observation of Gravitational Waves from a Binary Black Hole Merger

On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of 1.0×10(-21). It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203,000 years, equivalent to a significance greater than 5.1σ. The source lies at a luminosity distance of 410(-180)(+160)  Mpc corresponding to a redshift z=0.09(-0.04)(+0.03). In the source frame, the initial black hole masses are 36(-4)(+5)M⊙ and 29(-4)(+4)M⊙, and the final black hole mass is 62(-4)(+4)M⊙, with 3.0(-0.5)(+0.5)M⊙c(2) radiated in gravitational waves. All uncertainties define 90% credible intervals. These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO and Advanced Virgo

We present a possible observing scenario for the Advanced LIGO and Advanced Virgo gravitational-wave detectors over the next decade, with the intention of providing information to the astronomy community to facilitate planning for multi-messenger astronomy with gravitational waves. We determine the expected sensitivity of the network to transient gravitational-wave signals, and study the capability of the network to determine the sky location of the source. We report our findings for gravitational-wave transients, with particular focus on gravitational-wave signals from the inspiral of binary neutron-star systems, which are considered the most promising for multi-messenger astronomy. The ability to localize the sources of the detected signals depends on the geographical distribution of the detectors and their relative sensitivity, and 90% credible regions can be as large as thousands of square degrees when only two sensitive detectors are operational. Determining the sky position of a significant fraction of detected signals to areas of 5 deg2 to 20 deg2 will require at least three detectors of sensitivity within a factor of ∼ 2 of each other and with a broad frequency bandwidth. Should the third LIGO detector be relocated to India as expected, a significant fraction of gravitational-wave signals will be localized to a few square degrees by gravitational-wave observations alone.