ABSTRACT Candida parapsilosis is becoming a predominant non-albicans cause of invasive candidiasis (IC). Echinocandins are the preferred choice for IC treatment and prophylaxis. Resistance to echinocandins in C. parapsilosis has emerged in several countries, but little is known about the susceptibility profile in China or about mechanisms of resistance. Here, we investigated the echinocandin susceptibilities of 2523 C. parapsilosis isolates collected from China and further explored the resistance mechanism among echinocandin-resistant isolates. Anidulafungin exhibited the highest MICs (MIC50/90, 1 and 2 µg/mL; GM, 0.948 µg/mL), while caspofungin showed better activity (0.5 and 1 µg/mL; 0.498 µg/mL). Significantly higher echinocandin MICs were observed among blood-derived isolates compared to others, especially for caspofungin (GM, 1.348 µg/mL vs 0.478 µg/mL). Isolates from ICU and surgical wards also showed higher MICs. Twenty isolates showed intermediate phenotypes for at least one echinocandin. One was resistant to all three echinocandins, fluconazole and voriconazole, which caused breakthrough IC during long-term exposure to micafungin. WGS revealed this isolate carried a mutation S656P in hotspot1 region of Fks1. Bioinformatics analyses suggested that this mutation might lead to an altered protein conformation. CRISPR Cas9-mediated introduction of this mutation into a susceptible reference C. parapsilosis strain increased MICs of all echinocandins 64-fold, with similar results found in the subspecies, C. orthopsilosis and C. metapsilosis. This is the first report of a multi-azole resistant and pan-echinocandin resistant C. parapsilosis isolate, and the identification of a FKS1S656P conferring pan-echinocandin resistance. Our study underscores the necessity of rigorous management of antifungal use and of monitoring for antifungal susceptibility.

Decreased echinocandin susceptibility in Candida parapsilosis causing candidemia and emergence of a pan-echinocandin resistant case in China

Annexins are an extensive superfamily of structurally related calcium- and phospholipid-binding proteins, largely conserved and widely distributed among species. Twelve human annexins have been identified, referred to as Annexin A1-13 (A12 remains as of yet unassigned), whose genes are spread throughout the genome on eight different chromosomes. According to their distinct tissue distribution and subcellular localization, annexins have been functionally implicated in a variety of biological processes relevant to both physiological and pathological conditions. Dysregulation of annexin expression patterns and functions has been revealed as a common feature in multiple cancers, thereby emerging as potential biomarkers and molecular targets for clinical application. Nevertheless, translation of this knowledge to the clinic requires in-depth functional and mechanistic characterization of dysregulated annexins for each individual cancer type, since each protein exhibits varying expression levels and phenotypic specificity depending on the tumor types. This review specifically and thoroughly examines the current knowledge on annexin dysfunctions in carcinogenesis. Hence, available data on expression levels, mechanism of action and pathophysiological effects of Annexin A1-13 among different cancers will be dissected, also further discussing future perspectives for potential applications as biomarkers for early diagnosis, prognosis and molecular-targeted therapies. Special attention is devoted to head and neck cancers (HNC), a complex and heterogeneous group of aggressive malignancies, often lately diagnosed, with high mortality, and scarce therapeutic options.

/pdf/pathobiological-functions-and-clinical-implications-of-3g1voz7q.pdf

Pathobiological functions and clinical implications of annexin dysregulation in human cancers

Simple Summary Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology. Abstract Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.

/pdf/an-integrated-bioinformatics-analysis-towards-the-1o0bviku.pdf

An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

Identifying cancer biomarkers is crucial for improving patient outcomes and reducing cancer-related deaths. This research proposes BioSurv, a framework for biomarker identification and cancer survival prediction, using machine learning and deep learning techniques. Multi-omics data from breast cancer (BRCA) and lung adenocarcinoma (LUAD), including mRNA, miRNA, CNV, and DNA methylation, are analyzed. The collected dataset is passed to statistical tests and the random spatial local best cat swarm optimization (RSLBCSO) algorithm for feature selection, followed by KEGG and survival analyses to identify prognostic markers. Thirteen BRCA and fifteen LUAD poor prognostic markers are identified. A Bayesian optimized deep neural network (DNN) is used for cancer survival prediction, achieving high accuracy of 90% and 91% for BRCA and LUAD, respectively. 

