Inverse FASN and LDHA correlation drives metabolic resistance in breast cancer.

BACKGROUND: Breast cancer manifests as a heterogeneous pathology marked by complex metabolic reprogramming essential to satisfy its energy demands. Oncogenic signals boost the metabolism, modifying fatty acid synthesis and glucose use from the onset to progression and therapy resistant-forms. However, the exact contribution of metabolic dependencies during tumor evolution remains unclear. METHODS: In this study, we elucidate the connection between FASN and LDHA, pivotal metabolic genes, and their correlation with tumor grade and therapy response using datasets from public repositories. Subsequently, we evaluated the metabolic and proliferative functions upon FASN and LDHA inhibition in breast cancer models. Lastly, we integrated metabolomic and lipidomic analysis to define the contributions of metabolites, lipids, and precursors to the metabolic phenotypes. RESULTS: Collectively, our findings indicate metabolic shifts during breast cancer progression, unvealling two distinct functional energy phenotypes associated with aggressiveness and therapy response. Specifically, FASN exhibits reduced expression in advance-grade tumors and therapy-resistant forms, whereas LDHA demonstrates higher expression. Additionally, the biological and metabolic impact of blocking the enzymatic activity of FASN and LDHA was correlated with resistant conditions. CONCLUSIONS: These observations emphasize the intrinsic metabolic heterogeneity within breast cancer, thereby highlighting the relevance of metabolic interventions in the field of precision medicine.

Immune cell infiltration and inflammatory landscape in primary brain tumours.

BACKGROUND: Primary malignant brain tumours are more than one-third of all brain tumours and despite the molecular investigation to identify cancer driver mutations, the current therapeutic options available are challenging due to high intratumour heterogeneity. In addition, an immunosuppressive and inflammatory tumour microenvironment strengthens cancer progression. Therefore, we defined an immune and inflammatory profiling of meningioma and glial tumours to elucidate the role of the immune infiltration in these cancer types. METHODS: Using tissue microarrays of 158 brain tumour samples, we assessed CD3, CD4, CD8, CD20, CD138, Granzyme B (GzmB), 5-Lipoxygenase (5-LOX), Programmed Death-Ligand 1 (PD-L1), O-6-Methylguanine-DNA Methyltransferase (MGMT) and Transglutaminase 2 (TG2) expression by immunohistochemistry (IHC). IHC results were correlated using a Spearman correlation matrix. Transcript expression, correlation, and overall survival (OS) analyses were evaluated using public datasets available on GEPIA2 in Glioblastoma (GBM) and Lower Grade Glioma (LGG) cohorts. RESULTS: Seven out of ten markers showed a significantly different IHC expression in at least one of the evaluated cohorts whereas CD3, CD4 and 5-LOX were differentially expressed between GBMs and astrocytomas. Correlation matrix analysis revealed that 5-LOX and GzmB expression were associated in both meningiomas and GBMs, whereas 5-LOX expression was significantly and positively correlated to TG2 in both meningioma and astrocytoma cohorts. These findings were confirmed with the correlation analysis of TCGA-GBM and LGG datasets. Profiling of mRNA levels indicated a significant increase in CD3 (CD3D, CD3E), and CD138 (SDC1) expression in GBM compared to control tissues. CD4 and 5-LOX (ALOX5) mRNA levels were significantly more expressed in tumour samples than in normal tissues in both GBM and LGG. In GBM cohort, GzmB (GZMB), SDC1 and MGMT gene expression predicted a poor overall survival (OS). Moreover, in LGG cohort, an increased expression of CD3 (CD3D, CD3E, CD3G), CD8 (CD8A), GZMB, CD20 (MS4A1), SDC1, PD-L1, ALOX5, and TG2 (TGM2) genes was associated with worse OS. CONCLUSIONS: Our data have revealed that there is a positive and significant correlation between the expression of 5-LOX and GzmB, both at RNA and protein level. Further evaluation is needed to understand the interplay of 5-LOX and immune infiltration in glioma progression.

Machine learning-based radiomics analysis in predicting RAS mutational status using magnetic resonance imaging.

