Novel CAF-identifiers via transcriptomic and protein level analysis in HNSC patients.

Cancer-associated fibroblasts (CAFs), a prominent component of the tumor microenvironment, play an important role in tumor development, invasion, and drug resistance. The expression of distinct "CAF-markers" which separates CAFs from normal fibroblasts and epithelial cells, have traditionally been used to identify them. These commonly used CAF-markers have been reported to differ greatly across different CAF subpopulations, even within a cancer type. Using an unbiased -omic approach from public data and in-house RNAseq data from patient derived novel CAF cells, TIMP-1, SPARC, COL1A2, COL3A1 and COL1A1 were identified as potential CAF-markers by differential gene expression analysis using publicly available single cell sequencing data and in-house RNAseq data to distinguish CAF populations from tumor epithelia and normal oral fibroblasts. Experimental validation using qPCR and immunofluorescence revealed CAF-specific higher expression of TIMP-1 and COL1A2 as compared to other markers in 5 novel CAF cells, derived from patients of diverse gender, habits and different locations of head and neck squamous cell carcinoma (HNSC). Upon immunohistochemical (IHC) analysis of FFPE blocks however, COL1A2 showed better differential staining between tumor epithelia and tumor stroma. Similar data science driven approach utilizing single cell sequencing and RNAseq data from stabilized CAFs can be employed to identify CAF-markers in various cancers.

Estimation of ALU Repetitive Elements in Plasma as a Cost-Effective Liquid Biopsy Tool for Disease Prognosis in Breast Cancer.

BACKGROUND: Liquid biopsy is widely recognized as an efficient diagnostic method in oncology for disease detection and monitoring. Though the examination of circulating tumor cells (CTC) is mostly implemented for the assessment of genomic aberrations, the need of complex methodologies for their detection has impeded its acceptance in low-resource settings. We evaluated cell-free DNA (cfDNA) as a liquid biopsy tool and investigated its utility in breast cancer patients. METHODS: Total cell-free DNA was extracted from the plasma of breast cancer patients (n = 167) with a median follow-up of more than 5 years, at various stages of the disease. Quantitative PCR was performed to estimate the copy numbers of two fractions of ALU repetitive elements (ALU 115 and ALU 247), and DNA integrity (DI) was calculated as the ratio of ALU 247/115. Mutations in TP53 and PIK3CA in the cfDNA were estimated by next-gen sequencing (NGS) in a subset of samples. Associations of the levels of both the ALU fragments with various clinico-pathological factors and disease-free survival at various stages were examined. Nomogram models were constructed with clinical variables and ALU 247 levels to predict disease-free survival and the best performing model was evaluated by decision curve analysis. RESULTS: DI and ALU 247 levels were significantly lower (p < 0.0001) in the post-operative plasma when compared to their pre-surgery levels. DI and ALU 247 were found to be significantly higher in patients with metastasis (p < 0.05). Patients with higher levels of ALU 247 in their post-operative plasma had significant poor disease-free survival (p = 0.005). Higher levels of ALU 247 in the circulation also correlated with low tumor-infiltrating lymphocytes (TIL) within their primary tumors in the ER-negative breast cancer subtype (p = 0.01). Cox proportional hazard analysis confirmed ALU 247 as an independent variable of disease-free survival both in univariate and multivariate analysis [HR 1.3 (95% CI 1.047 to 1.613, p = 0.017)]. The nomogram model showed that the addition of ALU 247 with other variables significantly improved (C-index 0.823) the predictive ability of the model. CONCLUSION: Our results confirm the utility of cfDNA as an evolving liquid biopsy tool for molecular analysis. Evaluation of larger fragments of cfDNA estimated through ALU 247 can provide vital information concurrent with the pathological process of disease evolution in breast cancer and warrants expansion to other cancer types.

Lipocalin 2 expression promotes tumor progression and therapy resistance by inhibiting ferroptosis in colorectal cancer.

Lipocalin 2 is a siderophore-binding protein that regulates iron homeostasis. Lipocalin 2 expression is elevated in multiple tumor types; however, the mechanisms that drive tumor progression upon Lipocalin 2 expression remain unclear. When Lipocalin 2 is over-expressed, it leads to resistance to 5-fluorouracil in colon cancer cell lines in vitro and in vivo by inhibiting ferroptosis. Lipocalin 2 inhibits ferroptosis by decreasing intracellular iron levels and stimulating the expression of glutathione peroxidase4 and a component of the cysteine glutamate antiporter, xCT. The increase in xCT levels is dependent on increased levels of ETS1 in Lipocalin 2 over-expressing cells. Inhibiting Lipocalin 2 function with a monoclonal antibody leads to a decrease in chemo-resistance and transformation in vitro, and a decrease in tumor progression and chemo-resistance in xenograft mouse models. Lipocalin 2 and xCT levels exhibit a positive correlation in human tumor samples suggesting that the pathway we have identified in cell lines is operative in human tumor samples. These results indicate that Lipocalin 2 is a potential therapeutic target and that the monoclonal antibody described in our study can serve as the basis for a potential therapeutic in patients who do not respond to chemotherapy.

Correlation of Cry1Ac mRNA and protein abundance in transgenic Gossypium hirsutum plant.

