Plakophilin3 Loss Leads to an Increase in PRL3 Levels Promoting K8 Dephosphorylation, Which Is Required for Transformation and Metastasis

The desmosome anchors keratin filaments in epithelial cells leading to the formation of a tissue wide IF network. Loss of the desmosomal plaque protein plakophilin3 (PKP3) in HCT116 cells, leads to an increase in neoplastic progression and metastasis, which was accompanied by an increase in K8 levels. The increase in levels was due to an increase in the protein levels of the Phosphatase of Regenerating Liver 3 (PRL3), which results in a decrease in phosphorylation on K8. The increase in PRL3 and K8 protein levels could be reversed by introduction of an shRNA resistant PKP3 cDNA. Inhibition of K8 expression in the PKP3 knockdown clone S10, led to a decrease in cell migration and lamellipodia formation. Further, the K8 PKP3 double knockdown clones showed a decrease in colony formation in soft agar and decreased tumorigenesis and metastasis in nude mice. These results suggest that a stabilisation of K8 filaments leading to an increase in migration and transformation may be one mechanism by which PKP3 loss leads to tumor progression and metastasis

Fascin overexpression promotes neoplastic progression in oral squamous cell carcinoma

<p>Abstract</p> <p>Background</p> <p>Fascin is a globular actin cross-linking protein, which plays a major role in forming parallel actin bundles in cell protrusions and is found to be associated with tumor cell invasion and metastasis in various type of cancers including oral squamous cell carcinoma (OSCC). Previously, we have demonstrated that fascin regulates actin polymerization and thereby promotes cell motility in K8-depleted OSCC cells. In the present study we have investigated the role of fascin in tumor progression of OSCC.</p> <p>Methods</p> <p>To understand the role of fascin in OSCC development and/or progression, fascin was overexpressed along with vector control in OSCC derived cells AW13516. The phenotype was studied using wound healing, Boyden chamber, cell adhesion, Hanging drop, soft agar and tumorigenicity assays. Further, fascin expression was examined in human OSCC samples (N = 131) using immunohistochemistry and level of its expression was correlated with clinico-pathological parameters of the patients.</p> <p>Results</p> <p>Fascin overexpression in OSCC derived cells led to significant increase in cell migration, cell invasion and MMP-2 activity. In addition these cells demonstrated increased levels of phosphorylated AKT, ERK1/2 and JNK1/2. Our in vitro results were consistent with correlative studies of fascin expression with the clinico-pathological parameters of the OSCC patients. Fascin expression in OSCC showed statistically significant correlation with increased tumor stage (<it>P </it>= 0.041), increased lymph node metastasis (<it>P </it>= 0.001), less differentiation (<it>P </it>= 0.005), increased recurrence (<it>P </it>= 0.038) and shorter survival (<it>P </it>= 0.004) of the patients.</p> <p>Conclusion</p> <p>In conclusion, our results indicate that fascin promotes tumor progression and activates AKT and MAPK pathways in OSCC-derived cells. Further, our correlative studies of fascin expression in OSCC with clinico-pathological parameters of the patients indicate that fascin may prove to be useful in prognostication and treatment of OSCC.</p

Utility of Keratins as Biomarkers for Human Oral Precancer and Cancer

Human oral cancer is the single largest group of malignancies in the Indian subcontinent and the sixth largest group of malignancies worldwide. Squamous cell carcinomas (SCC) are the most common epithelial malignancy of the oral cavity, constituting over 90% of oral cancers. About 90% of OSCCs arise from pre-existing, potentially malignant lesions. According to WHO, OSCC has a 5-year survival rate of 45–60%. Late diagnosis, recurrence, and regional or lymph nodal metastases could be the main causes of the high mortality rates. Biomarkers may help categorize and predict premalignant lesions as high risk of developing malignancy, local recurrence, and lymph nodal metastasis. However, at present, there is a dearth of such markers, and this is an area of ongoing research. Keratins (K) or cytokeratins are a group of intermediate filament proteins that show paired and differentiation dependent expression. Our laboratory and others have shown consistent alterations in the expression patterns of keratins in both oral precancerous lesions and tumors. The correlation of these changes with clinicopathological parameters has also been demonstrated. Furthermore, the functional significance of aberrant keratins 8/18 expression in the malignant transformation and progression of oral tumors has also been documented. This article reviews the literature that emphasizes the value of keratins as biomarkers for the prognostication of human oral precancers and cancers.</jats:p

Versatile hemidesmosomal linker proteins: Structure and function

Hemidesmosomes are anchoring junctions which connect basal epidermal cells to the extracellular matrix. In complex epithelia like skin, hemidesmosomes are composed of transmembrane proteins like α6β4 integrin, BP180, CD151 and cytoplasmic proteins like BPAG1e and plectin. BPAG1e and plectin are plakin family cytolinker proteins which anchor intermediate filament proteins i.e. keratins to the hemidesmosomal transmembrane proteins. Mutations in BPAG1e and plectin lead to severe skin blistering disorders. Recent reports indicate that these hemidesmosomal linker proteins play a role in various cellular processes like cell motility and cytoskeleton dynamics apart from their known anchoring function. In this review, we will discuss their role in structural and signaling functions