PURPOSE: To assess the efficacy of radiomics features, obtained by magnetic resonance imaging (MRI) with hepatospecific contrast agent, in pre-surgical setting, to predict RAS mutational status in liver metastases. METHODS: Patients with MRI in pre-surgical setting were enrolled in a retrospective study. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. The features were extracted considering the agreement with the Imaging Biomarker Standardization Initiative (IBSI). Balancing was performed through synthesis of samples for the underrepresented classes using the self-adaptive synthetic oversampling (SASYNO) approach. Inter- and intraclass correlation coefficients (ICC) were calculated to assess the between-observer and within-observer reproducibility of all radiomics characteristics. For continuous variables, nonparametric Wilcoxon-Mann-Whitney test was utilized. Benjamini and Hochberg's false discovery rate (FDR) adjustment for multiple testing was used. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. Moreover, features selection were performed before and after a normalized procedure using two different methods (3-sigma and z-score). McNemar test was used to assess differences statistically significant between dichotomic tables. All statistical procedures were done using MATLAB R2021b Statistics and Machine Toolbox (MathWorks, Natick, MA, USA). RESULTS: Seven normalized radiomics features, extracted from arterial phase, 11 normalized radiomics features, from portal phase, 12 normalized radiomics features from hepatobiliary phase and 12 normalized features from T2-W SPACE sequence were robust predictors of RAS mutational status. The multivariate analysis increased significantly the accuracy in RAS prediction when a LRM was used, combining 12 robust normalized features extracted by VIBE hepatobiliary phase reaching an accuracy of 99%, a sensitivity 97%, a specificity of 100%, a PPV of 100% and a NPV of 98%. No statistically significant increase was obtained, considering the tested classifiers DT, KNN and SVM, both without normalization and with normalization methods. CONCLUSIONS: Normalized approach in MRI radiomics analysis allows to predict RAS mutational status.

Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction.

PURPOSE: To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases. METHODS: Patient selection in a retrospective study was carried out from January 2018 to May 2021 considering the following inclusion criteria: patients subjected to surgical resection for liver metastases; proven pathological liver metastases; patients subjected to enhanced CT examination in the presurgical setting with a good quality of images; and RAS assessment as standard reference. A total of 851 radiomics features were extracted using the PyRadiomics Python package from the Slicer 3D image computing platform after slice-by-slice segmentation on CT portal phase by two expert radiologists of each individual liver metastasis performed first independently by the individual reader and then in consensus. Balancing technique was performed, and inter- and intraclass correlation coefficients were calculated to assess the between-observer and within-observer reproducibility of features. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers were considered. Moreover, features selection was performed before and after a normalized procedure using two different methods (3-sigma and z-score). RESULTS: Seventy-seven liver metastases in 28 patients with a mean age of 60 years (range 40-80 years) were analyzed. The best predictors, at univariate analysis for both normalized procedures, were original_shape_Maximum2DDiameter and wavelet_HLL_glcm_InverseVariance that reached an accuracy of 80%, an AUC ≥ 0.75, a sensitivity ≥ 80% and a specificity ≥ 70% (p value < < 0.01). However, a multivariate analysis significantly increased the accuracy in RAS prediction when a linear regression model (LRM) was used. The best performance was obtained using a LRM combining linearly 12 robust features after a z-score normalization procedure: AUC of 0.953, accuracy 98%, sensitivity 96%, specificity of 100%, PPV 100% and NPV 96% (p value < < 0.01). No statistically significant increase was obtained considering the tested machine learning both without normalization and with normalization methods. CONCLUSIONS: Normalized approach in CT radiomics analysis allows to predict RAS mutational status in colorectal liver metastases patients.

Plexiform Fibromyxoma in the Stomach: Immunohistochemical Profile and Comprehensive Genetic Characterization.