Biomarker identification and cancer survival prediction using random spatial local best cat swarm and Bayesian optimized DNN

Antibiotic tolerance is the ability of a susceptible population to survive high doses of cidal drugs and has been shown to compromise therapeutic outcomes in bacterial infections. In comparison, whether fungicide tolerance can be induced by host-derived factors during fungal diseases remains largely unknown. Here, through a systematic evaluation of metabolite-drug-fungal interactions in the leading fungal meningitis pathogen, Cryptococcus neoformans, we found that brain glucose induces fungal tolerance to amphotericin B (AmB) in mouse brain tissue and patient cerebrospinal fluid via the fungal glucose repression activator Mig1. Mig1-mediated tolerance limits treatment efficacy for cryptococcal meningitis in mice via inhibiting the synthesis of ergosterol, the target of AmB, and promoting the production of inositolphosphorylceramide, which competes with AmB for ergosterol. Furthermore, AmB combined with an inhibitor of fungal-specific inositolphosphorylceramide synthase, aureobasidin A, shows better efficacy against cryptococcal meningitis in mice than do clinically recommended therapies. 

Brain glucose induces tolerance of Cryptococcus neoformans to amphotericin B during meningitis.

Simple Summary Identification of new prognostic biomarkers and therapeutic targets could be essential ways to improve the outcome of bladder cancer (BC) patients. In this study, we comprehensively analyzed the mRNA expression and prognosis of Annexin family members (ANXA1-11, 13) in BC through public analysis tools, including Oncomine, GEPIA2 and our in-house OSblca web server, and found that several Annexins were aberrantly expressed and associated with prognosis in BC. Then, we constructed and validated an Annexin-related prognostic signature (ARPS) in four individual BC cohorts through LASSO and COX regression, indicating that ARPS was an independent prognostic factor for BC. Briefly, our study was to determine the clinical significance of Annexins and provided a potential prognostic model and potential therapeutic targets for BC. Abstract Abnormal expression and dysfunction of Annexins (ANXA1-11, 13) have been widely found in several types of cancer. However, the expression pattern and prognostic value of Annexins in bladder cancer (BC) are currently still unknown. In this study, survival analysis by our in-house OSblca web server revealed that high ANXA1/2/3/5/6 expression was significantly associated with poor overall survival (OS) in BC patients, while higher ANXA11 was associated with increased OS. Through Oncomine and GEPIA2 database analysis, we found that ANXA2/3/4/13 were up-regulated, whereas ANXA1/5/6 were down-regulated in BC compared with normal bladder tissues. Further LASSO analysis built an Annexin-Related Prognostic Signature (ARPS, including four members ANXA1/5/6/10) in the TCGA BC cohort and validated it in three independent GEO BC cohorts (GSE31684, GSE32548, GSE48075). Multivariate COX analysis demonstrated that ARPS is an independent prognostic signature for BC. Moreover, GSEA results showed that immune-related pathways, such as epithelial–mesenchymal transition and IL6/JAK/STAT3 signaling were enriched in the high ARPS risk groups, while the low ARPS risk group mainly regulated metabolism-related processes, such as adipogenesis and bile acid metabolism. In conclusion, our study comprehensively analyzed the mRNA expression and prognosis of Annexin family members in BC, constructed an Annexin-related prognostic signature using LASSO and COX regression, and validated it in four independent BC cohorts, which might help to improve clinical outcomes of BC patients, offer insights into the underlying molecular mechanisms of BC development and suggest potential therapeutic targets for BC.

