Prosthetic valve endocarditis (PVE) is a serious infection associated with high mortality that often requires surgical treatment. Study on clinical characteristics and prognosis of a large ...contemporary prospective cohort of prosthetic valve endocarditis (PVE) that included patients diagnosed between January 2008 and December 2020. Univariate and multivariate analysis of factors associated with in-hospital mortality was performed. The study included 1354 cases of PVE. The median age was 71 years with an interquartile range of 62-77 years and 66.9% of the cases were male. Patients diagnosed during the first year after valve implantation (early onset) were characterized by a higher proportion of cases due to coagulase-negative staphylococci and Candida and more perivalvular complications than patients detected after the first year (late onset). In-hospital mortality of PVE in this series was 32.6%; specifically, it was 35.4% in the period 2008-2013 and 29.9% in 2014-2020 (p = 0.031). Variables associated with in-hospital mortality were: Age-adjusted Charlson comorbidity index (OR: 1.15, 95% CI: 1.08-1.23), intracardiac abscess (OR:1.78, 95% CI:1.30-2.44), acute heart failure related to PVE (OR: 3. 11, 95% CI: 2.31-4.19), acute renal failure (OR: 3.11, 95% CI:1.14-2.09), septic shock (OR: 5.56, 95% CI:3.55-8.71), persistent bacteremia (OR: 1.85, 95% CI: 1.21-2.83) and surgery indicated but not performed (OR: 2.08, 95% CI: 1.49-2.89). In-hospital mortality in patients with surgical indication according to guidelines was 31.3% in operated patients and 51.3% in non-operated patients (p<0.001). In the latter group, there were more cases of advanced age, comorbidity, hospital acquired PVE, PVE due to Staphylococcus aureus, septic shock, and stroke. Not performing cardiac surgery in patients with PVE and surgical indication, according to guidelines, has a significant negative effect on in-hospital mortality. Strategies to better discriminate patients who can benefit most from surgery would be desirable.
Liquid biopsy has proven valuable in identifying individual genetic alterations; however, the ability of plasma ctDNA to capture complex tumor phenotypes with clinical value is unknown. To address ...this question, we have performed 0.5X shallow whole-genome sequencing in plasma from 459 patients with metastatic breast cancer, including 245 patients treated with endocrine therapy and a CDK4/6 inhibitor (ET + CDK4/6i) from 2 independent cohorts. We demonstrate that machine learning multi-gene signatures, obtained from ctDNA, identify complex biological features, including measures of tumor proliferation and estrogen receptor signaling, similar to what is accomplished using direct tumor tissue DNA or RNA profiling. More importantly, 4 DNA-based subtypes, and a ctDNA-based genomic signature tracking retinoblastoma loss-of-heterozygosity, are significantly associated with poor response and survival outcome following ET + CDK4/6i, independently of plasma tumor fraction. Our approach opens opportunities for the discovery of additional multi-feature genomic predictors coming from ctDNA in breast cancer and other cancer-types.
Although chemotherapy is the cornerstone treatment for patients with metastatic colorectal cancer (mCRC), acquired chemoresistance is common and constitutes the main reason for treatment failure. ...Monoclonal antibodies against insulin-like growth factor-1 receptor (IGF-1R) have been tested in pre-treated mCRC patients, but results have been largely deceiving.
We analysed time to progression, overall survival, and the mutational status of RAS, BRAF and nuclear p-IGF-1R expression by immunohistochemistry, in 470 metastatic CRC patients. The effect of IGF-1R activation and distribution was also assessed using cellular models of CRC and RNAi for functional validation.
Nuclear IGF-1R increased in metastatic tumours compared to paired untreated primary tumours, and significantly correlated with poor overall survival in mCRC patients. In vitro, chemo-resistant cell lines presented significantly higher levels of IGF-1R expression within the nuclear compartment, and PIAS3, a protein implicated also in the sumoylation process of intranuclear proteins, contributed to IGF-1R nuclear sequestration, highlighting the essential role of PIAS3 in this process. Intriguingly, we observed that ganitumab, an IGF-1R blocking-antibody used in several clinical trials, and dasatinib, an SRC inhibitor, increased the nuclear localisation of IGF-1R.
Our study demonstrates that IGF-1R nuclear location might lead to chemotherapy and targeted agent resistance.
Both clinical and genomic data independently predict survival and treatment response in early-stage HER2-positive breast cancer. Here we present the development and validation of a new HER2DX risk ...score, and a new HER2DX pathological complete response (pCR) score, both based on a 27-gene expression plus clinical feature-based classifier.