Plexiform fibromyxoma (PF), also referred to as plexiform angiomyxoid myofibroblast tumor, is an exceedingly rare mesenchymal neoplasm primarily affecting the stomach. Herein, we present a case of PF diagnosed in a 71-year-old male with a history of lung cancer, initially suspected to have a gastrointestinal stromal tumor (GIST) of the stomach, who subsequently underwent subtotal gastrectomy. The histopathological and molecular features of the tumor, including mutations in ABL1, CCND1, CSF1R, FGFR4, KDR, and MALAT1-GLI1 fusion, are elucidated and discussed in the context of diagnostic, prognostic, and therapeutic considerations.

Oligo-metastatic neoPlasms from the gastro-intestinal tract: iDentIfiCaTIon of cliNical and molecular drivers: the PREDICTION study.

BACKGROUND: Metastatic disease in tumors originating from the gastrointestinal tract can exhibit varying degrees of tumor burden at presentation. Some patients follow a less aggressive disease course, characterized by a limited number of metastatic sites, referred to as "oligo-metastatic disease" (OMD). The precise biological characteristics that define the oligometastatic behavior remain uncertain. In this study, we present a protocol designed to prospectively identify OMD, with the aim of proposing novel therapeutic approaches and monitoring strategies. METHODS: The PREDICTION study is a monocentric, prospective, observational investigation. Enrolled patients will receive standard treatment, while translational activities will involve analysis of the tumor microenvironment and genomic profiling using immunohistochemistry and next-generation sequencing, respectively. The first primary objective (descriptive) is to determine the prevalence of biological characteristics in OMD derived from gastrointestinal tract neoplasms, including high genetic concordance between primary tumors and metastases, a significant infiltration of T lymphocytes, and the absence of clonal evolution favoring specific driver genes (KRAS and PIK3CA). The second co-primary objective (analytic) is to identify a prognostic score for true OMD, with a primary focus on metastatic colorectal cancer. The score will comprise genetic concordance (> 80%), high T-lymphocyte infiltration, and the absence of clonal evolution favoring driver genes. It is hypothesized that patients with true OMD (score 3+) will have a lower rate of progression/recurrence within one year (20%) compared to those with false OMD (80%). The endpoint of the co-primary objective is the rate of recurrence/progression at one year. Considering a reasonable probability (60%) of the three factors occurring simultaneously in true OMD (score 3+), using a significance level of α = 0.05 and a test power of 90%, the study requires a minimum enrollment of 32 patients. DISCUSSION: Few studies have explored the precise genetic and biological features of OMD thus far. In clinical settings, the diagnosis of OMD is typically made retrospectively, as some patients who undergo intensive treatment for oligometastases develop polymetastatic diseases within a year, while others do not experience disease progression (true OMD). In the coming years, the identification of true OMD will allow us to employ more personalized and comprehensive strategies in cancer treatment. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT05806151.

Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor. METHODS: Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy. RESULTS: By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs. CONCLUSIONS: These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.

Aberrant Expression of Long Non Coding RNA HOTAIR and De-Regulation of the Paralogous 13 HOX Genes Are Strongly Associated with Aggressive Behavior of Gastro-Entero-Pancreatic Neuroendocrine Tumors.

Gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NENs) are rare diseases occurring in the gastrointestinal tract and pancreas. They are characterized by the loss of epithelial tubular gland elements, and by the increased expression of neuroendocrine markers. GEP-NENs are subdivided into two histo-pathological types, gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) and gastro-entero-pancreatic neuroendocrine carcinomas (GEP-NECs). According to WHO 2017 and 2019 classification criteria are graded and staged in four categories, NET-G1, NET-G2, NET-G3, and NEC-G3. The molecular characterization of these tumors can be fundamental for the identification of new diagnostic, prognostic and predictive biomarkers. The main purpose of this study was to analyze the expression of the paralogous 13 HOX genes, normally involved in embryogenic development and frequently deregulated in human cancers, and of the HOX regulating lncRNA HOTAIR in GEP-NENs. The expression of HOX genes is gradually lost in the transition from GEP NET G1 to NET/NEC G3 tumors, while HOTAIR expression, inversely correlated with HOX genes expression and weakly expressed in low-grade GEP NENs, becomes aberrant in NET G3 and NEC G3 categories. Our data highlights their potential role in the molecular stratification of GEP-NENs by suggesting new prognostic markers and potential therapeutic targets.