/pdf/identification-and-validation-of-an-annexin-related-2oia8xi6.pdf

Identification and Validation of an Annexin-Related Prognostic Signature and Therapeutic Targets for Bladder Cancer: Integrative Analysis

Cryptococcus neoformans and its sister species Cryptococcus deuterogattii are important human fungal pathogens. Despite their phylogenetically close relationship, these two Cryptococcus pathogens are greatly different in their clinical characteristics. However, the determinants underlying the regulatory differences of their pathogenicity remain largely unknown. Here, we show that the forkhead transcription factor Hcm1 promotes infection in C. neoformans but not in C. deuterogattii. Monitoring in vitro and in vivo fitness outcomes of multiple clinical isolates from the two pathogens indicates that Hcm1 mediates pathogenicity in C. neoformans through its key involvement in oxidative stress defense. By comparison, Hcm1 is not critical for antioxidation in C. deuterogattii. Furthermore, we identified SRX1, which encodes the antioxidant sulfiredoxin, as a conserved target of Hcm1 in two Cryptococcus pathogens. Like HCM1, SRX1 had a greater role in antioxidation in C. neoformans than in C. deuterogattii. Significantly, overexpression of SRX1 can largely rescue the defective pathogenicity caused by the absence of Hcm1 in C. neoformans. Conversely, Srx1 is dispensable for virulence in C. deuterogattii. Overall, our findings demonstrate that the difference in the contribution of the antioxidant sulfiredoxin to oxidative stress defense underlies the Hcm1-mediated regulatory differences of pathogenicity in two closely related pathogens. 

A forkhead transcription factor contributes to the regulatory differences of pathogenicity in closely related fungal pathogens

Periplakin (PPL) is a main member in plakin family, which plays important role in cellular adhesion complexes supporting and cytoskeletal integrity supplying. PPL was reported to be a potential biomarker candidate for several types of cancers. However, the biological functions and underlying mechanisms of PPL in ovarian cancer (OV) remain unclear. In the present study, we used GEPIA 2, Human Protein Atlas, Oncomine, LinkedOmics, Kaplan-Meier Plotter, STRING, CytoHubba plug-in and TIMER to determine the associations among PPL expression, prognosis, and immune cell infiltration in OV. RT-qPCR and IHC analysis were conducted to validated the role of PPL in an independent OV cohort. Compared with the normal ovary tissues, the levels of PPL mRNA and protein expression were both obviously higher in OV tumors from multiple datasets (P < 0.05), and a poor survival was observed to be strongly correlated with high PPL expression (P < 0.05). Moreover, the results were further validated by RT-qPCR and IHC analysis in an independent OV cohort. A gene-clinical nomogram was constructed, including PPL mRNA expression and clinical factors in TCGA. Functional network analysis suggested that PPL participates in the important pathways like Wnt signaling pathway, MAPK signaling pathway. Ten hub genes (LAMC2, PXN, LAMA3, LAMB3, LAMA5, ITGA3, TLN1, ACTN4, ACTN1, and ITGB4) were identified to be positively associated with PPL. Furthermore, PPL expression was negatively correlated with infiltrating levels of CD4+ T cell, macrophages, neutrophils, and dendritic cells. In conclusion, PPL may be an unfavorable prognostic biomarker candidate in OV, which was also correlated with immune infiltrating and function in immunotherapy response. 

/pdf/prognostic-implications-of-ppl-expression-in-ovarian-cancer-1s2azaaa.pdf

Prognostic implications of PPL expression in ovarian cancer

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Papers

Identification and Validation of an Annexin-Related Prognostic Signature and Therapeutic Targets for Bladder Cancer: Integrative Analysis

A forkhead transcription factor contributes to the regulatory differences of pathogenicity in closely related fungal pathogens

Prognostic implications of PPL expression in ovarian cancer