Analysis of cell free DNA to predict outcome to bevacizumab therapy in colorectal cancer patients.

To predict outcome to combination bevacizumab (BVZ) therapy, we employed cell-free DNA (cfDNA) to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients. Low-coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples, collected from 74 mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444), and analysed for CIN and NFs. A validation cohort of plasma samples from the University Medical Center Mannheim (UMM) was similarly profiled. 61 AC-ANGIOPREDICT plasma samples collected before and following BVZ treatment were selected for targeted methylation sequencing. Using cfDNA CIN profiles, AC-ANGIOPREDICT samples were subtyped with 92.3% accuracy into low and high CIN clusters, with good concordance observed between matched plasma and tumor. Improved survival was observed in CIN-high patients. Plasma-based CIN clustering was validated in the UMM cohort. Methylation profiling identified differences in CIN-low vs. CIN high (AUC = 0.87). Moreover, significant methylation score decreases following BVZ was associated with improved outcome (p = 0.013). Analysis of CIN, NFs and methylation profiles from cfDNA in plasma samples facilitates stratification into CIN clusters which inform patient response to treatment.

Intracranial thrombus composition is associated with occlusion location and endovascular treatment outcomes: results from ITACAT multicenter study.

BACKGROUND: The impact of thrombolytics directed towards different thrombus components regarding site of occlusion in combination with mechanical thrombectomy (MT) to achieve endovascular complete recanalization is unclear. METHODS: Retrospective analysis of a prospective database in two stroke centers. Intracranial thrombi retrieved by MT were analyzed using hematoxylin-eosin staining for fibrin and red blood cell proportions, and CD61 immunostaining for platelets proportion in thrombus (PLTPT) assessment. Thrombi composition, baseline variables, etiology, treatment features and occlusion location were analyzed. RESULTS: Overall, 221 patients completed the per protocol analysis and 110 cases achieved a final expanded Thrombolysis in Cerebral Infarction (eTICI) 3 (49%) of which 70 were MT (32%) by first pass effect (FPE). Thrombi from medium distal vessel occlusions had higher PLTPT compared with thrombi from proximal large vessel occlusions (68% vs 61%, P=0.026). In particular, middle cerebral artery M2-M3 segment thrombi had the highest PLTPT (70%), and basilar artery thrombi the lowest PLTPT (41%). After logistic regression analysis adjusted for occlusion location and intravenous fibrinolysis, lower baseline National Institutes of Health Stroke Scale score (adjusted OR (aOR) 0.95, 95% CI 0.913 to 0.998) and PLTPT (aOR 0.97, 95% CI 0.963 to 0.993) were independently associated with FPE. Fewer MT passes (aOR 0.67, 95% CI 0.538 to 0.842) and platelet poor thrombus (<62% PLTPT; aOR 2.39, 95% CI 1.288 to 4.440) were independently associated with final eTICI 3. CONCLUSIONS: Occlusion location might be a surrogate parameter for thrombus composition. Platelet poor clots and fewer MT passes were independently associated with complete endovascular recanalization. Clinical trials testing the benefits of combining selective intra-arterial platelet antagonists with MT to improve endovascular outcomes are warranted.

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.

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.

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 ß-amyloid (Aß) 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 Aß 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.

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.

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.

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.

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.

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.

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.