Estrogen Induces Selective Transcription of Caveolin1 Variants in Human Breast Cancer through Estrogen Responsive Element-Dependent Mechanisms.

The estrogen receptor (ER) signaling regulates numerous physiological processes mainly through activation of gene transcription (genomic pathways). Caveolin1 (CAV1) is a membrane-resident protein that behaves as platform to enable different signaling molecules and receptors for membrane-initiated pathways. CAV1 directly interacts with ERs and allows their localization on membrane with consequent activation of ER-non-genomic pathways. Loss of CAV1 function is a common feature of different types of cancers, including breast cancer. Two protein isoforms, CAV1α and CAV1ß, derived from two alternative translation initiation sites, are commonly described for this gene. However, the exact transcriptional regulation underlying CAV1 expression pattern is poorly elucidated. In this study, we dissect the molecular mechanism involved in selective expression of CAV1ß isoform, induced by estrogens and downregulated in breast cancer. Luciferase assays and Chromatin immunoprecipitation demonstrate that transcriptional activation is triggered by estrogen-responsive elements embedded in CAV1 intragenic regions and DNA-binding of estrogen-ER complexes. This regulatory control is dynamically established by local chromatin changes, as proved by the occurrence of histone H3 methylation/demethylation events and association of modifier proteins as well as modification of H3 acetylation status. Thus, we demonstrate for the first time, an estrogen-ERs-dependent regulatory circuit sustaining selective CAV1ß expression.

Posterior HOX genes and HOTAIR expression in the proximal and distal colon cancer pathogenesis.

BACKGROUND: Increasing evidences showed that the location of the primary tumor on the right (proximal) or left (distal) side of the colon have a prognostic/predictive value for colon cancer patients. However, the understanding of the molecular mechanisms that contribute to the pathogenesis in different location of colon is still unclear. Probably an important role could be played by genes that control the spatial-temporal development of bodily structures, such as HOX genes. METHODS: The main purpose of this study was to analyze the expression of the paralogous 13 HOX genes and of the HOX regulating lncRNA HOTAIR in distal and proximal CRC cases. We have carried out a Tissue Micro Array with left and right CRC samples associated with all clinical-pathological parameters of patients. The expression of HOX genes was evaluated by immunohistochemistry and the staining of HOTAIR was performed by in situ hybridization using a specifically designed LNA probe. RESULTS: All paralogous 13 HOX genes and HOTAIR are silent in normal tissue and expressed in CRC samples. HOXB13, HOXC13 and HOTAIR showed a statistical association with lymph nodes metastasis (p value = 0.003, p value = 0.05, p value = 0.04). HOXB13, HOXC13 and lncRNA HOTAIR are overexpressed in right CRCs samples (p value < 0 and p value = 0.021). HOTAIR is also strongly correlated with HOXB13 (p value = 0.02) and HOXC13 (p value = 0.042) expression. CONCLUSIONS: Our data highlighted an important role of posterior HOX genes in colorectal cancer carcinogenesis. Specifically, the aberrant expression of the HOXB13, HOXC13 and HOTAIR in proximal colon cancers could add an important dowel in understanding molecular mechanisms related to tumor pathogenesis in this location.

Exploring the Spectrum of VEGF Inhibitors' Toxicities from Systemic to Intra-Vitreal Usage in Medical Practice.

The use of Vascular Endothelial Growth Factor inhibitors (VEGFi) has become prevalent in the field of medicine, given the high incidence of various pathological conditions necessitating VEGF inhibition within the general population. These conditions encompass a range of advanced neoplasms, such as colorectal cancer, non-small cell lung cancer, renal cancer, ovarian cancer, and others, along with ocular diseases. The utilization of VEGFi is not without potential risks and adverse effects, requiring healthcare providers to be well-prepared for identification and management. VEGFi can be broadly categorized into two groups: antibodies or chimeric proteins that specifically target VEGF (bevacizumab, ramucirumab, aflibercept, ranibizumab, and brolucizumab) and non-selective and selective small molecules (sunitinib, sorafenib, cabozantinib, lenvatinib, regorafenib, etc.) designed to impede intracellular signaling of the VEGF receptor (RTKi, receptor tyrosine kinase inhibitors). The presentation and mechanisms of adverse effects resulting from VEGFi depend primarily on this distinction and the route of drug administration (systemic or intra-vitreal). This review provides a thorough examination of the causes, recognition, management, and preventive strategies for VEGFi toxicities with the goal of offering support to oncologists in both clinical practice and the design of clinical trials.