Utility of Keratins as Biomarkers for Human Oral Precancer and Cancer

Human oral cancer is the single largest group of malignancies in the Indian subcontinent and the sixth largest group of malignancies worldwide. Squamous cell carcinomas (SCC) are the most common epithelial malignancy of the oral cavity, constituting over 90% of oral cancers. About 90% of OSCCs arise from pre-existing, potentially malignant lesions. According to WHO, OSCC has a 5-year survival rate of 45–60%. Late diagnosis, recurrence, and regional or lymph nodal metastases could be the main causes of the high mortality rates. Biomarkers may help categorize and predict premalignant lesions as high risk of developing malignancy, local recurrence, and lymph nodal metastasis. However, at present, there is a dearth of such markers, and this is an area of ongoing research. Keratins (K) or cytokeratins are a group of intermediate filament proteins that show paired and differentiation dependent expression. Our laboratory and others have shown consistent alterations in the expression patterns of keratins in both oral precancerous lesions and tumors. The correlation of these changes with clinicopathological parameters has also been demonstrated. Furthermore, the functional significance of aberrant keratins 8/18 expression in the malignant transformation and progression of oral tumors has also been documented. This article reviews the literature that emphasizes the value of keratins as biomarkers for the prognostication of human oral precancers and cancers

Near-lossless compression scheme using hamming codes for non-textual important regions in document images

Working at Bell Labs in 1950, irritated with error-prone punched card readers, R W Hamming began working on error-correcting codes, which became the most used error-detecting and correcting approach in the field of channel coding in the future. Using this parity-based coding, two-bit error detection and one-bit error correction was achievable. Channel coding was expanded further to correct burst errors in data. Depending upon the use of the number of data bits ‘d’ and parity bits ‘k’ the code is specified as (n, k) code, here ‘n’ is the total length of the code (d+k). It means that 'k' parity bits are required to protect 'd' data bits, which also means that parity bits are redundant if the code word contains no errors. Due to the framed relationship between data bits and parity bits of the valid codewords, the parity bits can be easily computed, and hence the information represented by 'n' bits can be represented by 'd' bits. By removing these unnecessary bits, it is possible to produce the optimal (i.e., shortest length) representation of the image data. This work proposes a digital image compression technique based on Hamming codes. Lossless and near-lossless compression depending upon need can be achieved using several code specifications as mentioned here. The achieved compression ratio, computational cost, and time complexity of the suggested approach with various specifications are evaluated and compared, along with the quality of decompressed images.</jats:p

Near-lossless compression scheme using hamming codes for non-textual important regions in document images

Working at Bell Labs in 1950, irritated with error-prone punched card readers, R W Hamming began working on error-correcting codes, which became the most used error-detecting and correcting approach in the field of channel coding in the future. Using this parity-based coding, two-bit error detection and one-bit error correction was achievable. Channel coding was expanded further to correct burst errors in data. Depending upon the use of the number of data bits ‘d’ and parity bits ‘k’ the code is specified as (n, k) code, here ‘n’ is the total length of the code (d+k). It means that 'k' parity bits are required to protect 'd' data bits, which also means that parity bits are redundant if the code word contains no errors. Due to the framed relationship between data bits and parity bits of the valid codewords, the parity bits can be easily computed, and hence the information represented by 'n' bits can be represented by 'd' bits. By removing these unnecessary bits, it is possible to produce the optimal (i.e., shortest length) representation of the image data. This work proposes a digital image compression technique based on Hamming codes. Lossless and near-lossless compression depending upon need can be achieved using several code specifications as mentioned here. The achieved compression ratio, computational cost, and time complexity of the suggested approach with various specifications are evaluated and compared, along with the quality of decompressed images

Verification of role of data scanning direction in image compression using fuzzy composition operations

A digital image is a numerical representation of visual perception that can be manipulated according to specifications. In order to reduce the cost of storage and transmission, digital images are compressed. Depending upon the quality of reconstruction, compression methods are categorized as Lossy and Lossless compression. The lossless image compression techniques, where the exact recovery of data is possible, is the most challenging task considering the tradeoff between the compression ratio achieved and the quality of reconstruction. The inherent data redundancies like interpixel redundancy and coding redundancy in the image are exploited for this purpose. The interpixel redundancy is treated by decorrelation using Run-length Encoding, Predictive Coding, and other Transformation Coding techniques. While entropy-based coding can be achieved using Huffman codes, arithmetic codes, and the LZW algorithm, which eliminates the coding redundancy. During the implementation of these sequential coding algorithms, the direction used for data scanning plays an important role. A study of various image compression techniques using sequential coding schemes is presented in this paper. The experimentation on 100 gray-level images comprising 10 different classes is carried out to understand the effect of the direction of scanning of data on its compressibility. Depending upon this study the interrelation between the maximum length of the Run and compression achieved similarly the resultant number of Tuples and compression achieved is reported. Considering the fuzzy nature of these relations, fuzzy composition operations like max-min, min-max, and max-mean compositions are used for decision-making. In this way, a rational comment on which data scanning direction is suitable for a particular class of images is made in the conclusion.</jats:p