Comprehensive analysis of prognostic value and immune infiltration of kindlin family members in non-small cell lung cancer

Inactivation of kindlin-3 increases human melanoma aggressiveness through the collagen-activated tyrosine kinase receptor DDR1

The role of the focal adhesion protein kindlin-3 as a tumor suppressor and its interaction mechanisms with extracellular matrix constitute a major field of investigation to better decipher tumor progression. Besides the well-described role of kindlin-3 in integrin activation, evidence regarding modulatory functions between melanoma cells and tumor microenvironment are lacking and data are needed to understand mechanisms driven by kindlin-3 inactivation. Here, we show that kindlin-3 inactivation through knockdown or somatic mutations increases BRAFV600mut melanoma cells oncogenic properties via collagen-related signaling by decreasing cell adhesion and enhancing proliferation and migration in vitro, and by promoting tumor growth in mice. Mechanistic analysis reveals that kindlin-3 interacts with the collagen-activated tyrosine kinase receptor DDR1 (Discoidin domain receptor 1) modulating its expression and its interaction with β1-integrin. Kindlin-3 knockdown or mutational inactivation disrupt DDR1/β1-integrin complex in vitro and in vivo and its loss improves the anti-proliferative effect of DDR1 inhibition. In agreement, kindlin-3 downregulation is associated with DDR1 over-expression in situ and linked to worse melanoma prognosis. Our study reveals a unique mechanism of action of kindlin-3 in the regulation of tumorigenesis mediated by the collagen-activated tyrosine kinase receptor DDR1 thus paving the way for innovative therapeutic targeting approaches in melanoma.

The neuroimmune axis of Alzheimer's disease

Alzheimer's disease (AD) is a genetically complex and heterogeneous disorder with multifaceted neuropathological features, including β-amyloid plaques, neurofibrillary tangles, and neuroinflammation. Over the past decade, emerging evidence has implicated both beneficial and pathological roles for innate immune genes and immune cells, including peripheral immune cells such as T cells, which can infiltrate the brain and either ameliorate or exacerbate AD neuropathogenesis. These findings support a neuroimmune axis of AD, in which the interplay of adaptive and innate immune systems inside and outside the brain critically impacts the etiology and pathogenesis of AD. In this review, we discuss the complexities of AD neuropathology at the levels of genetics and cellular physiology, highlighting immune signaling pathways and genes associated with AD risk and interactions among both innate and adaptive immune cells in the AD brain. We emphasize the role of peripheral immune cells in AD and the mechanisms by which immune cells, such as T cells and monocytes, influence AD neuropathology, including microglial clearance of amyloid-β peptide, the key component of β-amyloid plaque cores, pro-inflammatory and cytotoxic activity of microglia, astrogliosis, and their interactions with the brain vasculature. Finally, we review the challenges and outlook for establishing immune-based therapies for treating and preventing AD.

The involvement of an interferon-induced protein 44-like (CgIFI44L) in the antiviral immune response of Crassostrea gigas

Interferon-stimulated genes (ISGs) encoding proteins are the essential executors of interferon (IFN) mediated antiviral defense. In the present study, an ISG member, interferon-induced protein 44-like (IFI44L) gene (designed as CgIFI44L-1) was identified from the Pacific oyster Crassostrea gigas. The ORF of CgIFI44L-1 cDNA was of 1437 bp encoding a polypeptide of 479 amino acids with a TLDc domain and an MMR_HSR1 domain. The mRNA transcripts of CgIFI44L-1 were detected in all the tested tissues with highest level in haemocytes, which was 15.78-fold of that in gonad (p < 0.001). Among the haemocytes, the CgIFI44L-1 protein was detected to be highly expressed in granulocytes with dominant distribution in cytoplasm. The mRNA expression level of CgIFI44L-1 in haemocytes was significantly induced by poly (I:C) stimulation, and the expression level peaked at 24 h, which was 24.24-fold (p < 0.0001) of that in control group. After the treatment with the recombinant protein of an oyster IFN-like protein (rCgIFNLP), the mRNA expression level of CgIFI44L-1 was significantly enhanced at 6 h, 12 h and 24 h, which was 2.67-fold (p < 0.001), 5.44-fold (p < 0.001) and 5.16-fold (p < 0.001) of that in control group, respectively. When the expressions of CgSTAT and CgIFNLP were knocked down by RNA interference (RNAi), the mRNA transcripts of CgIFI44L-1 were significantly down-regulated after poly (I:C) stimulation, which was 0.09-fold (p < 0.001) and 0.06-fold (p < 0.001) of those in EGFP group, respectively. These results suggested that CgIFI44L-1 was a conserved ISG in oyster, which was regulated by CgIFNLP and CgSTAT, and involved in the oyster antiviral immune response.

Joint Secondary Transcriptomic Analysis of Non-Hodgkin's B-Cell Lymphomas Predicts Reliance on Pathways Associated with the Extracellular Matrix and Robust Diagnostic Biomarkers