Treatments, prognostic factors, and genetic heterogeneity in advanced cholangiocarcinoma: A multicenter real-world study.

BACKGROUND AND AIMS: Cholangiocarcinoma (CCA), a rare and aggressive hepatobiliary malignancy, presents significant clinical management challenges. Despite rising incidence and evolving treatment options, prognosis remains poor, motivating the exploration of real-world data for enhanced understanding and patient care. METHODS: This multicenter study analyzed data from 120 metastatic CCA patients at three institutions from 2016 to 2023. Kaplan-Meier curves assessed overall survival (OS), while univariate and multivariate analyses evaluated links between clinical variables (age, gender, tumor site, metastatic burden, ECOG performance status, response to first-line chemotherapy) and OS. Genetic profiling was conducted selectively. RESULTS: Enrolled patients had a median age of 68.5 years, with intrahepatic tumors predominant in 79 cases (65.8%). Among 85 patients treated with first-line chemotherapy, cisplatin and gemcitabine (41.1%) was the most common regimen. Notably, one-third received no systemic treatment. After a median 14-month follow-up, 81 CCA-related deaths occurred, with a median survival of 13.1 months. Two clinical variables independently predicted survival: response to first-line chemotherapy (disease control vs. no disease control; HR: 0.27; 95% CI: 0.14-0.50; p < 0.0001) and metastatic involvement (>1 site vs. 1 site; HR: 1.99; 95% CI: 1.04-3.80; p = 0.0366). The three most common genetic alterations involved the ARID1A, tp53, and CDKN2A genes. CONCLUSIONS: Advanced CCA displays aggressive clinical behavior, emphasizing the need for treatments beyond chemotherapy. Genetic diversity supports potential personalized therapies. Collaborative research and deeper CCA biology understanding are crucial to enhance patient outcomes in this challenging malignancy.

Targeting HDAC2-Mediated Immune Regulation to Overcome Therapeutic Resistance in Mutant Colorectal Cancer.

A large body of clinical and experimental evidence indicates that colorectal cancer is one of the most common multifactorial diseases. Although some useful prognostic biomarkers for clinical therapy have already been identified, it is still difficult to characterize a therapeutic signature that is able to define the most appropriate treatment. Gene expression levels of the epigenetic regulator histone deacetylase 2 (HDAC2) are deregulated in colorectal cancer, and this deregulation is tightly associated with immune dysfunction. By interrogating bioinformatic databases, we identified patients who presented simultaneous alterations in HDAC2, class II major histocompatibility complex transactivator (CIITA), and beta-2 microglobulin (B2M) genes based on mutation levels, structural variants, and RNA expression levels. We found that B2M plays an important role in these alterations and that mutations in this gene are potentially oncogenic. The dysregulated mRNA expression levels of HDAC2 were reported in about 5% of the profiled patients, while other specific alterations were described for CIITA. By analyzing immune infiltrates, we then identified correlations among these three genes in colorectal cancer patients and differential infiltration levels of genetic variants, suggesting that HDAC2 may have an indirect immune-related role in specific subgroups of immune infiltrates. Using this approach to carry out extensive immunological signature studies could provide further clinical information that is relevant to more resistant forms of colorectal cancer.

Role of shrinkage in esophageal-gastric junction cancer.

The esophagus undergoes shrinkage after resection and fixation. The surgical in situ margin is greater than the specimen margin, measured by the pathologist. The length of disease-free margins is critical to therapeutic planning. We propose specimen fixing to avoid discrepancies between the operative finding and the pathological result.

Corrigendum: Immune checkpoint inhibitor therapy increases systemic SDF-1, cardiac DAMPs Fibronectin-EDA, S100/Calgranulin, galectine-3, and NLRP3-MyD88-chemokine pathways.