HER2DX is a supervised learning algorithm incorporating tumour size, nodal staging, and 4 gene expression signatures tracking immune infiltration, tumour cell proliferation, luminal differentiation, and the expression of the HER2 amplicon, into a single score. 434 HER2-positive tumours from the Short-HER trial were used to train a prognostic risk model; 268 cases from an independent cohort were used to verify the accuracy of the HER2DX risk score. In addition, 116 cases treated with neoadjuvant anti-HER2-based chemotherapy were used to train a predictive model of pathological complete response (pCR); two independent cohorts of 91 and 67 cases were used to verify the accuracy of the HER2DX pCR likelihood score. Five publicly available independent datasets with >1,000 patients with early-stage HER2-positive disease were also analysed.
In Short-HER, HER2DX variables were associated with good risk outcomes (i.e., immune, and luminal) and poor risk outcomes (i.e., proliferation, and tumour and nodal staging). In an independent cohort, continuous HER2DX risk score was significantly associated with disease-free survival (DFS) (p=0·002); the 5-year DFS in the low-risk group was 97·4% (94·4-100·0%). For the neoadjuvant pCR predictor training cohort, HER2DX variables were associated with pCR (i.e., immune, proliferation and HER2 amplicon) and non-pCR (i.e., luminal, and tumour and nodal staging). In both independent test set cohorts, continuous HER2DX pCR likelihood score was significantly associated with pCR (p<0·0001). A weak negative correlation was found between the HER2DX risk score versus the pCR score (correlation coefficient -0·19).
The two HER2DX tests provide accurate estimates of the risk of recurrence, and the likelihood to achieve a pCR, in early-stage HER2-positive breast cancer.
This study received funding from Reveal Genomics, IDIBAPS and the University of Padova.
Tumor cell subpopulations can either compete with each other for nutrients and physical space within the tumor niche, or co-operate for enhanced survival, or replicative or metastatic capacities. ...Recently, we have described co-operative interactions between two clonal subpopulations derived from the PC-3 prostate cancer cell line, in which the invasiveness of a cancer stem cell (CSC)-enriched subpopulation (PC-3M, or M) is enhanced by a non-CSC subpopulation (PC-3S, or S), resulting in their accelerated metastatic dissemination.
M and S secretomes were compared by SILAC (Stable Isotope Labeling by Aminoacids in Cell Culture). Invasive potential in vitro of M cells was analyzed by Transwell-Matrigel assays. M cells were co-injected with S cells in the dorsal prostate of immunodeficient mice and monitored by bioluminescence for tumor growth and metastatic dissemination. SPARC levels were determined by immunohistochemistry and real-time RT-PCR in tumors and by ELISA in plasma from patients with metastatic or non-metastatic prostate cancer.
Comparative secretome analysis yielded 213 proteins differentially secreted between M and S cells. Of these, the protein most abundantly secreted in S relative to M cells was SPARC. Immunodepletion of SPARC inhibited the enhanced invasiveness of M induced by S conditioned medium. Knock down of SPARC in S cells abrogated the capacity of its conditioned medium to enhance the in vitro invasiveness of M cells and compromised their potential to boost the metastatic behavior of M cells in vivo. In most primary human prostate cancer samples, SPARC was expressed in the epithelial tumoral compartment of metastatic cases.
The matricellular protein SPARC, secreted by a prostate cancer clonal tumor cell subpopulation displaying non-CSC properties, is a critical mediator of paracrine effects exerted on a distinct tumor cell subpopulation enriched in CSC. This paracrine interaction results in an enhanced metastatic behavior of the CSC-enriched tumor subpopulation. SPARC is expressed in the neoplastic cells of primary prostate cancer samples from metastatic cases, and could thus constitute a tumor progression biomarker and a therapeutic target in advanced prostate cancer.
infection (CDI) is the main cause of nosocomial diarrhea in developed countries. A key challenge in CDI is the lack of objective methods to ensure more accurate diagnosis, especially when ...differentiating between true infection and colonization/diarrhea of other causes. The main objective of this study was to explore the role of the microbiome as a predictive biomarker of CDI.
Between 2018 and 2021, we prospectively included patients with CDI, recurrent CDI (R-CDI), non-CDI diarrhea (NO-CDI), colonization by
, and healthy individuals. Clinical data and fecal samples were collected. The microbiome was analyzed by sequencing the hypervariable V4 region of the 16S rRNA gene on an Illumina Miseq platform. The mothur bioinformatic pipeline was followed for pre-processing of raw data, and mothur and R were used for data analysis.