Transcription and translation in eukaryotes are distinct processes of the molecular cascade leading to protein production from genetic material. However, establishing correlation between mRNA expression and protein abundance, the end results of the two processes of central dogma, remains a challenge. For transgenic plants, such correlation between mRNA and protein expression serves as a guide to design the transgene, in particular the choices of promoter and codon usage to ensure stable expression of the target protein in relevant tissues under various stress conditions. To elucidate level of mRNA-protein correlation in a commercial transgenic cotton plant Gossypium hirsutum, Bollgard II® (MON15985), we present the results of Cry1Ac protein expression correlating with corresponding mRNA levels. Protein was quantitated using a home-grown validated ELISA assay with a monoclonal-polyclonal antibody pair, whereas mRNA level was detected by a real-time quantitative PCR assay using standardized reference genes. Our results indicate that protein and mRNA levels are highly correlated in the leaves, but not in squares and stem. The correlations seem to be consistent between young and mature leaves and increase over time of harvesting of samples from months 1-3. These findings demonstrate that transcript level measurement could serve as a proxy to protein abundance for this commercially important cotton species, particularly for leaf tissues which are the most vulnerable organs to cotton bollworms and other pathogens. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-021-02828-2.

IL-6 and IL-10 as predictors of disease severity in COVID-19 patients: results from meta-analysis and regression.

AIMS: SARS-CoV-2, an infectious agent behind the ongoing COVID-19 pandemic, induces high levels of cytokines such as IL-1, IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ etc in infected individuals that play a role in the underlying patho-physiology. Nonetheless, exact association and contribution of every cytokine towards COVID-19 pathology remains poorly understood. Delineation of the roles of cytokines during COVID-19 holds the key to efficient patient management in clinics. This study performed a comprehensive meta-analysis to establish association between induced cytokines and COVID-19 disease severity to help in prognosis and clinical care. MAIN METHODS: Scientific literature was searched to identify 13 cytokines (IL-1ß, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-17, TNF-α and IFN-γ) from 18 clinical studies. Standardized mean difference (SMD) for selected 6 cytokines IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ between severe and non-severe COVID-19 patient groups were summarized using random effects model. A classifier was built using logistic regression model with cytokines having significant SMD as covariates. KEY FINDINGS: Out of the 13 cytokines, IL-6 and IL-10 showed statistically significant SMD across studies synthesized. Classifier with mean values of both IL-6 and IL-10 as covariates performed well with accuracy of ~92% that was significantly higher than accuracy reported in literature with IL-6 and IL-10 as individual covariates. SIGNIFICANCE: Simple panel proposed by us with only two cytokine markers can be used as predictors for fast diagnosis of patients with higher risk of COVID-19 disease deterioration and thus can be managed well for a favourable prognosis.

Relative quantification of BCL2 mRNA for diagnostic usage needs stable uncontrolled genes as reference.

Dysregulation of BCL2 is a pathophysiology observed in haematological malignancies. For implementation of available treatment-options it is preferred to know the relative quantification of BCL2 mRNA with appropriate reference genes. For the choice of reference genes-(i) Reference Genes were selected by assessing variation of >60,000 genes from 4 RNA-seq datasets of haematological malignancies followed by filtering based on their GO biological process annotations and proximity of their chromosomal locations to known disease translocations. Selected genes were experimentally validated across various haematological malignancy samples followed by stability comparison using geNorm, NormFinder, BestKeeper and RefFinder. (ii) 43 commonly used Reference Genes were obtained from literature through extensive systematic review. Levels of BCL2 mRNA was assessed by qPCR normalized either by novel reference genes from this study or GAPDH, the most cited reference gene in literature and compared. The analysis showed PTCD2, PPP1R3B and FBXW9 to be the most unregulated genes across lymph-nodes, bone marrow and PBMC samples unlike the Reference Genes used in literature. BCL2 mRNA level shows a consistent higher expression in haematological malignancy patients when normalized by these novel Reference Genes as opposed to GAPDH, the most cited Reference Gene. These reference genes should also be applicable in qPCR platforms using Taqman probes and other model systems including cell lines and rodent models. Absence of sample from healthy-normal individual in diagnostic cases call for careful selection of Reference Genes for relative quantification of a biomarker by qPCR.BCL2 can be used as molecular diagnostics only if normalized with a set of reference genes with stable yet low levels of expression across different types of haematological malignancies.

Genome wide search to identify reference genes candidates for gene expression analysis in Gossypium hirsutum.

BACKGROUND: Cotton is one of the most important commercial crops as the source of natural fiber, oil and fodder. To protect it from harmful pest populations number of newer transgenic lines have been developed. For quick expression checks in successful agriculture qPCR (quantitative polymerase chain reaction) have become extremely popular. The selection of appropriate reference genes plays a critical role in the outcome of such experiments as the method quantifies expression of the target gene in comparison with the reference. Traditionally most commonly used reference genes are the "house-keeping genes", involved in basic cellular processes. However, expression levels of such genes often vary in response to experimental conditions, forcing the researchers to validate the reference genes for every experimental platform. This study presents a data science driven unbiased genome-wide search for the selection of reference genes by assessing variation of > 50,000 genes in a publicly available RNA-seq dataset of cotton species Gossypium hirsutum. RESULT: Five genes (TMN5, TBL6, UTR5B, AT1g65240 and CYP76B6) identified by data-science driven analysis, along with two commonly used reference genes found in literature (PP2A1 and UBQ14) were taken through qPCR in a set of 33 experimental samples consisting of different tissues (leaves, square, stem and root), different stages of leaf (young and mature) and square development (small, medium and large) in both transgenic and non-transgenic plants. Expression stability of the genes was evaluated using four algorithms - geNorm, BestKeeper, NormFinder and RefFinder. CONCLUSION: Based on the results we recommend the usage of TMN5 and TBL6 as the optimal candidate reference genes in qPCR experiments with normal and transgenic cotton plant tissues. AT1g65240 and PP2A1 can also be used if expression study includes squares. This study, for the first time successfully displays a data science driven genome-wide search method followed by experimental validation as a method of choice for selection of stable reference genes over the selection based on function alone.