[This corrects the article DOI: 10.3389/fcvm.2022.930797.].

The Impact of O6-Methylguanine-DNA Methyltransferase (MGMT) Promoter Methylation on the Outcomes of Patients with Leiomyosarcoma Treated with Dacarbazine.

Dacarbazine is an important drug in the therapeutic landscape of leiomyosarcoma (LMS). Alkylating agents are subjected to resistance mechanisms based on anti-apoptotic pathways and repair mechanisms, including the DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT). In this retrospective study, the methylation status of the MGMT promoter in histological tumor samples from patients with LMS, dacarbazine-based regimens-treated, was measured and correlated with clinical outcomes aimed at optimizing the use of dacarbazine in soft tissue sarcomas. The patients with unmethylated MGMT had better outcomes than those with methylated MGMT. Patients without MGMT methylation had better Progression Free Survival (PFS) when aged ≥62 years compared to those aged <62 years, while PFS of patients with methylated MGMT was less favorable independently of age (p = 0.0054). The patients without a methylated MGMT gene had higher Disease control rate (DCR). These results are not in agreement with the role of the methylated MGMT gene in other tumors, and with this study, we demonstrated the correlation between methylated MGMT and poor prognosis; despite that, sample smallness, heterogeneity of LMS and of treatment history could be selection bias. Predictive markers of response to chemotherapies in sarcomas remain an unmet need.

Oligo-Metastatic Cancers: Putative Biomarkers, Emerging Challenges and New Perspectives.

Some cancer patients display a less aggressive form of metastatic disease, characterized by a low tumor burden and involving a smaller number of sites, which is referred to as "oligometastatic disease" (OMD). This review discusses new biomarkers, as well as methodological challenges and perspectives characterizing OMD. Recent studies have revealed that specific microRNA profiles, chromosome patterns, driver gene mutations (ERBB2, PBRM1, SETD2, KRAS, PIK3CA, SMAD4), polymorphisms (TCF7L2), and levels of immune cell infiltration into metastases, depending on the tumor type, are associated with an oligometastatic behavior. This suggests that OMD could be a distinct disease with specific biological and molecular characteristics. Therefore, the heterogeneity of initial tumor burden and inclusion of OMD patients in clinical trials pose a crucial methodological question that requires responses in the near future. Additionally, a solid understanding of the molecular and biological features of OMD will be necessary to support and complete the clinical staging systems, enabling a better distinction of metastatic behavior and tailored treatments.

Multi-Institutional Evaluation of Pathologists' Assessment Compared to Immunoscore.

BACKGROUND: The Immunoscore (IS) is a quantitative digital pathology assay that evaluates the immune response in cancer patients. This study reports on the reproducibility of pathologists' visual assessment of CD3+- and CD8+-stained colon tumors, compared to IS quantification. METHODS: An international group of expert pathologists evaluated 540 images from 270 randomly selected colon cancer (CC) cases. Concordance between pathologists' T-score, corresponding hematoxylin-eosin (H&E) slides, and the digital IS was evaluated for two- and three-category IS. RESULTS: Non-concordant T-scores were reported in more than 92% of cases. Disagreement between semi-quantitative visual assessment of T-score and the reference IS was observed in 91% and 96% of cases before and after training, respectively. Statistical analyses showed that the concordance index between pathologists and the digital IS was weak in two- and three-category IS, respectively. After training, 42% of cases had a change in T-score, but no improvement was observed with a Kappa of 0.465 and 0.374. For the 20% of patients around the cut points, no concordance was observed between pathologists and digital pathology analysis in both two- and three-category IS, before or after training (all Kappa < 0.12). CONCLUSIONS: The standardized IS assay outperformed expert pathologists' T-score evaluation in the clinical setting. This study demonstrates that digital pathology, in particular digital IS, represents a novel generation of immune pathology tools for reproducible and quantitative assessment of tumor-infiltrated immune cell subtypes.

Immune checkpoint inhibitor therapy increases systemic SDF-1, cardiac DAMPs Fibronectin-EDA, S100/Calgranulin, galectine-3, and NLRP3-MyD88-chemokine pathways.

