Nocardia nova (N. nova) is a Gram-positive aerobic actinomycete and a rare pathogen that can cause severe infections, particularly in immunocompromised patients.

We report here a rare case of N. nova bacteremia combined with viral pneumonia in a 54-year-old woman who underwent a modified radical mastectomy for breast cancer. Post-surgery, she developed high fever and lung inflammation. Initial empirical therapy with levofloxacin was administered for the pulmonary infection. Upon identification of N. nova through blood cultures and antibiotic susceptibility testing (AST), treatment was switched to trimethoprim-sulfamethoxazole (TMP-SMX) and imipenem/cilastatin, which led to initial improvement. However, the patient relapsed and required an additional six months of antibiotics to achieve full recovery.

Establishing a diagnosis of nocardiosis is a precondition for successful antibiotic therapy. Nocardia bacteremia is a rare event, but it can be confirmed through blood cultures. Our report underscores the pathogenic potential of Nocardia species in patients with underlying conditions, highlighting the critical importance of prompt diagnosis and targeted treatment, especially in postoperative cancer patients at risk for co-infections.

There is no standardized classification system for defining segments of colon carcinoma within cancer registries. We aimed to conduct a systematic literature review on studies that specifically address colon cancer and provide definitions for each segment.

Five authors conducted an independent systematic literature search of studies on colon cancer between 01/1992 and 11/2023. Only English-language original articles including cohort studies, case series, previous reviews, meta-analyses, and randomized clinical trials were considered for inclusion. Exclusion criteria were case reports, editorials, and letters. After identifying the relevant studies, those describing particular colon cancer segments were assessed. Whether or not oncologic outcomes were assessed, whether any definitions for particular colon cancer segments were used, were reviewed and extracted.

A total of 9059 articles were screened, and 1143 of them were identified and included in the current study. Out of 1143 included articles, 130 defined the specific colon cancer segment. Distribution of included articles with definition ratios for each segment was as follows: Cecum (n = 2; 2.35%), ascending colon (n = 2; 1.94%), hepatic flexure (n = 2; 33.3%), transverse colon (n = 33; 42.85%), splenic flexure (n = 38; 58.46%), descending colon (n = 16; 8.04%), sigmoid colon (n = 34; 4.99%), and rectosigmoid colon (n = 16; 15.23%). A total of 397 articles reported long-term oncologic outcomes.

Our study unveils discrepancies in the published literature, revealing that nearly 10% of the studies focusing on colon cancer provide various definitions for each colonic segment. Standardizing the definitions of colon cancer segments is essential to prevent the use of arbitrary definitions, which can result in inconsistency and hinder accurate outcome assessments.

Cell growth regulator with EF-hand domain 1 (CGREF1) has been implicated in the upregulation across various cancer types. However, its functional role and clinical relevance in colorectal cancer (CRC) remain poorly characterized. The current study explored the role of CGREF1 in the development and progression CRC.

Bioinformatics analysis was used to examine the expression of CGREF1 in various malignancies, including CRC. Immunohistochemistry (IHC) and Quantitative real-time PCR (qRT-PCR) were performed to determine the expression of CGREF1 in CRC tissues. In vitro proliferation and invasion assays, and orthotopic mouse metastatic model were used to analyze the effect of CGREF1 on the development and progression of CRC.

Bioinformatics analyses confirmed significant upregulation of CGREF1 in multiple malignancies, including CRC. qRT-PCR validated these findings by showing a marked increase in CGREF1 mRNA levels in CRC tissues relative to paired normal adjacent tissues. Consistently, IHC evaluations further corroborated these findings, demonstrating that CGREF1 expression was significantly upregulated in human CRC tissues compared to matched adjacent normal intestinal epithelial tissues. Notably, high expression levels of CGREF1 were significantly correlated with aggressive tumor characteristics and poorer prognostic outcomes in CRC patients. Specifically, CGREF1 expression was markedly elevated in high-grade budding (Bd3), highlighting its potential role in this critical process. Knockdown of CGREF1 in CRC cells significantly attenuated the migration capacity in vitro and in vivo, but did not affect cellular proliferation. Furthermore, knockdown of CGREF1 decreased attenuated F-actin polymerization and reduced pseudopodia formation in CRC cells.