During the study period, 753 samples from 657 patients were analyzed. Of these, 247 were from patients with CDI, 43 were from patients colonized with
, 63 were from healthy individuals, 324 were from NOCDI, and 76 were from R-CDI. We found significant differences across the groups in alpha and beta diversity and in taxonomic abundance. We identified various genera as the most significant biomarkers for CDI (
), R-CDI (
), and colonization by
(
).
We observed differences in microbiome patterns between healthy individuals, colonized patients, CDI, R-CDI, and NOCDI diarrhea. We identified possible microbiome biomarkers that could prove useful in the diagnosis of true CDI infections. Further studies are warranted.
In a point-prevalence study performed in 145 Spanish hospitals in 2006, we collected 463 isolates of Staphylococcus aureus in a single day. Of these, 135 (29.2%) were methicillin ...(meticillin)-resistant S. aureus (MRSA) isolates. Susceptibility testing was performed by a microdilution method, and mecA was detected by PCR. The isolates were analyzed by pulsed-field gel electrophoresis (PFGE) after SmaI digestion, staphylococcal chromosomal cassette mec (SCCmec) typing, agr typing, spa typing with BURP (based-upon-repeat-pattern) analysis, and multilocus sequence typing (MLST). The 135 MRSA isolates showed resistance to ciprofloxacin (93.3%), tobramycin (72.6%), gentamicin (20.0%), erythromycin (66.7%), and clindamycin (39.3%). Among the isolates resistant to erythromycin, 27.4% showed the M phenotype. All of the isolates were susceptible to glycopeptides. Twelve resistance patterns were found, of which four accounted for 65% of the isolates. PFGE revealed 36 different patterns, with 13 major clones (including 2 predominant clones with various antibiotypes that accounted for 52.5% of the MRSA isolates) and 23 sporadic profiles. Two genotypes were observed for the first time in Spain. SCCmec type IV accounted for 6.7% of the isolates (70.1% were type IVa, 23.9% were type IVc, 0.9% were type IVd, and 5.1% were type IVh), and SCCmec type I and SCCmec type II accounted for 7.4% and 5.2% of the isolates, respectively. One isolate was nontypeable. Only one of the isolates produced the Panton-Valentine leukocidin. The isolates presented agr type 2 (82.2%), type 1 (14.8%), and type 3 (3.0%). spa typing revealed 32 different types, the predominant ones being t067 (48.9%) and t002 (14.8%), as well as clonal complex 067 (78%) by BURP analysis. The MRSA clone of sequence type 125 and SCCmec type IV was the most prevalent throughout Spain. In our experience, PFGE, spa typing, SCCmec typing, and MLST presented good correlations for the majority of the MRSA strains; we suggest the use of spa typing and PFGE typing for epidemiological surveillance, since this combination is useful for both long-term and short-term studies.
Introduction
Clostridioides difficile infection (CDI) is the main cause of nosocomial diarrhoea in developed countries. Recurrent CDI (R-CDI), which affects 20%-30% of patients and significantly ...increases hospital stay and associated costs, is a key challenge. The main objective of this study was to explore the role of the microbiome and calprotectin levels as predictive biomarkers of R-CDI.
Methods
We prospectively (2019-2021) included patients with a primary episode of CDI. Clinical data and faecal samples were collected. The microbiome was analysed by sequencing the hypervariable V4 region of the 16S rRNA gene on an Illumina Miseq platform.
Results
We enrolled 200 patients with primary CDI, of whom 54 developed R-CDI and 146 did not. We analysed 200 primary samples and found that Fusobacterium increased in abundance, while Collinsella, Senegalimassilia, Prevotella and Ruminococcus decreased in patients with recurrent versus non-recurrent disease. Elevated calprotectin levels correlated significantly with R-CDI (p=0.01). We built a risk index for R-CDI, including as prognostic factors age, sex, immunosuppression, toxin B amplification cycle, creatinine levels and faecal calprotectin levels (overall accuracy of 79%).
Discussion
Calprotectin levels and abundance of microbial genera such as Fusobacterium and Prevotella in primary episodes could be useful as early markers of R-CDI. We propose a readily available model for prediction of R-CDI that can be applied at the initial CDI episode. The use of this tool could help to better tailor treatments according to the risk of R-CDI.
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