Background: Immune checkpoint inhibitors (ICIs) have significantly changed the oncology clinic in recent years, improving survival expectations in cancer patients. ICI therapy have a broad spectrum of side effects from endocrinopathies to cardiovascular diseases. In this study, pro-inflammatory and pro-fibrotic effects of short-term ICIs therapy in preclinical models were analyzed. Methods: Firstly, in a human in vitro model, human cardiomyocytes co-cultured with hPBMC were exposed to ICIs (with CTLA-4 or PD-1 blocking agents, at 200 nM) for 72 h. After treatment, production of DAMPs and 12 cytokines were analyzed in the supernatant through colorimetric and enzymatic assays. C57/Bl6 mice were treated with CTLA-4 or PD-1 blocking agents (15 mg/kg) for 10 days. Before (T0), after three days (T3) and after treatments (T10), ejection fraction, fractional shortening, radial and longitudinal strain were calculated by using bidimensional echocardiography (Vevo 2100, Fujfilm). Fibrosis, necrosis, hypertrophy and vascular NF-kB expression were analyzed through Immunohistochemistry. Myocardial expression of DAMPs (S100- Calgranulin, Fibronectin and Galectine-3), MyD88, NLRP3 and twelve cytokines have been analyzed. Systemic levels of SDF-1, IL-1ß, and IL-6 were analyzed before, during and after ICIs therapy. Results: Radial and longitudinal strain were decreased after 10 days of ICIs therapy. Histological analysis of NF-kB expression shows that short-term anti-CTLA-4 or anti-PD-1 treatment increased vascular and myocardial inflammation. No myocardial hypertrophy was seen with the exception of the pembrolizumab group. Myocardial fibrosis and expression of galectin-3, pro-collagen 1-α and MMP-9 were increased after treatment with all ICIs. Both anti-CTLA-4 or anti-PD-1 treatments increased the expression of DAMPs, NLRP3 inflammasome and MyD88 and induced both in vitro and in vivo the secretion of IL-1ß, TNF-α and IL-6. Systemic levels of SDF-1, IL-1ß and IL-6 were increased during and after treatment with ICIs. Conclusions: Short therapy with PD-1 and CTLA-4 blocking agents increases vascular expression of NF-kB, systemic SDF-1, IL-1ß, IL-6 levels and myocardial NLRP3, MyD88 and DAMPs expression in preclinical models. A pro-inflammatory cytokine storm was induced in myocardial tissues and in cultured cardiac cells after ICIs therapy. The overall picture of the study suggests new putative biomarkers of ICIs-mediated systemic and myocardial damages potentially useful in clinical cardioncology.

Metastatic colorectal cancer and type 2 diabetes: prognostic and genetic interactions.

The present study was undertaken to analyze prognostic and genetic interactions between type 2 diabetes and metastatic colorectal cancer. Patients' survival was depicted through the Kaplan-Meier product limit method. Prognostic factors were examined through the Cox proportional-hazards regression model, and associations between diabetes and clinical-pathologic variables were evaluated by the χ2 test. In total, 203 metastatic colorectal cancer patients were enrolled. Lymph nodes (P = 0.0004) and distant organs (> 2 distant sites, P = 0.0451) were more frequently involved in diabetic patients compared with those without diabetes. Diabetes had an independent statistically significant negative prognostic value for survival. Highly selected patients with cancer and/or diabetes as their only illness(es) were divided into three groups: (a) seven oligo-metastatic patients without diabetes, (b) 10 poly-metastatic patients without diabetes, and (c) 12 poly-metastatic diabetic patients. These groups of patients were genetically characterized through the Illumina NovaSeq 6000 (San Diego, CA, USA) platform and TruSigt™Oncology 500 kit, focusing on genes involved in diabetes and colorectal cancer. Gene variants associated with diabetes and cancer were more frequent in patients in group 3. We found that type 2 diabetes is a negative prognostic factor for survival in colorectal cancer. Diabetes-associated gene variants could concur with malignancy, providing a rational basis for innovative models of tumor progression and therapy.