Approximately 450,000 cases of Non-Hodgkin's lymphoma are annually diagnosed worldwide, resulting in ~240,000 deaths. An augmented understanding of the common mechanisms of pathology among larger numbers of B-cell Non-Hodgkin's Lymphoma (BCNHL) patients is sorely needed. We consequently performed a large joint secondary transcriptomic analysis of the available BCNHL RNA-sequencing projects from GEO, consisting of 322 relevant samples across ten distinct public studies, to find common underlying mechanisms and biomarkers across multiple BCNHL subtypes and patient subpopulations; limitations may include lack of diversity in certain ethnicities and age groups and limited clinical subtype diversity due to sample availability. We found ~10,400 significant differentially expressed genes (FDR-adjusted p-value < 0.05) and 33 significantly modulated pathways (Bonferroni-adjusted p-value < 0.05) when comparing BCNHL samples to non-diseased B-cell samples. Our findings included a significant class of proteoglycans not previously associated with lymphomas as well as significant modulation of genes that code for extracellular matrix-associated proteins. Our drug repurposing analysis predicted new candidates for repurposed drugs including ocriplasmin and collagenase. We also used a machine learning approach to identify robust BCNHL biomarkers that include YES1, FERMT2, and FAM98B, which have not previously been associated with BCNHL in the literature, but together provide ~99.9% combined specificity and sensitivity for differentiating lymphoma cells from healthy B-cells based on measurement of transcript expression levels in B-cells. This analysis supports past findings and validates existing knowledge while providing novel insights into the inner workings and mechanisms of transformed B-cell lymphomas that could give rise to improved diagnostics and/or therapeutics.

Heterogeneous Gene Expression Cross-Evaluation of Robust Biomarkers Using Machine Learning Techniques Applied to Lung Cancer

Background:

Nowadays, gene expression analysis is one of the most promising pillars for understanding and uncovering the mechanisms underlying the development and spread of cancer. In this sense, Next Generation Sequencing technologies, such as RNA-Seq, are currently leading the market due to their precision and cost. Nevertheless, there is still an enormous amount of non-analyzed data obtained from older technologies, such as Microarray, which could still be useful to extract relevant knowledge.

Methods:

Throughout this research, a complete machine learning methodology to cross-evaluate the compatibility between both RNA-Seq and Microarray sequencing technologies is described and implemented. In order to show a real application of the designed pipeline, a lung cancer case study is addressed by considering two detected subtypes: adenocarcinoma and squamous cell carcinoma. Transcriptomic datasets considered for our study have been obtained from the public repositories NCBI/GEO, ArrayExpress and GDC-Portal. From them, several gene experiments have been carried out with the aim of finding gene signatures for these lung cancer subtypes, linked to both transcriptomic technologies. With these DEGs selected, intelligent predictive models capable of classifying new samples belonging to these cancer subtypes have been developed.

Results:

The predictive models built using one technology are capable of discerning samples from a different technology. The classification results are evaluated in terms of accuracy, F1-score and ROC curves along with AUC. Finally, the biological information of the gene sets obtained and their relationship with lung cancer are reviewed, encountering strong biological evidence linking them to the disease.

Conclusion:

Our method has the capability of finding strong gene signatures which are also independent of the transcriptomic technology used to develop the analysis. In addition, our article highlights the potential of using heterogeneous transcriptomic data to increase the amount of samples for the studies, increasing the statistical significance of the results.

Long Noncoding RNA 00472: A Novel Biomarker in Human Diseases

Long non-coding RNAs (lncRNAs) play important roles in human diseases. They control gene expression levels and influence various biological processes through multiple mechanisms. Functional abnormalities in lncRNAs are strongly associated with occurrence and development of various diseases. LINC00472, which is located on chromosome 6q13, is involved in several human diseases, particularly cancers of the breast, lung, liver, osteosarcoma, bladder, colorectal, ovarian, pancreatic and stomach. Importantly, LINC00472 can be used as a biomarker for breast cancer cell sensitivity to chemotherapeutic regimens, including doxorubicin. LINC00472 is regulated by microRNAs and several signaling pathways. However, the significance of LINC00472 in human diseases has not been clearly established. In this review, we elucidate on the significance of LINC00472 in various human diseases, indicating that LINC00472 may be a diagnostic, prognostic as well as therapeutic target for these diseases.

FERMT3 mediates cigarette smoke-induced epithelial-mesenchymal transition through Wnt/β-catenin signaling

Background

Cigarette smoking is a major risk factor for chronic obstructive pulmonary disease (COPD) and lung cancer. Epithelial–mesenchymal transition (EMT) is an essential pathophysiological process in COPD and plays an important role in airway remodeling, fibrosis, and malignant transformation of COPD. Previous studies have indicated FERMT3 is downregulated and plays a tumor-suppressive role in lung cancer. However, the role of FERMT3 in COPD, including EMT, has not yet been investigated.

Methods

The present study aimed to explore the potential role of FERMT3 in COPD and its underlying molecular mechanisms. Three GEO datasets were utilized to analyse FERMT3 gene expression profiles in COPD. We then established EMT animal models and cell models through cigarette smoke (CS) or cigarette smoke extract (CSE) exposure to detect the expression of FERMT3 and EMT markers. RT-PCR, western blot, immunohistochemical, cell migration, and cell cycle were employed to investigate the potential regulatory effect of FERMT3 in CSE-induced EMT.

Results

Based on Gene Expression Omnibus (GEO) data set analysis, FERMT3 expression in bronchoalveolar lavage fluid was lower in COPD smokers than in non-smokers or smokers. Moreover, FERMT3 expression was significantly down-regulated in lung tissues of COPD GOLD 4 patients compared with the control group. Cigarette smoke exposure reduced the FERMT3 expression and induces EMT both in vivo and in vitro. The results showed that overexpression of FERMT3 could inhibit EMT induced by CSE in A549 cells. Furthermore, the CSE-induced cell migration and cell cycle progression were reversed by FERMT3 overexpression. Mechanistically, our study showed that overexpression of FERMT3 inhibited CSE-induced EMT through the Wnt/β-catenin signaling.

Conclusions

In summary, these data suggest FERMT3 regulates cigarette smoke-induced epithelial–mesenchymal transition through Wnt/β-catenin signaling. These findings indicated that FERMT3 was correlated with the development of COPD and may serve as a potential target for both COPD and lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01881-y.