Our findings establish CGREF1 as a critical promoter of CRC migration and a potential prognostic biomarker, providing novel insights into the molecular mechanisms underlying CRC metastasis.

High-dose chemotherapy (HDCT) combined with autologous stem cell transplantation (ASCT) rescue is an effective treatment option for relapsed or refractory germ-cell tumors. The TI-CE regimen, consisting of paclitaxel and ifosfamide for stem cell mobilization followed by high dose carboplatin and etoposide with ASCT rescue, is frequently used in the treatment of refractory disease. This regimen is challenging in patients who have undergone unilateral nephrectomy, since potential nephrotoxicity of ifosfamide poses a serious risk for permanent damage of the preserved kidney. Currently, the literature lacks data on the substitution of ifosfamide in the TI-CE regimen for an alternative chemotherapeutic agent with equivalent potency while being less nephrotoxic.

We present a case of a patient with refractory progressive metastatic germ-cell tumor who underwent nephrectomy and was successfully treated with a modified chemo-mobilization strategy. In the TI-CE protocol, ifosfamide was replaced for cyclophosphamide (TC-CE), resulting in a sufficient stem cell harvest through a single apheresis session. Post chemo-mobilization, LDH and hCG + hCGβ levels were normalized. Renal function remained stable throughout the course of treatment. Two months after HDCT, the patient showed a complete metabolic response, with no detectable tumor remnants. Currently, one year post-therapy, there are no signs of disease recurrence.

An effective and potentially less nephrotoxic chemo-mobilization regimen, using paclitaxel and cyclophosphamide (TC-CE), was administered to a patient with refractory metastatic germ-cell tumor who underwent HDCT followed by ASCT rescue after unilateral nephrectomy. Cyclophosphamide demonstrated to be a viable substitute for ifosfamide within the TI-CE regimen.

Pathology diagnosis of colorectal cancer is time-consuming and requires a high level of expertise. However, it is an essential step towards establishing the adequate treatment. The need to analyse a large number of these histopathological images calls for automatic tools capable of aiding pathologists in this arduous task. Deep learning techniques, together with the wealth of data available nowadays, provide a promising candidate for such job. Adopting state-of-the-art artificial intelligence algorithms, we developed a model to accurately detect colorectal cancer in digitalised histopathological whole-slide images. Our end-to-end approach uses the principles of multiple-instance learning combined with deep convolutional neural networks in order to fully leverage the information contained within each image and make robust predictions at the patient's level. The model also allows to highlight the areas in the slide most likely to harbour tumour tissue. Given the finite computational resources available, working at maximum resolution can be detrimental. Therefore, we explored the impact of lowering the working image resolution. The algorithms were trained and validated on a subset of more than 1300 patients of the Molecular Epidemiology of Colorectal Cancer study with histopathology images available. These images gave rise to [Formula: see text] tiles of [Formula: see text] pixels each. Once we identified the best-performing model we put it to the test on images from The Cancer Genome Atlas. We obtained the best outcomes working at 4 μm/pix, achieving the following metrics on the test dataset: F1-Score of 0.96, a Matthews correlation coefficient of 0.92 and an area under the receiver operating characteristic curve of 0.99. These results are exceptional and prove that computational costs can be reduced while keeping the performance up to standard.

Ovarian cancer (OVCA) is third most lethal gynecologic cancers and acquired chemoresistance is the key link in the high mortality rate of OVCA patients. Currently, there are no reliable methods to predict chemoresistance in OVCA. In our study, we identify genes, pathways and networks altered by DNA methylation in high-grade serous ovarian carcinoma (HGSC) cells that are associated with chemoresistance and prognosis of HGSC patients. We performed methylome-wide profiling using Illumina Infinium MethylationEPIC BeadChip (HM850K) methylation array on a set of HGSC chemoresistant and chemosensitive cell lines. Differentially Methylated CpG Probes (DMPs) were identified between the resistant and sensitive groups in HGSC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) over-representation analyses were conducted to identify both common and unique pathways between resistant and sensitive cells. While the HM850K array was used for the discovery phase to identify differentially methylated probes and regions in HGSC cell lines, the publicly available The Cancer Genome Atlas ovarian cancer (TCGA-OV) dataset generated using the Illumina Infinium HumanMethylation27 BeadChip (27 K array) methylation array served as an independent validation cohort for downstream survival and drug sensitivity analyses. Machine learning methods were applied to our dataset to predict drug sensitivity in the TCGA-OV cohort and to investigate associations with overall survival and progression-free survival. Kaplan-Meier analysis was performed to assess the relationship between differentially methylated genes and patient survival outcomes. The overlapping CpG probes shared between the two Illumina platforms were used for machine learning and survival analyses. Data visualization was performed using various R/Bioconductor packages. Our analysis identified a total of 3,641 DMPs spanning 1,617 differentially methylated genes between chemoresistant and sensitive HGSC cells, whereas 80% of them were hypermethylated CpG sites associated with HGSC resistant cells. Approximately half of the DMPs were distributed on chromosomes 1-3, 6, 11-12 and 17 and top identified hypermethylated CpGs were cg21226224 (SOX17, ∆β = 79%, adj.P = 7.73E-03), cg02538901 (ATP1A1, ∆β = 75%, adj.P = 7.6E-03), and cg17032184 (CD58, ∆β = 64%, adj.P = 4.39E-02). Machine learning analysis identified significant association of global hypermethylation in the HGSC chemoresistant cells with poor overall and progression-free survival of HGSC patients. Further analysis identified four differentially methylated genes (CD58, SOX17, FOXA1, ETV1) that were also positively associated with poor prognosis of HGSC OC patients. Functional enrichment analysis showed enrichment of several cancer-related pathways, including phosphatidylinositol signaling, homologous recombination and ECM-receptor interaction pathways. This study supplements the current knowledge of the underlying mechanism behind acquired chemoresistance in OVCA. Four differentially methylated genes identified in this study may have the potential to serve as promising epigenetic clinical biomarkers for HGSC chemotherapy resistance.

The accumulation of regulatory T cells (Tregs) in the tumor microenvironment is a key factor for immunosuppression and immune escape of cancer cells. Genistein is a natural isoflavonoid in soybeans, possessing a wide range of pharmacological bioactivities. However, the immunomodulatory potential of genistein remains largely unexplored. This study investigated the synergistic efficacy of genistein with anti-PD-1 therapy in a mouse model of melanoma. The regulatory role of genistein in Treg differentiation and functional stability was also examined in this study. The antitumor effects of genistein, alone or in combination with anti-PD-1 therapy, were evaluated in the mouse B16-F10 melanoma model. The profiles of intratumoral Tregs and CD8⁺ cytotoxic T cells were profiled using flow cytometry. The impact of genistein on the suppressive function and differentiation of Tregs was also studied in vitro. RT-qPCR, Western blotting and flow cytometry were conducted to characterize the functional phenotype of Tregs under genistein treatment. Genistein showed a synergistic effect with anti-PD-1 therapy in B16-F10 melanoma models, achieving enhanced immune infiltration and functional reprogramming of the tumor microenvironment. This combinatorial strategy not only reduced intratumoral Tregs but also elevated the CD8⁺/Treg ratio. At the mechanistic level, genistein effectively suppressed critical Treg surface markers, which are indispensable for Treg-mediated immunosuppression. Furthermore, it disrupted Treg differentiation by attenuating PI3K/AKT signaling phosphorylation. Our data demonstrated that genistein boosts the antitumor effect of anti-PD-1 therapy by impairing the immunosuppressive function and differentiation of Tregs, indicating that genistein has the potential to enhance the treatment outcome of the immune checkpoint inhibitor.

Glioblastoma, IDH wild-type (WHO grade 4) (GBM), is the most common primary brain tumor in adults with a 21-month median overall survival, despite surgical-resection and radio-chemotherapy. Bevacizumab, a monoclonal antibody towards vascular endothelial growth factor-A, is used to treat recurrent-GBM. To find predictors of poor-response, patient-derived xenograft (PDX)-tumors were treated with bevacizumab or vehicle and subsequently grouped based on survival-response; RNAseq expression was then compared by responder-status. Bioinformatic-analysis demonstrated differential gene expression in tumors from poor-responders (six-PDXs) as compared to tumors from good-responders (three-PDXs), along with upregulation of angiogenesis and collagen gene-sets in poor-responders. Within these gene-sets, multiple genes known to be regulated by the early growth response-1 (EGR1) transcription factor, which was also upregulated, were identified and CHRNA7 (α7-nicotinic-acetylcholine receptor, α7-nAChR) was selected for validation. In terms of protein/functional studies, in the bevacizumab-treated poor-responders, nuclear-EGR1 was elevated, Ki67-labeling was increased in EGR1^high tumor, and there was increased angiogenesis. Expression of α7-nAChR and nuclear EGR1 was directly correlated, suggesting CHRNA7 is an EGR1 downstream target. Data-mining (GLASS-database) showed that recurrent GBM in females with an elevated EGR1 and methylated MGMT promoter had a shorter survival. In summary, GBM with increased EGR1 expression, Ki67-labeling in EGR1^high tumor and angiogenesis demonstrated a poor-response to bevacizumab, suggesting EGR1 could be useful in predicting response.

BRD4 ("Bromodomain-containing protein 4"), a recognized gene regulator, is an attractive target for therapeutic development, particularly for the management of neuroblastoma. An integrated pharmacoinformatic strategy for the development of new BRD4 inhibitors is examined in this research. Pharmacophores were used to digitally screen five databases, and the current study aims to determine the best binding modes by docking the screened hits to the BRD4 active site. Using the BRD4 protein co-crystal ligand (73B) (PDB ID: 4BJX) as a template, pharmacophore hypotheses were produced. Five databases were subjected to a pharmacophore-based virtual screening process, and 1089 hits that satisfied the screening requirements were selected for docking against the BRD4 receptor by using the SP module of the Glide tool. The top ten docked compounds with the highest binding affinities, ranging from - 9.623 to - 8.894 kcal/mol, were selected. Further, the biological activity and ADMET analysis revealed that the selected compounds have values that fall in the acceptable range. The protein-ligand complexes' stability was verified by performing molecular dynamics (MD) simulations of the binding positions of the top two compounds against the BRD4 receptor. The stability and binding free energies of the compounds indicate that these compounds may function as lead compounds to affect the biological activity of BRD4 in the in vitro studies.

The aim of this study was to assess the immunohistochemical expression of second-generation neuroendocrine markers such as insulin gene enhancer protein 1, insulinoma-associated protein 1, and secretagogin in pheochromocytoma and their prognostic value.

The study included 30 operated pheochromocytoma patients. The tissue preparations were re-evaluated by two pathologists, and Pheochromocytoma of the Adrenal Gland Scaled Score score and Grading System for Adrenal Pheochromocytoma and Paraganglioma score were given. Four μm-thick paraffin block sections were stained with insulinoma-associated protein 1, insulin gene enhancer protein 1, and secretagogin antibodies to obtain staining intensity score, staining percentage, and H-score.

The mean age at diagnosis was 50.5 (±15.9) years. The most common complaint was high blood pressure. A total of four patients (13.3%) had a nonfunctioning adenoma. The lesions were mostly localized in the right adrenal gland, and the median tumor size was 45.0 (35.0-54.2) mm. The median Ki67 proliferation index was 2.0% (0.9-3.0). According to the Pheochromocytoma of the Adrenal Gland Scaled Score score, nine (30.0%) patients showed the benign clinical behavior (score <4), while according to the Grading System for Adrenal Pheochromocytoma and Paraganglioma score, only four (13.3%) patients were in the well-differentiated-type (0-2 points) group. insulinoma-associated protein 1 and insulin gene enhancer protein 1 were positive in 21 (70%) and 26 (86.7%) of the patients, respectively. However, secretagogin was positive only in six patients (20%). Among the second-generation neuroendocrine immunohistochemical markers, insulin gene enhancer protein 1 had the highest H-score. Correlation analysis showed a negative correlation between insulin gene enhancer protein 1 and tumor Hounsfield unit and a positive correlation between insulinoma-associated protein 1 and Ki67 proliferation index.

Insulinoma-associated protein 1, insulin gene enhancer protein 1, and secretagogin, which are second-generation neuroendocrine immunohistochemical markers, can be used in the differential diagnosis of pheochromocytoma. Notably, insulinoma-associated protein 1 may also have prognostic significance.